AMINO PCC EAMSC 2022 Volume 1: Scientific Paper

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Prognostic Value of Early Stage Biomarkers on COVID-19 Severity: A Systematic Review and Meta-Analysis Rasya Azka1, Zahra Rabiatul Z1 , Nadira Putri Nastiti1 , Andiva Nurul Fitri1 1

Faculty of Medicine, Universitas Airlangga, Indonesia

ABSTRACT Introduction: The outbreak of a new coronavirus called SARS-CoV-2, which causes COVID19, has been declared as the global pandemic by WHO in March 2020 and since then this outbreak has a role as the major threat to public health globally.1 The limitation of studies regarding laboratory findings, including hematological and biochemical parameters as the initial screening to predict the prognosis in COVID-19 patients, makes it important to conduct a study review to comprehend the variation and profile of specific biomarker to have the preferred modality to monitor the outcomes of disease. Several early stage biomarkers that could be used as prognostic markers to predict the severity of COVID-19 are plasma suPAR, serum neopterin, serum KL-6, and SP-D. Objective: The aim of this systematic review and meta-analysis is to evaluate the role of early stage biomarkers in predicting the severity prognosis of COVID-19. Furthermore, this study is expected to help the clinicians to identify the probability of disease progression towards severe in COVID-19 patients on admission. Materials and Methods: This meta analysis was reported based on criteria from PRISMA. The literature search was conducted in databases such as MEDLINE, Scopus, and ScienceDirect. Mean Differences (MD) and standard deviation (SD) with the confidence interval of suPAR [0.85, 2.22], KL-6 [0.85,1.57], and SP-D [0.79, 2.7]. Random Effect Model was used based on heterogeneity level and p value of suPAR <0.0001, KL-6 <0.00001, SP-D = 0.0003 was considered statistically significant. Risk of Bias was assessed for each study using QUIPS (Quality in Prognosis Studies) tools. Results: plasma suPAR (pooled SMD = 1.54, 95% CI = 0.85 - 2.22, p < 0.0001), serum KL-6 (pooled SMD = 1.21, 95% CI = 0.85 - 1.57, p < 0.00001), and SP-D (pooled SMD = 1.75, 95% CI = 0.79 - 2.70, p = 0.0003). Conclusion: This systematic review and meta analysis provide evidence that plasma suPAR, serum KL-6, and serum SP-D each have high prognostic value for COVID-19 severity. Keywords: COVID-19, Biomarker, Early stage, Severity, Prognosis


Prognostic Value of Early Stage Biomarkers on COVID-19 Severity: A Systematic Review and Meta-Analysis Asian Medical Students’ Conference 2021

Authors: Rasya Azka Lazuwardi Zahra Rabiatul Zhafira Nadira Putri Nastiti Andiva Nurul Fitri

FACULTY OF MEDICINE UNIVERSITAS AIRLANGGA 2021


Prognostic Value of Early Stage Biomarkers on COVID-19 Severity: A Systematic Review and Meta-Analysis Rasya Azka1, Zahra Rabiatul Z1 , Nadira Putri Nastiti1 , Andiva Nurul Fitri1 1

Faculty of Medicine, Universitas Airlangga, Indonesia

INTRODUCTION The outbreak of a new coronavirus called SARS-CoV-2, which causes COVID-19, has been declared as the global pandemic by WHO in March 2020 and since then this outbreak has a role as the major threat to public health globally.1 First recognized in Wuhan, China, as unexplained cases of pneumonia with zoonotic origin, the virus transmitted from human-tohuman similar to other respiratory pathogens even among the asymptomatic.2 Patients of COVID-19 have a wide range of symptoms, ranging from mild symptoms to severe illness. The most common symptoms are fever, dry cough, and fatigue while other clinical presentations include shortness of breath, muscle or joint pain, headache, loss of taste or smell, diarrhea, and other complications.3 As of November 2021, there had been more than 251 million confirmed cases of COVID-19 including exceeding 5 million deaths and rapidly spread to over 200 countries, territory or area worldwide.4 These numbers are believed to continue to rise further if the intervention of disease isn’t done effectively. Some countries had already experienced the second or third peak infections with the surge number of morbidity and mortality rate while it is still challenging for researchers and clinicians to identify COVID-19 disease severity in patients at the earliest with predictors. The information about biomarkers as diagnostic tools in COVID-19 is still not fully understood. The limitation of studies regarding laboratory findings, including hematological and biochemical parameters as the initial screening to predict the prognosis in COVID-19 patients, makes it important to conduct a study review to comprehend the variation and profile of specific biomarker to have the preferred modality to monitor the outcomes of disease. Several early stage biomarkers that could be used as prognostic markers to predict the severity of COVID-19 are suPAR, neopterin, prealbumin, zinc, and CRP. Some studies have shown that soluble urokinase plasminogen activator receptor (suPAR) is increased in viral infection diseases. As for COVID-19, high level of suPAR indicated that the patient’s immune system is chronically active and leads to weaker response for fighting the disease. Elevated


suPAR were associated with higher risk of intubation in patients confirmed COVID-19, this suggested that elevated suPAR will lead to worse prognosis of COVID-19 severity. SuPAR could also be used for triage in the emergency room by sorting the patients with COVID-19 symptoms without knowing the RT-PCR results.5 Neopterin is a biochemical marker produced by macrophage with stimulation of interferon-gamma which is associated with cell-mediated immunity. Neopterin can be used to predict the severity of disease in COVID-19 cases whereas it reflects the stage of activation of the cellular immune system. In the previous study of SARS patients, serum neopterin levels have already been detected since the first day after the onset of symptoms and rises until the third day.6 OBJECTIVES The aim of this systematic review and meta-analysis is to evaluate the role of early stage biomarkers in predicting the severity prognosis of COVID-19. Furthermore, this study is expected to help the clinicians to identify the probability of disease progression towards severe in COVID-19 patients on admission. METHODS Eligibility Criteria In this review, the authors only include (1) observational study (2) Study population consisted of patients with a confirmed diagnosis of COVID-19 (3) Measured outcome were the prognostic value of biomarker in early stage on COVID-19 severity. Nonetheless, studies were indicated as ineligible if it isn’t available in English, has irrelevant abstract and titles, has non-extractable data, types of

articles such as case series, case reports, review articles, commentary, conference abstracts, editorial letters, and brief reports. Information Sources The search of information was conducted on several electronic databases, such as MEDLINE, Scopus, ScienceDirect. Each database was last searched on 13th November Search Strategy Our data search used published studies from databases such as MEDLINE, Scopus, and ScienceDirect from inception to November 2021. The inclusion criteria are used in the form of articles featuring prognostic value of early stage biomarkers on COVID-19 severity. MeSH terms by MEDLINE were used to identify or refine keywords, synonyms or subject indexing terms to use in the search strategy. The terms used in the electronic databases were described


using Boolean operators. The search was limited to studies published in English. All of these studies were stored in the author’s library in Mendeley. Selection Process The selection process was conducted using automation tools in each database. By using the automation tool, we only include studies from 2019 - 2022 and research articles as the article type. The duplicate records were removed using mendeley. After the duplicates were removed, retrieved records were reviewed by two independent reviewers (RA and ZRZ). Full text articles that are potentially eligible were comprehensively assessed using the eligibility criteria mentioned before. If there are any disparities between the reviewers it will be discussed until the reviewers reach an accord. Data Collection Process and Data Items The data collection process was carried out by a reviewer independently (RA). Selected studies were extracted using Microsoft Excel. The following data were recorded first: author, year, country, study, design, cohort size, mean ± standard deviation, sensitivity, specificity, performance metric used (mean ± SD), cohort size (mean ± SD), p value. all results that were compatible with each outcome domain in each study were sought. Study Risk of Bias Assessment The studies risk of bias were comprehensively assessed using QUIPS (Quality in Prognosis Studies) tools. The studies risk of bias were assessed by two reviewers collaboratively through group discussion (RA and ZRZ). Any disparities between reviewers will be resolved in consensus involving both reviewers. Synthesis Methods Studies that have been reviewed in the systematic review then are grouped into studies that can be pooled quantitatively. There are 4 types of biomarkers that later become 4 groups of metaanalysis: plasma suPAR, serum neopterin, serum KL-6, and surfactant protein D. The data of mean and standard deviation of each biomarker's levels are taken and grouped into severe patient and non-severe patient. Studies that only have median and IQR data are then extrapolated into estimation of mean and SD using a standardized calculator online (https://www.math.hkbu.edu.hk/~tongt/papers/median2mean.html). We conduct the metaanalysis with RevMan 5.4 with continuous types. Heterogeneity test between studies then evaluated using Q test and I2 test and thus determines the model used for analysis; if indicated heterogeneity in the study, the model used is a random-effect model. SMD calculated and then pooled into a forrest plot.


RESULTS AND DISCUSSION Study Selection In this review, we generated 2426 articles from 3 databases (MEDLINE, Scopus, and ScienceDirect) as stated below and 14 articles from hand searching. We used an automation tool and 1080 articles were marked as ineligible. Six duplicates were removed from those databases. Then the author assessed the titles and abstract of 1340 articles, about 1104 records were excluded due to irrelevant title and abstract. Full text was retrieved for 226 reports. Then, the authors assess the report for eligibility, 64 reports were excluded due to its setting of admission wasn’t in the early stage of COVID-19, 3 reports were excluded due to its availability wasn’t in English, 43 reports were excluded because it doesn’t have the outcome of interest, 38 reports were excluded because it doesn’t explain the biomarker as prognostic tool for COVID-19, and 38 reports were excluded due to inappropriate data. All of the hand searched articles were marked as eligible and included in the systematic review. There are a total of 53 studies included for the systematic review and 14 studies included in the MetaAnalysis. Our study selection process is presented in the PRISMA diagram on Figure 1. Table 1. Database Searching Process Results Database

Keywords

Articles

MEDLINE

((COVID-19[MeSH Terms]) AND (Biomarker[MeSH Terms]) AND (Early[MeSH Terms]) AND (Severity[MeSH Terms]) AND (Prognostic[MeSH Terms]))

434

Scopus

(“COVID-19” OR “SARS-CoV-2”) AND “Biomarker” AND “Early stage” AND (“Severity” OR “Prognosis”)

904

Science Direct

(“COVID-19” OR “SARS-CoV-2”) AND “Biomarker” AND “Early stage” AND (“Severity” OR “Prognosis”)

1088


Figure 1. PRISMA 2020 Flow Diagram Study Characteristics and Results of Individual Studies Details of the studies included in this review are displayed in Table 2. In this review, patients with a confirmed diagnosis of COVID-19 served as the subject. Severity prognostic value of the biomarkers is the main focus of this review. Out of 53 studies included in the qualitative synthesis, 39 reports were marked as ineligible because it couldn't be pooled as quantitative data.

Risk of Bias in Studies The quality of the studies were comprehensively assessed using QUIPS (Quality in Prognosis Studies) tools. The studies were classified as low risk of bias as most of the studies did provide adequate information regarding the bias domains judgement. Unclear study participation was seen in Huang, et al. (2020). Unclear confounding measurement and account was seen in Napolitano, et al. (2021) and Tojo, et al. (2020). The risks of bias were summarized in Figure 2.

Study

Study

Prognostic

Outcome

Confoundi

Analysis


Participati on

Azam (2020)

Huang (2020)

Stauning (2021)

Oulhaj (2021)

Arnold (2021)

Rovina (2020)

Napolitano (2021)

Ozger (2020)

Koc (2020)

Attrition

Factor Measurem ent

Measurem ent

ng Measurem ent and Account


Robertson (2020)

Bergantini (2021)

Yamaya (2021)

d’Alessand ro (2020)

Deng (2021)

Awano (2020)

Xue (2020)

Xue (2021)

d’Alessand ro (2021)

Kerget (2020)


Kerget (2020)

Alay (2021)

Tojo (2021)

Tong (2021)

= Low risk of bias;

= Moderate risk of bias;

= High risk of bias


Meta-analysis The quantitative study in this paper compared pooled mean and standard deviation data from two groups: severe as the experimental group and non-severe as the control group. The data then processed in RevMan 5.4 into a pooled standardized mean difference in a forest plot form. We assessed four types of biomarkers that have extractable quantitative data and divided them into four subgroups with each containing from 3 to 8 studies, as seen in Figure 3 (a-d). a.

b.

c.

d.


Figure 3. Forest plot for the pooled standardized mean difference (SMD) and 95% confidence interval (CI) in biomarkers for severe and non-severe COVID-19 patients: a. suPAR; b. Neopterin; c. KL-6; SP-D. Our meta-analysis indicated that plasma suPAR, serum KL-6, and SP-D can be new promising biomarkers to assess COVID-19 patients even in the earliest stage. The p value from the pooled studies all reach significant value. From the results it is seen that in all 4 biomarkers, high levels indicate a more severe condition in the patient. Significant level can be seen in plasma suPAR (pooled SMD = 1.54, 95% CI = 0.85 - 2.22, p < 0.0001), serum KL-6 (pooled SMD = 1.21, 95% CI = 0.85 - 1.57, p < 0.00001), and SP-D (pooled SMD = 1.75, 95% CI = 0.79 - 2.70, p = 0.0003). Serum neopterin does not reveal a significant p value (p = 0.26). This can be explained by the first study by Koc, 2020 that is different from the two other studies. The levels of serum neopterin is higher in the non-severe group. But the follow up of the study revealed that the levels of serum neopterin is indeed both high in the admission stage (even higher in the nonsevere group), but progressly will lower down to the level that the level in the severe group exceeds the non-severe group.

Risk of Bias Across Studies a

b

c

d


Figure 4. Funnel plot for assessing the level of publication bias for each biomarker: a. suPAR; b. Neopterin; c. KL-6; SP-D. Despite the limitations of our study, our results indicate that there are so many biomarkers of severity and prognosis that can be accessed early, even on the first day in the hospital, in COVID-19 patient. Therefore, it should be used to further manage the stages and progress of COVID-19 cases and diagnosis. CONCLUSION AND RECOMMENDATION This systematic review and meta analysis exhibits that there are 21 biomarkers that can be assessed early in COVID-19 patients and 3 that are quantitatively significant: plasma suPAR, serum KL-6, and serum SP-D. Early assessment is really important to prevent progressivity of the disease in patients. Furthermore, we are recommending reviewing the biomarker that can show continuation of mortality in patients that can also accurately assessed early.

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School Reopening during Covid-19 Pandemic: Is It Safe? A Systematic Review Michelle Gunawan1a, Aurielle Annalicia Setiawan1, Ivena Leonita1, Neville1 1

Undergraduate Medical Program, Faculty of Medicine, Brawijaya University 1a

michellegunawann@gmail.com

ABSTRACT Introduction: School closures around the world during the COVID-19 pandemic has brought adverse impacts to students’ learning processes. School reopenings has been implemented in some regions, accompanied with health protocols. Strict implementation of health measures and policies are keys in preventing outbreaks in school settings. It is also necessary to identify precipitating factors in outbreaks to design the most effective health policies. Objective: To review the most effective health policies to prevent outbreaks and identify precipitating factors in outbreaks during school reopenings. Methods: Data was collected from Pubmed, ScienceDirect, Cochrane and ResearchGate from 2020-2021, then assessed according to the PRISMA flow diagram, resulting in 7 studies for qualitative analysis. Risk of bias was assessed using the Joanna-Briggs Institute checklist. Results: Current health measures implemented during the school reopenings are sufficient to reduce attack rates. Student attack rates are lower compared to staff (0.03% vs 4.4%) and older students tend to have higher attack rates (. Some effective health measures are bubbles and mandatory 14-day quarantine before entering schools. Precipitating factors are frequency of school attendance, parents’ occupation as healthcare workers, older age, certain ethnic groups, and positive COVID-19 cases in households. Conclusion: With low transmission and attack rates in students after implementation of health measures, it can be concluded that it is safe to reopen schools as long as proper health protocols are followed. Most effective health measures are wearing masks, hand hygiene, physical distancing, and early restriction to attend school for suspects, while main precipitating factors are frequency of attendance, age, and parents’ occupation.

Keywords: school, reopening, COVID-19, outbreak, transmission, health measures


SCHOOL REOPENING DURING COVID-19 PANDEMIC: IS IT SAFE? A SYSTEMATIC REVIEW

Authors: Michelle Gunawan Aurielle Annalicia Setiawan Ivena Leonita Neville

AMSA-UNIVERSITAS BRAWIJAYA


INTRODUCTION World Health Organization (WHO) has reported over 251 millions of confirmed cases worldwide of novel coronavirus disease 2019 (COVID-19), including 5 millions of deaths in early November 2021. Although several mitigation measures such as health policies have been developed all around the world in order to suppress the transmission rate of SARS-CoV-2 among vulnerable populations, there were still 29,212 new cases emerging as of November 12 th[1]. Likewise, this pandemic does not merely cause major morbidity and mortality in the adult, but also a threat for the younger population. Over 6.5 million children have been confirmed positive for COVID-19 since the onset of the pandemic and remains high as in November 4th[2]. Close contact with infected family members and history of travel or residence in endemic areas were reported to be the main risk factors of SARS-CoV-2 infection in children[3]. During COVID-19 pandemic, many countries have imposed strict lockdown measures, such as school closures in order to restrict the spread of SARS-CoV-2. The closure of educational settings were implemented almost ubiquitously around the world in effort to halt the potential spread, whereas actually this measure has adverse consequences regarding children’s wellbeing, either in social, physical or mental aspects[4,5]. Massive efforts are being made by educational instances at all levels to establish online courses and deliver them through the internet. However, this system imposes students to experience longer screen time and less physical activities which lead to unhealthy lifestyle and decrease of body fitness[6]. Human to human social connections and relationships are also reduced in online learning, making students deprived of the benefits of learning with peers[7]. Besides the disruptions experienced by students itself, recent studies showed that parents would also report a higher level of stress when they experienced more difficulties in supporting their child’s learning compared to pre-pandemic era[8]. These considerations bring up the idea of school reopening along with the implementation of health protocols as a tempting solution. Nonetheless, the chance of contracting COVID-19 in children in school settings cannot be ignored. Although case fatality rates in children are low, low adherence to mask-wearing, handwashing, and physical distancing in children make them susceptible targets for COVID-19 infection and transmission[9]. Unlike adults, children usually have less comorbidities thus making them develop less severe symptoms than adults. However, due to the mild symptoms appearing,


such as fever and cough, or either asymptomatic presentation of COVID-19 cases in children, which are the most frequent, it is more difficult to detect cases and avoid further transmission[10]. Studies reported that children with asymptomatic SARS-CoV-2 infections are potential to be a source of COVID-19 spread to parents and caregivers in various settings, including school, leading to rising hospitalization and bed occupation rate (BOR) for COVID-19 [3,5]. Therefore, knowing the urgency of school reopening in the midst of the pandemic, school and regional health policies become crucial in maintaining a healthy school environment, and preventing outbreaks and further transmission to households and communities. However, there is no systematic review that summarizes the effect of health policies in school reopening settings globally yet. Hence, there is a need to assess the most effective health measures applied in school settings during COVID-19 pandemic. In addition, it is necessary to identify the precipitating factors associated with COVID-19 outbreaks to design the most effective health policies for educational settings.

MATERIALS AND METHODS Search Strategy and Selection Criteria The authors use PRISMA (Preferred Reporting Items for Systematic Reviews and MetaAnalysis) to report the process of this systematic review, which focuses on reporting the transmission of COVID-19 in school settings from 2020 onwards. Search engines used for this review were PubMed, ScienceDirect, Cochrane, and ResearchGate with studies ranging from 2020-2021. Keywords used were: (“COVID-19” OR “SARS-CoV-2”) AND (“Transmission”) AND (“Outbreak”) AND (“School settings” OR “School reopening” OR “Educational settings”). Studies included original research that assessed the transmission of COVID-19 in school settings. All of the authors evaluated the journals individually and differences of opinion between the authors were discussed and eventually resolved. The process of literature search strategy is summarized in the flowchart shown on Figure 1.


Eligibility Criteria for Population-Based Study The authors use the following inclusion criteria for this review: (1) empirical study which showed number of new cases observed and/or attack rate (2) settings and participants are any school or educational setting who apply health protocol for COVID-19; (3) studies were done during the COVID-19 pandemic; (4) The study was published in the last 2 years, from 2020 2021; (5) studies were written in English. Moreover, exclusion criteria includes: (1) studies done outside of school setting; (2) studies done in schools who do not apply the COVID-19 health protocol; (3) studies were not done during the COVID-19 pandemic; (4) full text of the articles not found; (5) not a research article.

Studies Selection Screening and eligibility assessment of studies were based on suitability of topics, title and abstract, and inclusion and exclusion criteria, which were done by authors individually. Complete research articles are compiled in one folder and assessed for eligibility, risk of bias and data extraction. Duplicated articles are excluded and differences of opinion between the authors were discussed and eventually resolved. Flowchart is shown in Figure 1.

Figure 1. Flowchart of study identification and selection based on PRISMA


Data Extraction and Analysis Data extracted from studies found to be eligible are: author’s name, year of publication, settings, study design, duration of study, number of participants, participants characteristics, health protocol used, and outcomes. The authors examined and summarized the study's outcomes. Quality Assessment The quality of this study was evaluated by four reviewers with an equal portion using the Joanna-Briggs Institute (JBI) checklist for cohort and cross-sectional studies. Risk of bias assessed include selection bias, measurement of exposure, confounding variables, missing data, and reporting bias. No articles were excluded from risk of bias assessment. Studies were assessed by 4 authors individually and differences in opinions are discussed until approvals of all authors were gained. Assessments are written in the form of “Yes” and “No”, which counts as 1 point and zero point, respectively. Assessments with a value of 1-11 were considered for cohort studies (points from 9-11 were regarded as high quality studies; 5-8 as medium quality studies; under 5 as low quality studies), while points with a value of 1-8 were considered for cross sectional studies (points from 6-8 were regarded as high quality studies; 3-5 as medium quality studies; under 3 as low quality studies). Detailed assessments are shown in Appendix 1. RESULTS AND DISCUSSION Study Selection and Quality Assessment After a thorough search from PubMed (14), Cochrane (1), ScienceDirect (151), and ResearchGate (43), 26 eligible studies were found. A total of 19 studies were excluded due to its weak presentations and methodology, leaving 7 eligible studies to be included in qualitative and quantitative analysis. All authors agreed on all of the studies being included in this review. All 7 articles were assessed using JBI Critical Appraisal Tools and have shown 6 studies are high quality and 1 study evaluated as medium quality. Detailed assessments are shown in the Attachment 1.

Study Characteristics This systematic review included 7 valid and reliable studies which consisted of 2 case control studies and 5 prospective cohort studies. Five studies were done in Europe, a study was done in Australia, another study was done in America, and no studies were done in Asia and Africa during the literature search. In general, the results of this systematic review were described in these


following tables: studies’ characteristics (shown in Table 1.) and the effect and characteristics of health measures for COVID-19 cases during school openings (shown in Table 2. and Table 3.). Table 1. Study Characteristics Author, year

Gandini et al.,

Gras-Le Guen et

Ladhani et al.,

Buonsenso et al.,

2021

al., 2021

2021

2020

United Kingdom (Derby, East Country, state

Italy

France

London, Manchester,

Italy

North London, Oxford) Center

Multicentre Cross sectional, prospective,

Study design

cohort population-based study

Duration

101 days

Multicentre

Multicentre

Prospective,

Prospective,

cohort

cohort

population-based

population-based

study

study

35 days (week 38

62 days divided

- week 42)

into 3 rounds

8.898.128

11966

Multicentre

Cross sectional, population-based study

-

Preschool: 2.345.829 Elementary: Number of

2.497.067

participants

Middle school: 1.576.182 High school: 2.731.440

1.059 students 291 teachers/staff


Age

Age

Age

Kindergarten (3-6 0–2 years

Primary

years)

years)

3–5 years

Staff

Elementary (6-11 6–10 years years) Population

11–14 years

Middle

years)

school 15–17 years

characteristics (11-14 years)

Role

High school (14- Students, 19 years)

Age (4-12 Nursery Kindergarten (20-≥60 Primary School Middle School High Schools

Role

Role

Students,

Students,

teachers, and staff teachers, and staff teachers, and staff

Role Students, teachers, and staff

JBI score

Yes: 7

Yes: 8

Yes: 11

Yes: 6

No: 4

No: -

No: -

No: 2

Unclear: -

Unclear: -

Unclear: -

Unclear: -

Not applicable: -

Not applicable: 3

Not applicable: -

Not applicable: -

Author, year

Ismail et al., 2020

Country, state

England

Center

Multicentre

Multicentre

Prospective, cross

Prospective, cohort

sectional, population-

population-based

based study

study

-

45 days

Study design

Duration

Larosa et al., 2020 Italy, Regio Emillia province

Macartney et al., 2020

Australia, New South Wales

Multicentre

Prospective, cohort population-based study

100 days


Number of

994 students and 204

928.000

participants

1.448

teachers/staff

Age

Age

Early years (<5 years)

Infant-toddler

Primary School (5-11 and years, grade 1 and 6)

Age centre ECEC (6 weeks - 5 years)

preschool

(0-5 Primary (5-12 years)

years)

Secondary (13 - 18 years)

Secondary School (11- Primary school (6-10 Role Population characteristics

18 yo, grade 10 and 12) years)

Students, teachers, and staff

Mixed Age (primary & Middle school (11-13 secondary school)

years)

Staff

High

Role

years)

school

(14-19

Students, teachers, and Role staff

Students, teachers, and staff

JBI score

Yes: 6

Yes: 11

Yes: 9

No: 2

No: -

No: 2

Unclear: -

Unclear: -

Unclear: -

Not applicable: -

Not applicable: -

Not applicable: -

ECEC: Early Childhood Education and Care Table 2. Health measures implemented in schools or other educational settings where studies were conducted Gandini et al.,

Gras-Le Guen et

Ladhani et al.,

Buonsenso, et al.,

2021

al., 2021

2021

2020

Mask

-

Hand

-

Author, year

washing


Physical

distancing Others

Suspending

Not

extracurricular

children with body distancing, small student per class,

activities,

temperature

minimizing

38°C or higher to clustering of staff diagnosed

crowding

allowing Physical

at attend

entrances

of class

school, and

and daily disinfection (bubbles)

exits

Reduced number

size, if

a

child

is with

students SARS-CoV-2 infection, the class

of tables, floor,

is quarantined for

stationeries,

and

2 weeks, but the

objects,

rest of the school

other ensured

room

ventilation

is

requested

continue

normal

school activities

Author, year

Ismail et al., 2020

Larosa et al., 2020

Macartney et al., 2020

Mask

-

-

Hand washing

-

Physical

distancing

to


Others

Smaller

classes Suspending

separated

Home quarantine for 14 days

into extracurricular

bubbles: a group of activities, minimizing staff and children who crowding at entrances performed

all and exits

activities together and did not interact with other isolate

bubbles

(to

individual

bubbles in 14 days if any member of it develop

COVID-19

while other remaining bubbles continue to attend

educational

setting)

Table 3. Number of new cases and attack rate in students and teachers/staff identified from reopening schools during COVID-19 pandemic

Author, year

Screening tool

Gandini et al.,

Gras-Le Guen

Ladhani et al.,

Buonsenso, D.,

2021

et al., 2021

2021

et al., 2020

Unspecified swab

Antigen swab PCR swab

and blood

PCR swab

sampling

Students

-

-

91/816

-

Teachers/

-

-

209/1381

-

Index cases


staff

Verona

Incidence

Round 1:

Kindergarten:

province

(W38/W42)

91/816

171/236

Students

as 0–2 years: 20.9 / Round 2: 4/487

index cases: 54 Teachers

Round 3:

as 3–5 years: 26.1 / 16/337

index cases: 10

25.9

Non-teaching

6–10

staff Students

25.6

schools: 230/300 Middle schools:

years:

177/208

members 56.0 / 90.5

as index cases: 11–14

Elementary

High

years:

schools:

384/452

0

78.1 / 189.8

Peer

Italy

15–17

Institutions:

years:

Incidence rate 140.1 / 315.6

28/55

Elementary and Number

middle school:

of cases

66/10,000 High

school:

98/10,000 Verona

Incidence

Round 1:

Nursery: 30/236

province

(W38/W42)

209/1381

Elementary

Students index cases: 6 Teachers /staff

Teachers

as 0–2 years: 20.9 / Round 2: 1/767 25.6

as 3–5 years: 26.1 / 35/744

index cases: 6

25.9

Non-teaching

6–10

staff

Middle schools: 20/208 High

years:

members 56.0 / 90.5

as index cases: 11–14 5

Round 3:

schools: 45/300

years:

78.1 / 189.8

schools:

25/452 Peer Institutions: 11/55


15–17

Italy

years:

Incidence rate: 140.1 / 315.6 220/10,000

Number of contacts

-

-

-

Round 1:

17.5%***

Round 2:

Elementary

Round 3: -

-

Kindergarten:

11.15%

0.82%

Students

-

4.74%

schools: 22.2%*** Middle schools: 15.4%*** High

schools:

33.5%***

Attack

Peer

rate

Institutions: 4.1%*** Round 1: 15.13% Teachers/ staff

-

-

Round 2: 0.13% Round 3: 4.70%

-


Author, year

Ismail et al., 2020

Larosa et al., 2020

Macartney et al., 2020

Screening tool

PCR swab

Unspecified swab

PCR swab

97

43

12

162

5

15

Students Index cases Teachers/ staff

Incidence Early

years: teachers)

18/100,000 Primary Students

39 (39 students, 0

Infant-toddler school: centres

6/100,000

and

preschools: 0

19/1448

Number

Secondary school: Primary school: 1

of cases

6.8/100,000

student Secondary

school:

38 students Teachers

Incidence

/staff

27/100,000

0

22/1448

Students

Students

Primary School: 259

Infant-toddler Number of contacts

-

centres

and

preschools:

156

students Primary school: 266 students

Secondary School: 110 ECEC: 183 Teachers/staff Primary School: 18 Secondary School: 28 ECEC: 48


Secondary

school:

572 students Teachers: 199

Infant-toddler centres

and

preschools: 0 Primary Students

-

school: Students to Students:

0.44%

0.3%

Secondary Attack rate

school: Students to Staff: 1.0%

6.64% Total attack rate: 3.9%

Teachers/ staff

Students to Child: 1.5% -

0%

Students to Students: 4.4%

* = p< 0.05, ** = p<0.05, *** = p<0.01. ECEC: Early Childhood Education and Care

Health Policy Intervention Current preventive health measures are done by different countries using their own health policies. Health policies are implemented differently in each setting, but mostly use three main health measures such as using masks, hand hygiene, and physical distancing. 4 out of 7 studies showed incomplete health measures. Studies from Australia and England didn’t specify mask practice and hand hygiene, while a study from Italy did not mention hand hygiene. Other measures taken such as temperature control, unidirectional student flow, natural ventilation, reduced duration of school hours, daily disinfection of school environment, smaller classes, suspending


extracurricular activities, and home quarantine for 14 days for students showing symptoms of flu and COVID-19. Cases are confirmed by using different techniques. Most studies used nasopharyngeal to oropharyngeal swab and PCR to confirm the diagnosis, but 1 out of 7 studies used antigen and 2 out of 7 studies do not specify the method for swabbing.

Health Policy for Prevention of COVID 19 Outbreaks From Table 2. and Table 3., it is summarized that current health measures implemented during the reopening of schools or other educational settings during the COVID-19 pandemic are sufficient to reduce the attack rate. Most studies showed that student attack rates are low. Based on the data, students with higher levels of education and older ages tend to have the highest number of cases and attack rate among all students. It is also stated that attack rates in educational settings were lower than the general population[11]-[17]. Not only students, teachers and school staff are also involved in the transmission of COVID-19. Surprisingly, the incidence rates, attack rates, and transmission rates between staff were found to be higher than students. As reported by Macartney et al., school teachers or staff are most responsible for the transmission of the virus, whether they transmit it to the students or other staff (shown in Figure 2. And Figure 3.)[17]. This can be linked to the degree of compliance to health measures in staff compared to students. There are 2 studies from Ghana and Indonesia that showed only 12,6% and 34,4% adults comply with wearing masks in public places, respectively, while a study in children compliance showed that 56.2% preschool students wear masks and an increasing number of compliance can also be seen in children until secondary grade. Young adults particularly have a lower compliance rate due to no controlled motivation[18,19]. This can also be explained by the number of contacts that children have versus adults. Staff are more susceptible to exposure outside of educational settings, and therefore have to be more vigilant in implementing health measures[15].

Figure 2. COVID-19 transmission trends in educational settings with health measure applied[17].


Children are known to express less ACE2 receptors, as a receptor for COVID-19, compared to adults, therefore making them less susceptible to COVID-19 infections[11]. They also appear to develop better immunity towards COVID-19 from cross-reactivity due to exposure to seasonal coronaviruses[20]. Their cell-mediated immunity, which functions better compared to adults, can develop better responses towards the virus[21]. Children are also reported to primarily interact with individuals with the same age, therefore more time spent in schools may decrease their time spent with susceptible adults[22]. This can explain their low transmission, incidence, and attack rates compared to the staff (shown in Figure 3). Nevertheless, the number of infected staff in educational settings is still considered low compared to the general population. Therefore, it is considered relatively safe to reopen schools during the COVID-19 pandemic, as long as students and staff practice proper health measures. This is supported by the data in Figure 4., which shows that the reopening of schools does not correlate with the incidence of COVID-19 in the general population.

Figure 3. Comparison of incidence rate in school settings vs. the general population[11].

All of the studies have been categorized to three main health measures; using masks, physical distance, and hand hygiene. Other health measures such as reducing school duration and school staff are different for each study. In our results, the United Kingdom has applied unique physical distancing measures such as bubbles, where small groups of staff and students do all activities together, separate from other bubbles. If a member of a bubble has been infected, a mandatory 14-day quarantine is applied to all bubble members. This has been beneficial to the


reduction of cases, shown by the low number of secondary cases. In Australia, a mandatory 14day quarantine is applied before entering schools. This has resulted in a low number of child-tochild attack rates. On average, a symptomatic patient could transfer the virus to nearly three individuals. In fact, asymptomatic cases are not lower in infectivity either. Similar viral loads are also reported between asymptomatic patients and symptomatic patients. A study also showed that higher number cases of asymptomatic patients are reported and it may jeopardise the efforts in containing COVID-19 outbreaks[23]. So, it is mandatory to take early prevention protocols of index cases that can lead to lower numbers of COVID-19 cases.

Figure 4. Increased incidence of COVID-19 cases do not correlate with school openings[11].

A number of precipitating factors are also identified, such as frequency of school attendance, having parents who work as healthcare workers and older age are also identified. Students that attend school during lockdown are more likely to catch the virus. Those who attend everyday or more than half a week during lockdown are more likely to be infected than other students who did not attend, more than 1 day per week and less than a week. Cases in children with healthcare worker parents are shown to be higher. This may be due to the parents’ more frequent contacts with infected individuals. As for gender differences, boys and girls are affected equally. Some ethnic groups are also more susceptible than the others. Students who have positive COVID-19 cases in households also have an increased positive rate[13].


Although online learning seems to be the only convenient and safe way to continue the learning process during the COVID-19 pandemic, it is not free of disadvantages. Students are more likely to be distracted, frustrated, and confused during online learning compared to regular school. Moreover, online learning is more challenging for some countries than others, especially developing countries. Unequal access to electricity, internet, and electronic devices needed to be able to join online classes are some of the challenges faced by people from developing countries[24]. Teachers are also experiencing some difficulties with online learning. They feel that they lack interaction with their students, classes are less fun and less interactive, and it is difficult to control group interactions[25]. Some parents that are not familiar with modern technology are also complaining about having to set up devices for their children during online learning. Furthermore, having to discipline their children and the inability to guide and teach them during classes are also troublesome for some families. This leads to frustration and stress for parents, and that will affect their children at some point. The reopening of schools can be the solution to these problems that will benefit students, teachers, and parents[26]. This is the first systematic review that defined specifically different health measures in each study, including other measures that are taken by each policy in educational settings. This systematic review assessed different levels of educational settings which can show COVID-19 transmission trends and attack rates. The results are also divided between students and school staff members, to find the potential source of index cases in school settings. There are, however, some limitations of our study. Different methods of swab testing were used in some studies. Four studies identify COVID-19 cases using the PCR swab, one study used antigen swab and blood sampling, and two others used unspecified swab methods. Studies from countries other than Europe and Australia are still lacking and need to be assessed to be generalized. Furthermore, most of the studies showed a decrease in community COVID-19 incidence along with a lower rate of transmission in 2021. This condition has brought the authors into consideration that unexpected situations may emerge when the transmission rate is showing an upward trend in the future. Other external factors, such as individual behaviors and detailed backgrounds (e.g. ethnic groups), were not furtherly explored and discussed. Hence, identifying a broader spectrum of factors determining the outbreak and health measures effectiveness in educational settings in the future studies is necessary.


CONCLUSION AND RECOMMENDATION Observing the recent downward trend of COVID-19 transmission rate and incidences in most of the studies along with some rational urges of educational settings reopening, it is safe to reopen schools supposing that students and other educational-related populations are strictly applying proper health protocols. In this study, we found that wearing masks, hand hygiene, physical distancing, and early restriction to attend school for suspects as the most effective health measures to apply. Frequency of attendance, age, and parents’ occupation were found to be the main precipitating factors in school reopening during the pandemic. The results of this systematic review is expected to be a consideration for further studies and the development of health policies in handling school reopening during COVID-19, especially in other countries where COVID-19 cases have been rapidly decreasing.

ACKNOWLEDGMENT AND CONFLICT OF INTEREST We are grateful to have dr. Nuretha Hevy Purwaningtyas. MSc (FM), Sp.DLP providing the guidance for this systematic review. All authors have no conflict of interest to declare.

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https://www.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-andcovid-19-state-level-data-report/ 3. Alsohime F, Temsah MH, Al-Nemri AM, Somily AM, Al-Subaie S. COVID-19 infection prevalence in pediatric population: Etiology, clinical presentation, and outcome. Journal of infection and public health. 2020 Oct 20. 4. Munro AP, Faust SN. Children are not COVID-19 super spreaders: time to go back to school. Archives of disease in childhood. 2020 Jul 1;105(7):618-9. 5. Viner RM, Russell SJ, Croker H, Packer J, Ward J, Stansfield C, Mytton O, Bonell C, Booy R. School closure and management practices during coronavirus outbreaks including


COVID-19: a rapid systematic review. The Lancet Child & Adolescent Health. 2020 May 1;4(5):397-404. 6. Wang G, Zhang Y, Zhao J, Zhang J, Jiang F. Mitigate the effects of home confinement on children during the COVID-19 outbreak. The Lancet. 2020 Mar 21;395(10228):945-7. 7. Hasan N, Khan NH. ONLINE TEACHING-LEARNING DURING COVID-19 PANDEMIC: STUDENTS’ PERSPECTIVE. The Online Journal of Distance Education and e-Learning. 2020 Oct;8(4):202-13. 8. Spinelli M, Lionetti F, Pastore M, Fasolo M. Parents' stress and children's psychological problems in families facing the COVID-19 outbreak in Italy. Frontiers in psychology. 2020 Jul 3;11:1713. 9. Vermund SH, Pitzer VE. Asymptomatic transmission and the infection fatality risk for COVID-19: Implications for school reopening. Clinical Infectious Diseases. 2021 May 1;72(9):1493-6. 10. Hoang A, Chorath K, Moreira A, Evans M, Burmeister-Morton F, Burmeister F, Naqvi R, Petershack M, Moreira A. COVID-19 in 7780 pediatric patients: a systematic review. EClinicalMedicine. 2020 Jul 1;24:100433. 11. Gandini S, Rainisio M, Iannuzzo ML, Bellerba F, Cecconi F, Scorrano L. A cross-sectional and prospective cohort study of the role of schools in the SARS-CoV-2 second wave in Italy. The Lancet Regional Health-Europe. 2021 Jun 1;5:100092. 12. Gras-Le Guen C, Cohen R, Rozenberg J, Launay E, Levy-Bruhl D, Delacourt C. Reopening schools in the context of increasing COVID-19 community transmission: the French experience. Archives de Pédiatrie. 2021 Apr 1;28(3):178-85. 13. Ladhani SN, Baawuah F, Beckmann J, Okike IO, Ahmad S, Garstang J, Brent AJ, Brent B, Walker J, Andrews N, Ireland G. SARS-CoV-2 infection and transmission in primary schools in England in June–December, 2020 (sKIDs): an active, prospective surveillance study. The Lancet Child & Adolescent Health. 2021 Jun 1;5(6):417-27. 14. Buonsenso D, De Rose C, Moroni R, Valentini P. SARS-CoV-2 infections in Italian schools: preliminary findings after 1 month of school opening during the second wave of the pandemic. Frontiers in pediatrics. 2020;8. 15. Ismail SA, Saliba V, Bernal JL, Ramsay ME, Ladhani SN. SARS-CoV-2 infection and transmission in educational settings: a prospective, cross-sectional analysis of infection


clusters and outbreaks in England. The Lancet Infectious Diseases. 2021 Mar 1;21(3):34453. 16. Larosa E, Djuric O, Cassinadri M, Cilloni S, Bisaccia E, Vicentini M, Venturelli F, Rossi PG, Pezzotti P, Bedeschi E, Reggio Emilia Covid-19 Working Group. Secondary transmission of COVID-19 in preschool and school settings in northern Italy after their reopening in September 2020: a population-based study. Eurosurveillance. 2020 Dec 10;25(49):2001911. 17. Macartney K, Quinn HE, Pillsbury AJ, Koirala A, Deng L, Winkler N, Katelaris AL, O'Sullivan MV, Dalton C, Wood N, Brogan D. Transmission of SARS-CoV-2 in Australian educational settings: a prospective cohort study. The Lancet Child & Adolescent Health. 2020 Nov 1;4(11):807-16. 18. Siahaan AM, Lubis MP, Dalimunthe DA, Nasution MR, Lubis HP. Adherence to face mask and social distancing among residents in Medan during the COVID-19 pandemics. bmj. 2021;10:2414. 19. van Loenhout JA, Vanderplanken K, Scheen B, Van den Broucke S, Aujoulat I. Determinants of adherence to COVID-19 measures among the Belgian population: an application of the protection motivation theory. Archives of Public Health. 2021 Dec;79(1):1-5 20. Ng KW, Faulkner N, Cornish GH, Rosa A, Harvey R, Hussain S, Ulferts R, Earl C, Wrobel AG, Benton DJ, Roustan C. Preexisting and de novo humoral immunity to SARS-CoV-2 in humans. Science. 2020 Dec 11;370(6522):1339-43. 21. McElhaney JE, Kuchel GA, Zhou X, Swain SL, Haynes L. T-cell immunity to influenza in older adults: a pathophysiological framework for development of more effective vaccines. Frontiers in immunology. 2016 Feb 25;7:41. 22. Ludvigsson JF. Children are unlikely to be the main drivers of the COVID‐19 pandemic– a systematic review. Acta Paediatrica. 2020 Aug;109(8):1525-30. 23. Zhao H, Lu X, Deng Y, Tang Y, Lu J. COVID-19: asymptomatic carrier transmission is an underestimated problem. Epidemiology & Infection. 2020;148. 24. Dhawan S. Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems. 2020 Sep;49(1):5-22.


25. Nambiar D. The impact of online learning during COVID-19: students’ and teachers’ perspective. The International Journal of Indian Psychology. 2020 Apr;8(2):783-93. 26. Dong C, Cao S, Li H. Young children’s online learning during COVID-19 pandemic: Chinese parents’ beliefs and attitudes. Children and youth services review. 2020 Nov 1;118:105440.


APPENDIX Appendix 1. Quality assessment of JBI Critical Appraisal Tools

No 1 2 3 4 5 6 7 8 9 10 11

Checklist for Cohort Studies Two groups were similar and recruited from the same population The exposures were measured similarly to assign people to both exposed and unexposed groups The exposure were measured in a valid and reliable way Confounding factors were identified Strategies to deal with confounding factors were stated The groups/participants were free of the outcome at the start of the study (or at the moment of exposure) The outcomes were measured in a valid and reliable way The follow up time was reported and sufficient to be long enough for outcomes to occur The follow up was complete, and if not, the reasons to loss to follow up were described and explored Strategies to address incomplete follow up were utilized Appropriate statistical analysis was used Total Score and Interpretation

Gras-Le Guen et al., 2021

Ladhani et al., 2021

Larosa et al., 2020

Macartney,K. et al., 2020

Gandini et al., 2021

NA

YES

YES

YES

YES

NA

YES

YES

YES

YES

YES YES YES

YES YES YES

YES YES YES

YES NO NO

YES NO NO

NA

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

YES

NO

YES YES

YES YES 11 (High)

YES YES 11 (High)

YES YES

NO YES

9 (High)

7 (Medium)

9 (High)


Checklist for Cross-Sectional Studies

No 1 2 3 4 5 6 7 8

Were the criteria inclusion in the sample clearly defined? Were the study subjects and the setting described in detail? Was the exposure measured in a valid and reliable way? Were objective, standard criteria used for measurement of the condition? Were confounding factors identified? Were strategies to deal with confounding factors stated? Were the outcomes measured in valid and reliable way? Was appropriate statistical analyses used? Total Score and Interpretation

Buonsenso, D., et al., 2020 YES YES YES YES NO NO YES YES 6 (High)

Ismail et al., 2020 YES YES YES YES NO NO YES YES 6 (High)


Addressing Factors Associated with Public Compliance Towards Quarantine Measurements as A Breakthrough Way Fighting Covid-19 Pandemic: A Meta-analysis Ayers Gilberth Ivano Kalaij1, Nathaniel Gilbert Dyson1, Valerie Josephine Dirjayanto1, Stella Kristi Triastari1 1

Faculty of Medicine, Universitas Indonesia

ABSTRACT INTRODUCTION: Quarantine strategy is implemented to prevent COVID-19 transmission and other infectious disease pandemic. Multiple concerns, such as economic, psychological, and social impacts have risen due to the policy which may lead to protocol violation. Low adherence to selfisolation were found (18.2% in the UK and range of 0-93% in a rapid review). OBJECTIVE: Our study aims to assess the factors related to the compliance of stay-at-home policy in order to increase quarantine adherence as breakthrough way of fighting COVID-19. MATERIALS AND METHODS: Systematic search through PubMed, Google Scholar, Cochrane, EBSCO, Medline, and Scopus, were done until 11th November 2021. Critical appraisal of included studies were performed using the JBI I (Joanna Briggs Institute) tools. We analyzed pooled Odds Ratio (OR) and its p-value using fixed effects models. RESULTS AND DISCUSSION: Nine studies of 13,282 subjects were included in this review. Better compliance was significantly associated with unmodifiable factors, namely female sex (OR=1.26[95%CI:1.15-1.37],p<0.00001), 0.90],p=0.0006),

elderly

single

marital

status

(OR=1.01[95%CI:1.01-1.02],p=0.002),

(OR=0.79[95%CI:0.69and

city

residents

(OR=1.19[95%CI:1.03-1.37],p=0.02), and modifiable factors including existing emergency regulations (OR=1.80[95%CI:1.49-2.17],p<0.00001), perception to protect own families (OR=1.67[95% CI:1.25-2.22,p=0.0004]), higher education degree (OR=1.29[95%CI:1.101.52],p=0.002), trust in government (OR=1.44[95%CI:1.33-1.55],p<0.00001), and worry or distress over COVID-19 (OR=1.44[95%CI:1.34-1.56],p<0.00001). We recommend the application of these findings to daily practice by widening broadcast of isolation regulations, ensuring consistent and trustworthy government policies with disease containment along with socioeconomic considerations, and providing better education in efforts to reduce disease spread,


decrease overloaded healthcare burdens, and prepare the public not only during COVID-19 but also for future outbreaks. CONCLUSION: Compliance toward quarantine orders are influenced by several modifiable and unmodifiable factors. We hope that strategies to further increase people compliance toward quarantine may be formulated based on this comprehensive assessment. KEYWORD: Factors Associated, Public Compliance, Quarantine, COVID-19 pandemic, Metaanalysis


Addressing Factors Associated with Public Compliance Towards Quarantine Measurements as A Breakthrough Way Fighting Covid-19 Pandemic: A Meta-analysis Scientific Paper

Author: Ayers Gilberth Ivano Kalaij1, Nathaniel Gilbert Dyson1, Valerie Josephine Dirjayanto1, Stella Kristi Triastari1

1

Faculty of Medicine, Universitas Indonesia

2021


INTRODUCTION On December 31st 2019, WHO’s Country Office was informed on new cases of ‘viral pneumonia’ in Wuhan. The virus was later identified as Sars-CoV-2, which causes the COVID19 disease. Since then, the virus quickly spread to other countries, leading to the World Health Organization (WHO) to characterize it as a pandemic in March 2020.1 According to the official WHO statement, as of 11 November 2021, 251,266,207 confirmed cases of COVID-19 were found globally, among which 5,070,244 died.2 A lot of countries implement social distancing, quarantine, and lockdown strategies to prevent the spread of COVID-19 or any other pandemic. Quarantine itself is defined as the act of staying at home when someone might have been exposed to the virus, while isolation is when someone is infected by the virus, even if he or she is asymptomatic.3 Quarantine has been a powerful strategy related to public health response to infectious diseases. It was proven efficacious during the 2003 severe acute respiratory syndrome pandemic, when quarantine, border controls, contact tracing, and surveillance lead to containment of the global threat around the time of 3 months.4 According to research and previous pandemic, mass quarantine may also flatten the curve of the transmission of the disease. This curve predicts the number of people who will be infected by the virus. The steeper the rise of the curve, the disease is also spread exponentially in a shorter time, which may lead to overloading of the healthcare system.5 Quarantine may also provide protection to the second wave of the pandemic, as shown in Thailand, where the second wave originated from migrants not documented and captured in the quarantine system.6 Although it is considered important, many also question the method. Multiple concerns, such as economic, psychological, and social impacts have risen. Supplies of daily necessities such as food, medicine, and grocery must be ensured. Adverse mental health problems, such as PTSD, anger, avoidance behavior, were also found. Prejudice and discrimination to certain ethnitcity, race, or national origin may also rise due to the quarantine and travel restrictions from certain countries. These objectives may explain the low adherence to self-isolation (18.2% in the UK) and a range of 0-93% of adherence were found in a rapid review.7,8 These differences indicates that quarantine measurement needs to be improve due to lack of considerations of factors associated, thus creating gaps in full implementation and impact from this method in fighting the pandemic itself.5


Recent research have mentioned that there are several factors that are associated with public compliance towards quarantine measurement as a breakthrough way in finding the best quarantine measurement in fighting COVID-19 pandemic. However, to our knowledge, currently no systematic review and meta-analysis specifically assess factors associated with public compliance towards quarantine measurement during COVID-19 pandemic era was present. Thus, we present to you the first systematic review and meta-analysis specifically assess this problem. In this systematic review and meta-analysis, we aim to assess the factors related to the compliance of stay-at-home policy. By addressing the most important factors, strategies to increase adherence to the policy may be formulated and implemented to reduce the transmission of communicable diseases.

METHODS AND MATERIALS Information Sources and Search Strategy The search strategy for this systematic review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Multiple electronic databases, consisting of PubMed, Google Scholar, Cochrane Central Register of Controlled Trials (CENTRAL), EBSCO, Medline, and Scopus, were screened by four independent reviewers up to 11th November 2021. The keywords used in the pursuit were customized according to the database used, as shown in Appendix 1. Suitable advanced search techniques were applied whenever appropriate. The literature search was limited by the language, as the authors were only compatible with English or Bahasa Indonesia language. Availability of fulltext articles was also one of the limitations. Inclusion & Exclusion Criteria We applied the following criteria: (1) cross sectional or cohort studies, (2) general population during COVID-19 pandemic, (3) received stay-at-home orders, (4) assess the isolation compliance parameter as the study outcome, and (5) Odds Ratio (OR) data present. The exclusion criteria for our literature search includes: (1) COVID-19 patients, (2) only assess beta scores, (3) studies with irretrievable full text, (4) articles including reviews, commentaries, letters, conference abstracts, and (5) studies written in languages other than English or Bahasa Indonesia.


Quality Assessment The studies included in the review were assessed for the Risk of Bias (RoB) assessment using The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for analytical crosssectional study. The end score will be Include, Exclude, or Seek Further Info. The cutoff score of 50% was used to include the study. Quality assessment was performed by four reviewers independently and discrepancies were discussed and resolved by agreement between reviewers. Data extraction We predetermined the outcome sheet in tabular form to include the following data to be extracted: (1) author and year of publication; (2) study characteristics, including study design, study location, and study period; (3) study population, including number of patients, mean age, and sex with the proportion of male and female ratio; (4) intervention type; and (5) study outcomes, including associated factors of public compliance to self-isolation in terms of its odds ratio and significance (p) values. Qualitative characteristics were extracted by three reviewers, and an independent author rechecked accuracy of extracted data meanwhile performing statistical analysis. All the comparative indicators are represented in OR which further analyzed through forest plot and funnel plot if necessary. Quantitative data analysis We performed statistical analysis using Review Manager ver. 5.4 (The Nordic Cochrane Center, The Cochrane Collaboration, Copenhagen). The odds ratio with 95% confidence interval (CI) and p-value were extracted from studies and we interpreted the pooled effects. The main result which we use in the statistical analysis was the public compliance towards self-isolation during COVID-19 pandemic. Odds ratio (OR) with a 95% confidence interval and its respective p-value was used to determine the factors associated with public compliance towards self-isolation. If OR >1, the factor was associated with better public compliance, thus, means it could be key factors in achieving pandemic erradication since selfisolation is one of the key in fighting this pandemic. Factors were put as study code, log of odds ratio, and standard of error which will be calculated for study weight, fixed odds ratio, and also its 95% confidence interval (CI) which will be presented in forest plot. We utilised inverse variance, fixed effects model as proposed by Adriani et al, since we considered that individual-specific effect of the factors associated will be contrasted and highlighted more.9 Heterogeneity was further evaluated using I2 statistics, with cut-off limits of 0%, 25%, 50%,


and 75% as insignificant, low, moderate, and high heterogeneity, respectively.10 Additionally, we performed sensitivity analysis following the Duval and Tweedie’s trim-and-fill method to identify any outlier study.

RESULTS AND DISCUSSION Search results and study selection Initial search from PubMed, Cochrane, Google Scholar, EBSCOhost, Scopus, and Medline, using search strategy mentioned above resulted a total of 3,470 studies after which 27 duplicates were removed. Primary filtering via title screening removed 3,190 articles, and with further abstract screening we removed 224 studies as it is not relevant to our inclusion and exclusion criteria. Finally, 29 studies were assessed for full-text eligibility. On the whole, we found 13 studies with irrelevant outcome, 1 study with qualitative study design, and 6 other studies not assessing compliance, thus, been removed. Final search resulted in 9 included studies which was further extracted and analyzed throughout this systematic review and metaanalysis. Screening of titles and abstracts of studies was carried out by three independent reviewers with any disagreement to be solved and judged by the fourth authors. The planned procedure is illustrated in Figure 1.


Figure 1. Diagram flow of literature search strategy Study characteristics and design All 9 studies included are clinical trials, conducted in several regions including 6 studies in Asia continent and 3 studies in Europe. To be precise, there are 7 cross-sectional studies and 2 prospective cohort studies included, with the study period widely spread throughout 2020 to 2021. Overall, 13,282 people with mean age of mostly adults age group participated in the included studies. The complete characteristics of included studies are shown in Appendix 2. Participants were recruited via random sampling, except for study by Alkhaldi et al and Zabadi et al, and were given online or web-based questionnaire to be filled regarding their sex, age, marrital status, education degree, and other relevant data. Meanwhile, self-isolation compliance was assessed by asking about their perception and attitude towards local or national instruction of self-isolation in each country. Outcomes were reported using odds ratio to see the association between the relevant factors with self-isolation compliance. Further outcome results were demonstrated in Appendix 3. Study quality assessment


Assessment of the quality of studies are depicted in Appendix 4. Overall, all studies have good quality and low risk of bias, with exceptions of confounding factors bias which are unclear and unavoidable due to the study design in 5 studies. RESULTS UNMODIFIABLE FACTORS Female sex

Figure 3A. Forest plot showing association of female sex with compliance to self-isolation

Figure 3B. Sensitivity analysis for studies assessing female sex as factors of compliance The first unmodifiable factors that affects patients’ compliance to self-isolation is female sex, as reported in seven included studies. Our quantitative analysis demonstrated that female are significantly more compliant compared to male, yielding a pooled odds ratio (OR) value of 1.36 (p<0.00001; 95%CI: 1.15-1.37) (Figure 3A and 3B). Although high heterogeneity has been found, with an I2 value of 95%, our sensitivity analysis identified Zabadi et al’s study as an outlier, and with its removal the heterogeneity has decreased to much lower value of 89%. When this study is removed, the pooled OR becomes 1.03 (p=0.53;


95%CI: 0.93, 1.14). This might be due to the use of non-randomized, snowball sampling method by Zabadi et al’s study which resulted in much higher number of female participants compared to male.11 Furthermore, the main possible reasons to support our results is that females had higher level of anxiety compared to males and a nature of caring their family in order to stay safe and healthy during the pandemic, thus, are more compliant to self-isolation.12 Marital Status

Figure 4A. Forest plot showing association of marrital status with compliance to selfisolation

Figure 4B. Sensitivity analysis for studies assessing marrital status as factors of compliance Our quantitative analysis also demonstrated that people with single status are significantly more compliant compared to married couple, with a pooled OR value of 0.79 (p=0.0006; 95%CI: 0.69-0.90) (Figure 4A and 4B). Moreover, high heterogeneity has been found, with an I2 value of 82%, thus, we perform our sensitivity analysis which identified Alkhaldi et al’s study as an outlier, and by removing it we get an I2 value become much lower of 58%. When this study is removed, the pooled OR become 0.73 (p<0.0001, 95%CI: 0.63, 0.84). This might be due to the way Alkhaldi et al recruiting participants with non-randomized method. Surprisingly, married couple which was previously thought to be more compliant to quarantine, turned out to be the opposite one. 12 As reported in Zabadi et al’s study, 11 this might be due to more responsibilities of daily courses to organize their home with what is needed during the self-isolation period. Furthermore, this resulted in higher level of stress and anxiety


which make quarantine more boring and associated with negative emotion. Therefore, going out for a walk or could be one good solution to alleviate stress between family members so their compliance could be better towards isolation. 11 Older age

Figure 5A. Forest plot showing association of older age with compliance to self-isolation

Figure 5B. Sensitivity analysis for studies assessing older age as factors of compliance Furthermore, the next factors that we found significantly related to self-isolation compliance is older age groups with a pooled OR value of 1.01 (p=0.002; 95%CI: 1.01-1.02) (Figure 5A and 5B). Moreoever, high heterogeneity has been found, with an I2 value of 74%, thus, we perform our sensitivity analysis which identified Alkhaldi et al’s study as an outlier, and by removing it we get an I2 value become much lower of 60%. When this study is removed, the pooled OR become 1.01 (p=0.002, 95%CI: 1.01, 1.02). Similar to previous discussion, Alkhaldi et al used non-randomized sampling method to recruit participants which resulted in lower number of elderly group. The possible explanation to support our findings is that older age group were wiser and more thoughtful about the importance of quarantine during the pandemic. On the other side, the younger age group were less anxious about going out because they thought that their immune system was strong enough to fight the virus if infected. 13


COVID-19 infection history

Figure 6. Forest plot showing association of history of having COVID-19 with compliance to self-isolation Subsequently, we also found two included studies assessing COVID-19 infection status as a factor that might be related to self-isolation compliance. Our quantitative analysis demonstrated that patients which had COVID-19 were less compliant compared to healthy population, although not significantly related, with a pooled OR value of 0.86 (p=0.23; 95%CI: 0.67-1.10) (Figure 6A). Moreoever, high heterogeneity has been found, with an I2 value of 85%, however, sensitivity analysis could not be performed due to inadequate number of study. The possible explanation to support these results is that people who had experienced COVID19 symptoms in the past thought that they were unable to be infected again, thus, lower their compliance to quarantine. 14,15 Residency in the city

Figure 7. Forest plot showing association of older age with compliance to self-isolation Residents in the city were found to be more compliant to self-isolation compared to those living in village or rural area, with our quantitative analysis resulted in pooled OR of 1.19 (p=0.02, 95%CI: 1.03-1.37) (Figure 7A). However, high heterogeneity has been found, with an I2 value of 90%, yet sensitivity analysis could not be performed due to inadequate findings from included studies. People who live in urban area tend to get more complete information and socialization about COVID-19 and its impacts, through social media or internet. On the other hand, as reported by Zabadi et al’s study, residents in rural area or village rarely get


adequate information about quarantine regulations, in addition to less understanding about COVID-19 itself. 11,15 MODIFIABLE FACTORS Existence of emergency regulations COVID-19 emergency regulations are one of the most prominent modifiable factors that affect isolation adherence. Our analysis demonstrates that the existence of emergency guidelines that require oneself to stay home increases adherence to isolation precautions (pooled OR=1.80 [95%CI: 1.49-2.17], p<0.00001). The heterogeneity is negligible (I2=0%), establishing the strength of this association. Furthermore, we did not perform sensitivity analysis due to the limited number of studies and I2 value which is already low. The reason behind this strong association might be correlated with the constant reminders and sense of urgency the regulations imply on the general population. As mentioned by Zabadi et al, 11 emergency regulations allow the public to be more self-conscious about staying home rather than focusing on the length of quarantine period. Considering that this finding is modifiable, the results can be used as a basis for governmental regulations to enforce better emergency isolation adherence, which would be elaborated more on the following recommendations section of this paper.

Figure 8. Forest plot showing association between emergency regulations and isolation compliance. Perception to protect the health of one’s family Citing the Protection Motivation Theory, adherence to a protective act is affected by self-appraisal of the extent and severity of the threat, as well as personal susceptibility. 15 This theory thus can explain the significant association between personal perception to protect family’s health and compliance to self-isolation guidelines. In the following plot, our analysis shows a pooled OR of 1.67 (95% CI: 1.25-2.22, p=0.0004) with negligible heterogeneity


(I2=0). Here, due to the limited number of studies and negligible heterogeneity, we did not perform sensitivity analysis. Indeed, the willingness to protect loved ones can encourage behaviours that limit possible exposure to diseases, reinforced by knowledge of possibility of household transmission.

Figure 9. Forest plot showing association between perception to protect family and isolation compliance. Higher Education Degree Higher education degree also contributes to better self-isolation compliance (pooled OR=1.29 [95%CI: 1.10-1.52], p=0.002). Low heterogeneity is found (I2=20%), thus we did not perform sensitivity analysis. This trend of association between higher education and better protective behaviours have also been identified in the prevention efforts of other diseases including in transmissible diseases such as vector-borne diseases and in the control of chronic diseases such as treatment adherence in hypertension. 16,17 More importantly, higher education might contribute to better disease knowledge and therefore risk perception, 17 which leads to better compliance to protective behaviour in all diseases including isolation in avoidance of transmissible respiratory infections such as COVID-19.

Figure 10. Forest plot showing association between higher education degree and isolation compliance.


Trust in Government Interestingly, trust in government also leads to better compliance to isolation (pooled OR=1.44 [95%CI: 1.33-1.55]), with significant association (p<0.00001) and low insignificant heterogeneity (I2=0%). As the heterogeneity is insignificant, we did not perform further sensitivity analysis. These results reinforce the importance of maintaining public trust for governments, which can be achieved through consistency in regulations as well as assurances about household income during absence from workplaces. In particular, economic considerations by the government while exerting outbreak policies is an important key to encourage trust via physiological needs in accordance to Maslow’s theory. 18 This factor is also associated with others, since heightened worry and anxiety levels of the public result in increased dependency and therefore trust on the Ministry of Health. Conversely, indecisive actions from the government leads to reduced compliance and thus heightened risk of disease spread. 18

Figure 11. Forest plot showing association between trust in government and isolation compliance. Worry or distress over COVID-19 Affective response including worry and distress over COVID-19 also contributes to better isolation compliance with pooled OR of 1.44 (95%CI: 1.34-1.56, p<0.00001). This is comprehensible since increased worry reflects increased risk perception and therefore better compliance to isolation in efforts to avoid the disease spread. However, since there is substantial heterogeneity as demonstrated by the high I2 value of 88%, we performed further sensitivity analysis. This identifies Kaim et al as an outlier study, with its removal resulting in greater pooled effect (pooled OR=1.50 [95%CI=1.39-1.62]) with much lower heterogeneity that approaches negligible value (I2=0%). In contrast to Bodas et al’s and Smith et al’s study which measures degree of worry via a 5-point Likert scale, 15,18 Kaim et al’s study measures of


distress via scales developed during the study after pilot testing to 25 individuals. 19 This newly developed scale thus may become a source of heterogeneity in this case, which result in lower odds of compliance in contrast to other studies.

Figure 12A. Forest plot showing association between worry or distress over COVID-19 and isolation compliance.

Figure 12B. Sensitivity analysis of worry as a factor for isolation compliance.

Recommendations On Daily Practice The association of modifiable factors with compliance we identified in our analysis calls for further interventions. For the unmodifiable status, our study indicated that the government and healthcare officers should be more aware about the group of people who tend to be less compliant to quarantine procedure during the COVID-19 pandemic. Moreover, there should be more education and additional attention to be put in those groups to ensure that their knowledge and perception about quarantine is equivalent with the rest of the populations. On the other hand, for the factors that can be modified, we strongly suggest the need of a strong and assertive commitment from every parties, especially government. Firstly, we recommend broadcast of emergency regulations by official statements by the government, as well as the aid of various media in increasing public awareness of the importance of isolation in controlling disease spread and reducing overloaded healthcare burdens. The government is also encouraged to make consistent, clear-cut decisions with regards to the outbreak in order


to maintain public trust that will create better adherence to isolation. Moreover, citing Maslow’s hierarchy of needs that safety and security are secondary to physiological needs, governments should also consider the economic aspect of policies, including the assurance of household income during absence from workplaces or the allowance of remote working, so that the fulfillment of these can shift the trend upwards.

18

With regards to long-term

approaches, since we identified better compliance associations in populations with higher educational degree, higher socioeconomic status, and residence in the cities, efforts to reach these by providing compulsory education of minimum 12 years, provision of jobs, and providing better public facilities can be beneficial as well. All in all, policies should be aimed to increase awareness, emphasize the urgency, and prevent the public from getting used to the disease, which can contribute to disobedience to isolation regulations and risk-taking behaviors that can lead to uncontrolled disease spread. The associations that we identified in this analysis and the corresponding recommendations does not only apply to COVID-19, but also in other diseases and possible outbreaks. The resulting increase in adherence with isolation recommendations can thus hopefully reduce disease transmission, reduce the pressure of overloaded healthcare systems, and encourage better preparation before future outbreaks. Strengths And Limitations This study is the first systematic review and meta-analysis that evaluate the factors associated with compliance to self-isolation or quarantine procedures during the COVID-19 pandemic. Furthermore, by including large number of studies all across different continents, either in developed or developing countries, results of this study were more likely to be generalized for all population. Our analysis has also succeeded to found several significant factors, both unmodifiable and modifiable, which is crucial to be known in order to achieve a high compliance of quarantine. Nevertheless, this study is not without limitations. There might be a possibility to miss some important information in literatures written in other language other than English or Indonesian. Moreover, unavailable full-text version is also the limitation of this study.


CONCLUSION & FURTHER RECOMMENDATION Although quarantine is powerful strategy related to public health response to infectious diseases, some also oppose the policy and does not comply with the instructions. Based on the review, compliance to quarantine is influenced by various factors, grouped into modifiable and unmodifiable factors. This study showed that unmodifiable factors such as female sex, marital status, older age, and had COVID-19 and modifiable factors including existence of emergency regulations, perception to protect own families, higher education degree, trust in government, and worry or distress over COVID-19 were associated with compliance toward quarantine. We hope that strategies to further increase people compliance toward quarantine may be formulated based on this comprehensive assessment, such as increase of supervision for unmodifiable factors and direct intervention to improve the modifiable factors. This knowledge may also raise the governments attention to people who violate the quarantine orders and also promote awareness on the importance of quarantine in preventing surge of pandemic. Furthermore, we hope that compliance toward quarantine orders could increase, pandemic surge may be prevented, and the consequence of the pandemic such as mortality rate may be reduced.


References 1. Listings of WHO’s response to COVID-19 [Internet]. [cited 2021 Nov 15]. Available from: https://www.who.int/news/item/29-06-2020-covidtimeline

2. WHO Coronavirus (COVID-19) Dashboard [Internet]. [cited 2021 Jul 11]. Available from: https://covid19.who.int

3. CDC. COVID-19 and Your Health [Internet]. Centers for Disease Control and Prevention. 2020 [cited 2021 Jan 29]. Available from: https://www.cdc.gov/coronavirus/2019ncov/vaccines/different-vaccines/mrna.html

4. Conti AA. Historical and methodological highlights of quarantine measures: from ancient plague epidemics to current coronavirus disease (COVID-19) pandemic. Acta Biomed. 2020 May 11;91(2):226–9.

5. Patel A, Patel S, Fulzele P, Mohod S, Chhabra KG. Quarantine an effective mode for control of the spread of COVID19? A review. J Family Med Prim Care. 2020 Aug 25;9(8):3867–71. 6. Rajatanavin N, Tuangratananon T, Suphanchaimat R, Tangcharoensathien V. Responding to the COVID-19 second wave in Thailand by diversifying and adapting lessons from the first wave. BMJ Global Health. 2021 Jul 1;6(7):e006178. 7. Director-General Health and Social Care. Compliance with self-isolation and quarantine measures: literature review [Internet]. Scottish: Scottish Government; 2021 Oct 6 [cited 2021 Nov 16]. Available from: https://www.gov.scot/publications/compliance-self-isolationquarantine-measures-literature-review/pages/4/ 8. McCall MC, Nunan D, Heneghan C. Is a 14-day quarantine effective against the spread of COVID-19? [Internet]. Unknown: CEBM; 2020 Apr [cited 2021 Nov 16]. Available from: https://www.cebm.net/covid-19/is-a-14-day-quarantine-effective-against-the-spread-of-covid19/

9. Nikolakopoulou A, Mavridis D, Salanti G. How to interpret meta-analysis models: fixed effect and random effects meta-analyses. Evidence-Based Mental Health. 2014 May 1;17(2):64–64.

10. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in metaanalyses. BMJ. 2003 Sep 6;327(7414):557–60.

11. Al Zabadi H, Yaseen N, Alhroub T, Haj-Yahya M. Assessment of Quarantine Understanding and Adherence to Lockdown Measures During the COVID-19 Pandemic in Palestine: Community Experience and Evidence for Action. Front Public Health. 2021 Mar 2;9:570242.

12. Alkhaldi G, Aljuraiban GS, Alhurishi S, De Souza R, Lamahewa K, Lau R, et al. Perceptions towards COVID-19 and adoption of preventive measures among the public in Saudi Arabia: a cross sectional study. BMC Public Health. 2021 Dec;21(1):1251.

13. Carlucci L, D’Ambrosio I, Balsamo M. Demographic and Attitudinal Factors of Adherence to Quarantine Guidelines During COVID-19: The Italian Model. Front Psychol. 2020 Oct 21;11:559288.

14. Guillon M, Kergall P. Attitudes and opinions on quarantine and support for a contact-tracing application in France during the COVID-19 outbreak. Public Health. 2020 Nov;188:21–31.


15. Smith LE, Aml R. Factors associated with adherence to self-isolation and lockdown measures in the UK: a cross-sectional survey. :2.

16. Uchmanowicz B, Chudiak A, Uchmanowicz I, Rosińczuk J, Froelicher ES. Factors influencing adherence to treatment in older adults with hypertension. Clin Interv Aging. 2018;13:2425–41.

17. Aerts C, Revilla M, Duval L, Paaijmans K, Chandrabose J, Cox H, et al. Understanding the role of disease knowledge and risk perception in shaping preventive behavior for selected vector-borne diseases in Guyana. PLoS Negl Trop Dis. 2020 Apr;14(4):e0008149.

18. Bodas M, Peleg K. Income assurances are a crucial factor in determining public compliance with self-isolation regulations during the COVID-19 outbreak – cohort study in Israel. Isr J Health Policy Res. 2020 Dec;9(1):54.

19. Kaim A, Siman-Tov M, Jaffe E, Adini B. Factors that enhance or impede compliance of the public with governmental regulation of lockdown during COVID-19 in Israel. International Journal of Disaster Risk Reduction. 2021 Dec;66:102596.


Appendix 1. Keyword details Database screened Cochrane

Keyword used

Central (Isolation):ti,ab,kw OR (Quarantine):ti,ab,kw OR (Social

Register of Controlled isolation):ti,ab,kw Trials (CENTRAL)

OR

(Self-isolation):ti,ab,kw

AND

(Factors):ti,ab,kw OR (Factors associated):ti,ab,kw AND MeSH descriptor: [COVID-19] explode all trees

EBSCO

("COVID-19" OR "sars-cov-2" OR "coronavirus") AND ("home monitoring" OR "telemonitoring" OR "remote monitoring")

Medline

( ( "sars-cov-2" OR "covid-19" OR outbreak ) AND ( "home monitoring" OR web-based OR virtual OR telemonitoring ) ) AND ( LIMIT-TO ( OA , "all" ) ) AND ( LIMIT-TO ( DOCTYPE , "ar" ) ) AND ( LIMIT-TO ( LANGUAGE , "English" ) )

Pubmed

(Self) AND ("isolation" OR "quarantine" OR "social isolation" OR "self-isolation") AND (compliance OR adherence) AND (factors OR factors associated) AND (COVID-19 OR "sars-cov2"[MeSH Terms] OR "covid-19"[MeSH Terms] OR outbreak)

Scopus

( ( self ) AND ( "isolation" OR "quarantine" OR "social isolation" OR "self-isolation" ) AND ( compliance OR adherence ) AND ( factors OR factors AND associated ) AND ( covid-19 ) )

Google Scholar

(Self) AND ("isolation" OR "quarantine" OR "social isolation" OR "self-isolation") AND (compliance OR adherence) AND (factors OR factors associated) AND COVID-19


Appendix 2. Characteristic of selected studies Author; year

Studies characteristics Study design Crosssectional

Study location Saudi Arabia, Asia

Study period AprilJune 2020

Number of participants 2393 participants

Bodas et al, 2020

Cohort

Israel, Asia

February - March 2020

1074 participants

Nivette et al, 2021

Zurich, Switzerla nd

April 2020

Paykani et al, 2020

Prospecti velongitudi nal cohort Crosssectional

Mashhad , Iran

Shati et al, 2020

Crosssectional

16 cities in Iran

Alkhaldi et al, 2021

Mean age

Sex (M:F in %)

18-24 y : 19.4% 25-34 y : 25.7% 35-44 y : 27.2% 45-54 y : 15.9% 55-64 y : 7.5% 65-74 y : 2.8% >75 y : 1.5% 39.57 ± 14.09 y

59.9 : 40.1

Time to follow-up N/A

50.4 : 49.6

N/A

737 participants

Age 15, 17, 20, 22, 23

51:49

N/A

4-12 April 2020

1073 participants

Median IQR 38 (30-51)

49:50.98

N/A

February -May 2020

558 participants

69.9 ± 7.4

45.6:54.4

N/A

Intervention type An open web-based survey which had originally been designed by public health experts in Hong Kong was distributed to adult participants in Saudi Arabia

Responses were collected through the iPanel online polling service. The main tool used was a questionnaire designed only for this study, which comprised of: news consumption, personal concern, public panic, and attitudes toward public health regulations. Random sampling for 8 waves of child interviews at ages 7, 8, 9, 11, 13, 15, 17, and 20. For ages 15 and 17, paper/pencil question naires were given in classrooms outside of regular lesson times. For age 20, invitations by SMS and e-mail were sent on April 8, 2020, with reminders on 11 and 13 April. Systematic random sampling using phone number lists provided by Telecommunication Company. Phone interviews were carried out by trained interviewers from the Iranian Students Polling Agency (ISPA). The survey included sociodemographic questions, perceived social support scale (MSPSS) and questions about self-isolation during the Nowruz holiday.

Quota sampling to recruit respondents from 16 cities selected based on their population size (4, 7, and 5 cities for localities with ≤500 000, 500 000-1 000 000, and ≥1 000 000 populations) and geographical direction (West = 4 cities; North, East, South, Center = 3 each). At least 30 respondents per locality were selected. Phone interviews of 558 respondents


(out of 560; response rate = 99.6%) were performed by local trained interviewers using a validated interview form. Participants were recruited using an online questionnaire posted on generic Facebook groups and on the websites of local newspapers. An information letter was presented, stating the eligibility criteria: age 18 years and older and living in France during the general quarantine. Participants were asked how many times in the past seven days they went out of their quarantine home by categories of trip, general quarantine extension, and contact-tracing application acceptability.

Guillon et al, 2020

Crosssectional

France

April 16th May 7th 2020

1849 participants

20-29 y: 650 (35.2%) 30-39 y: 346 (18.7%) 40-49 y: 310 (16.8%) 50-59 y: 303 (16.4%) 60-74 y: 240 (13.0%)

24:76

N/A

Kaim et al, 2020

Crosssectional

Israel

March 2020

503 participants

40.5 ± 14.4

48.9:51.1

N/A

Recruiting participants to the study was conducted through an online internet panel company that consists of over 100,000 members, representing all geographic and demographic sectors of the Israeli population (http://www.ipanel.co.il/). A stratified sampling method was used, based on data published by the Israeli Central Bureau of Statistics in regard to age, gender, religiosity and geographic zones.

Smith et al, 2020

Crosssectional

UK

6th and 7th May 2020

2240 participants

18 years and older

48.06:51.94

N/A

Zabadi et al, 2021

Crosssectional

Palestine

22nd March to 5th May 2020

2819 participants

29.47 (18-71) years

27.2:72.8

N/A

An online cross-sectional survey, recruited from quota sampling based on age, gender, social grade, level of education, and government office region to ensure representativeness of the data. Participants were asked about whether they left their home in the past 24 h and in the past seven days, while also asked about factors assessed in this study. A cross-sectional web-based questionnaire, distributed throughout social media (Facebook and Instagram).


Appendix 3. Study outcome summary Author year of study Factors affecting isolation adherence Female sex* Older age*

Married status*

Odds ratio (95%CI) Alkhaldi et al, 2021 1.266** (0.96– 1.671)

Bodas et al, 2020 0.739** (0.575- 0.948)

Kaim et al, Guillon et al, 2020 2020 0.72 (0.49– 0.853 1.08) (0.728,0.999)**

Smith et al, 2020 1.5625 (1.251.961)**

1.276 (0.844,1.931)**

1.149 (0.6022.22)**

0.324 1.014 (0.146–0.717)** (1.005- 1.024)**

1.509 (1.02– 2.233)**

Residency in the city* Worry over COVID19*

1.505 (1.330-1.702)**

Trust in Government*

1.428 (1.259-1.620)**

0.75 (0.54– 1.04)** 1.61 (1.16– 2.24)**

Higher Education Degree* Perception to protect the health of one’s family* Emergency regulation that

1.68 (1.09– 2.58)** 1.64 (1.17– 2.31)**

Zabadi et al, Nivette et al, 2021 2021 2.77 (2.273.37)**

Shati et al, 2020 2.3 (1.5-3.3)** 2.3 (1.2-4.3)**

0.971 (0.7041.333)**

0.70 (0.590.83)**

0.813 (0.6171.064)**

1.37 (1.161.64)**

1.4925 (1.3511.695)** 1.219 (0.980,1.515)

Paykani et al, 2020

1.515 (1.3331.724)**

1.38 (1.031.86)**

1.417 1.1235 (0.885(1.074,1.870)** 1.408)**

1.51 (1.062.16)**

1.266 (1.1361.408)** 1.87 (1.492.34)**

0.561 (0.370.85)**


requires oneself to stay home* Low socioeconomic status*

1.15 (0.711.85)

News Consumption Retired from work

1.396 (1.228-1.587)** 11.608 (2.192– 61.469)**

Working Have at least 1 respiratory/ cold/ flu-like symptom Smoking

0.621 (0.4780.806)** 0.545 (0.412–0.721)** 0.89(0.731.09)

Enough food supply

1.23 (1.031.47)**

Having a child in the household Had COVID-19* Understanding of government measures, if some one in house was symptomatic Perceived social norms Perceptions about impact on mental health Self-reported general health

0.877 (0.6581.163)** 1.123 (0.818-1.540)**

0.581 (0.3950.855)** 1.299 (1.0311.639)**

1.0101 (1.01011.0204)** 0.990 (0.8771.1236)** 0.952 (0.8551.064)**

0.73 (0.5071.075)**


Afraid to pass coronavirus to someone else Health impact of COVID-19 in France (moderately serious) Efficacy of the general quarantine (neither agree nor disagree) Individual health consequences in case of infection by COVID-19 (intermediate) Individual risk of infection by COVID-19 (intermediate) Respect of the general quarantine rules by most people Support from family members Support from friends Support from significant other

1.515 (1.3331.724)** 1.003 (0.7901.272)** 0.785 (0.573-1.075)** 0.935 (0.758-1.154)**

1.257 (1.024-1.542) 0.930 (0.738-1.171) 1.14 (1.0531.25)** 0.871 (0.8180.929)** 1.08 (0.99- 1.178)

Living with family members Low household income

1.0 (0.6-1.8) 0.783 (0.43-1.43)


Migrant background - both parents born abroad

1.06 (0.771.47)

*Selected for quantitative analysis through meta-analysis **statistically significant on independent basis

Appendix 4. Studies quality assessment based on JBI Tool for Cross-Sectional Studies Bias Criteria

Author; year of study Alkhaldi et al, 2021 Yes

Bodas et al, 2020 Yes

Nivette et al, 2021 Yes

Paykani et al, 2020 Yes

Shati et al, 2020 Yes

Guillon et al, 2020 Yes

Kaim et al, 2020 Yes

Zabadi et al, 2021 Yes

Smith et al, 2020 Yes

Were the study subjects and the setting described in detail?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Was the exposure measured in a valid and reliable way?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Were objective, standard criteria used for measurement of the condition?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Were confounding factors identified?

Yes

Yes

Yes

Unclear

Unclear

Unclear

Unclear

Unclear

Unclear

Were strategies to deal with confounding factors stated?

Yes

Yes

Yes

Unclear

Unclear

Unclear

Unclear

Unclear

Unclear

Were the outcomes measured in a valid and reliable way?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Was appropriate statistical analysis used?

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Overall appraisal

Include

Include

Include

Include

Include

Include

Include

Include

Include

Were the criteria for inclusion in the sample clearly defined?


A Novel SARS-CoV-2 Diagnostic Test Using Saliva RT-LAMP: A Systematic Review and Meta-Analysis Kelvin Kohar1, Stephanie Amabella Prayogo1, Emir Gibraltar Faisal1, Shakira Amirah1 1Faculty

of Medicine, Universitas Indonesia

ABSTRACT INTRODUCTION: In March 2020, WHO declared a global pandemic condition by COVID19. As the worldwide protocol of this pandemic, the superior diagnostic method is needed and considered as a top priority for public health interventions in the COVID-19 pandemic. Currently, the gold standard Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) imposes a complexity and offers some challenges in a sense of urgency ahead. Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP) is one of the breakthrough innovations to which the technique performs better as a promising diagnostic. The use of saliva also provides many advantages compared to nasopharyngeal swabs. OBJECTIVE: This systematic review and meta-analysis aims to investigate the use of saliva RT-LAMP as SARS-CoV-2 diagnostic tool. This study is needed due to the urgency of the current situation and finally to design an appropriate solution. METHOD: This systematic review was conducted using PRISMA statement on several databases. Each quality of included cross-sectional study was assessed using updated QUADAS-2 tool for diagnostic test accuracy study. All eligible studies were then quantitatively processed using RevMan 5.4.1 and MetaDTA, and extrapolated into summary points to further be expressed in forest and SROC plots. RESULTS AND DISCUSSIONS: Eleven studies, with a total of 2,486 samples, were included in this meta-analysis. The pool sensitivity and specificity of all studies were 88.7% (95%CI: 0.773-0.948) and 97.9% (95%CI: 0.917-0.995). Furthermore, our study also found that sensitivity optimization might be done using buffer and RNA extraction resulting in higher sensitivity of 92% (95% CI: 0.833-0.964) for RNA extraction only, and 93.5% (95%CI: 0.8870.964) for combination of such methods. CONCLUSION: To summarize, saliva RT-LAMP is a promising diagnostic tool in COVID19. However, further studies are still required to provide the best optimization method.


KEYWORDS: SARS-CoV-2,COVID-19, RT-PCR, Saliva RT-LAMP, diagnostic tool


A Novel SARS-CoV-2 Diagnostic Test Using Saliva RT-LAMP: A Systematic Review and Meta-Analysis

Authors: Kelvin Kohar Stephanie Amabella Prayogo Emir Gibraltar Faisal Shakira Amirah

AMSA-UNIVERSITAS INDONESIA 2021


1.

INTRODUCTION

In March 2020, WHO declared a global pandemic condition by COVID-19, which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). On the 14th of November 2021, there have been 251,788,329 confirmed cases, including more than 5 million death cases by SARS-CoV-2. COVID-19 has caused a high case of worldwide mortality, which has spread to 224 countries.1 SARS-CoV-2 is transmitted amongst human via respiratory droplets and aerosols of infected people. Currently, various studies have been carried out to find drugs or vaccines that are effective against COVID-19.2 The absence of an effective therapeutic agent to ward off COVID-19 demands a simple, fast, reliable, decentralized, and affordable diagnosis tool of COVID-19.3 The need for superior diagnostics in the detection of COVID-19 is a top priority for public health interventions in the COVID-19 pandemic. This approval of superior testing and diagnostics will be in line with various habits, such as washing hands, wearing mask, and keeping distance accompanied by COVID-19 vaccinations.4 Currently, the main diagnostic tool used for the diagnosis of COVID-19 is Reverse Transcriptase Polymerase Chain Reaction (RT-PCR), which detects SARS-CoV-2 genetic material from in nasopharyngeal (NP) samples. RT-PCR is believed to be very reliable in the diagnosis of COVID-19. Unfortunately, this diagnosis is very complex and expensive; as well as requires trained medical personnels, specialized instrumentation, supply-limited reagents, and substantial technical labor. Even at the beginning of the pandemic, when all countries used RT-PCR, there was a shortage of reagents used for sample extraction and viral RNA.5 The high number and rapid increase of COVID-19 cases have urged the replacement of RTPCR with other molecular detections of the same quality that does not require high costs for implementation or interpretation of the results. More specifically, loop-mediated isothermal amplification with simultaneous reverse-transcription (RT-LAMP) allows rapid and sensitive genetic detection of SARS-CoV-2 within one hour and is easy to interpret. Previously, RTLAMP had also succeeded in detecting several respiratory viral RNAs, including COVID-19.6 RT-LAMP is a DNA amplification technique, which is considered as a promising diagnostic method for several reasons, such as high sensitivity and specificity, less time needed, and less dependence on sophisticated tools. In RT-LAMP, the amplification of genetic material is carried out at a constant temperature without the need for thermal cycling. This fact indicates


that diagnosis with RT-LAMP can be carried out anywhere with simpler tools, as they only require a heat block or a water bath set to a single temperature.7 The single reaction present in RT-LAMP can also shorten diagnosis time. Results from RT-LAMP can be detected by staining in real time, then interpreted by the eye directly, including the untrained eye with a short turnaround time. Finally, the simplicity of the procedure means it can be easily mastered by a junior laboratory technician or healthcare worker with little training.8 Various studies have been carried out to develop protocols for using RT-LAMP as a diagnosis of COVID-19. Novel RT-LAMP has a sensitivity comparable to RT-PCR, achieving even higher sensitivity on a clinical basis. Currently, NPS is the gold standard sample for PCR testing despite many clinical disadvantages, such as patient discomfort, exposing healthcare directly to the viral, requiring trained healthcare workers, and possible bleeding as side effect for thrombocytopenic individuals.9 It is already known that saliva is one of the most promising types of sample due to its several advantages, such as easy to collect (even self-collected) and patient comfort.10 Besides, it may also potentially eliminate the need of health care professionals to sample collection; Therefore, the risk of infection spreading will reduce significantly.11,12 Currently, there is no systematic review or meta-analysis related to the topic. Therefore, this systematic review and metaanalysis aims to investigate the use of saliva RT-LAMP as SARS-CoV-2 diagnostic tool. Studies and reviews like this are needed due to the urgency of the current situation as already stated above and finally to design an appropriate solution. 2.

MATERIALS & METHODS

The systematic review was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA)13 guidelines to objectively searching and screening relevant studies related to the topic. 2.1 Search Strategy Literature search was conducted independently by all authors (KK, SAP, SA, EGF) through several scientific databases, including PubMed, ScienceDirect, Scopus, ProQuest, Wiley, and EBSCOHost. Any discrepancies were further discussed subjectively among the authors. The keywords used in each database consist of “Reverse transcriptase-Loop mediated isothermal amplification”, “RT-LAMP”, “Saliva”, “COVID-19”, and “SARS-CoV-2”. Subsequently,


Medical Subject Headings (MeSH) term was also used in PubMed if applicable. Retrieved search results were then deduplicated and screened according to eligibility criteria. 2.2 Study Eligibility Criteria Screening processes were done to filter 1032 deduplicated articles found in initial searching. All articles were screened according to inclusion and exclusion criteria. The authors included cross-sectional, cohort, case control, and randomized clinical trial which evaluated the sensitivity and specificity of RT-LAMP saliva detecting SARS-CoV-2. Studies were considered to be excluded if fulfilled any of the following criteria: (1) Review articles, case series, case reports, and letter to the editors; (2) Non-human studies; (3) Irretrievable full-text; and (4) Non-English articles. 2.3 Study Selection All retrieved studies from initial studies were pooled using Google Spreadsheet (Google LLC, Mountain View, CA, USA). The articles were deduplicated manually to remove duplicates. All articles were then independently reviewed by each author based on PRISMA guideline scheme. Screening process was started with title and abstract screening to exclude studies according to the criteria discussed above. The underlying excluded reason was also mentioned. Nonexcluded studies were continued to the next step. Afterwards, all investigators independently read the full text and exclude selected studies if met the exclusion criteria. Finally, all included studies were then validated to ensure studies eligibility for qualitative and quantitative analysis. 2.4 Data Extraction and Quality Assessment The data extraction was conducted using predetermined form with Google Spreadsheet (Google LLC, Mountain View, CA, USA). The investigators extracted independently the following data from each study: study authors; publication years; study location; study period; study design; sample size; index test (sample preparation, buffer used, RNA extraction, primer, and assay); and reference test. Besides, the reviewers also recorded some outcomes, including true positive, false positive, true negative, false negative, sensitivity, and specificity.

Next, each study was assessed for its methodological quality to minimize systematic biases and errors from extracted data. Two investigators (SA, EGP) independently assessed each crosssectional study using updated QUADAS-2 (Quality Assessment Tool for Diagnostic Accuracy Studies). This tool evaluates diagnostic accuracy studies on systematic reviews which consists of four domains, involving patient selection, index test, reference standard, as well as flow and


timing. The scoring of every domain is separated into risk of bias (with signaling questions) and applicability. Each study is judged by “low”, “high”, and “unclear” risk of bias .14 The summary of quality assessment is presented in a graph generated in Google Spreadsheet (Google LLC, Mountain View, CA, USA). 2.5 Pooled Analysis Pooled analysis was done by using sensitivity and specificity data of each study. Both values are generated from true positive, false positive, true negative, false negative provided. Furthermore, the authors conducted subgroup analysis for studies reported using RNA extraction and buffer during the research. Quantitative analysis was done using univariate random effect, pooling and weighing sensitivity and specificity across all studies. All results were visualized into forest plot and summary receiver operating characteristic (SROC) plot. The forest plot was processed using RevMan 5.4.1; Meanwhile, the summary points of sensitivity and specificity, as well as SROC plot was conducted using MetaDTA software (University of Leicester, Leicester, England). 3.

RESULTS

Figure 1. PRISMA Flowchart


3.1 Study Selection and Study Characteristics The authors yielded a total of 1,132 records upon initial search. After removing 100 articles, titles and abstracts screening were performed and 43 articles were obtained to be assessed afterwards in full-text level. We further excluded 32 studies due to ineligible data. As a result, 11 articles were included in this systematic review.

All included studies were cross-sectional and published between 2020 and 2021. Out of 11 studies, 4 were done in Europe15–18, 4 in America19–22, and 3 in Asia23–25. Among the total of 2,846 samples collected, the majority were tested positive or negative with reference test (RT-qPCR) from NP swab (gold standard). There were variations across studies regarding reference kit test used, such as Superscript III Platinum One-Step qRT-PCR, TaqMan 2019-nCoV assay kit, TaqPath 1-Step RT-qPCR Master Mix GC, Altona RealStar SARS-CoV-2, and others. The authors further divided index RT-LAMP test’s protocols into five sections, namely sample preparation, buffer used (if any), RNA extraction method (if any), primer used, and assay / kit used. Ten out of eleven studies conducted preparation protocols for their samples, with most of them doing the incubation process by heating their samples. Again, there were variations regarding the incubation’s time and temperature across studies ranging from 65 to 95 0C and 5 to 30 minutes, respectively. Buffers were used in 8 studies; while the rest did not report any usage of buffers. Six out of eleven studies were extracting samples’ RNA before further processed using QIAamp Viral RNA Mini Kit (n = 3), semi-alkaline protease (n = 1), and mySPINTM 12 (n = 1). Different primers were used throughout studies, and two did not mention the information. Last but not least, WarmStart Colorimetric LAMP 2x Master Mix was the most popular kit that was used in 7 studies. Other remaining kits used were The EasyCov, Genelyzer Kit, GspSSD 2.0 Isothermal Mastermix, and Suputazyme. 3.2 Study Outcomes The baseline characteristics and outcomes summary of each incorporated study is listed in Table 1 and Table 2 respectively. All 11 studies reported true positive and false negative for sensitivity measurement; however, false positive and true negative, which were essential for specificity measurement, were merely reported by 9 studies. The outcomes analyses were done for sensitivity and specificity using 95% of confidence interval.


Table 1. Baseline characteristics of included studies

No

Authors, Study Year Location

Study Period

Study Design

Sample Size

Sample preparation Cross- 67 positive Heated at 950C sectional samples for 30 minutes; centrifugated at 5000g for 5 minutes Cross- 49 positive Propagated in sectional samples Vero cells in minimum essential medium (Gibco, Waltham, MA, USA) Cross- 34 random N/A sectional samples

1.

Amaral, 2021

Lisbon N/A (Portugal)

2.

Chow, 2020

Hong Kong

N/A

3.

Ganguli, 2021

Urbana (USA)

N/A

4.

Lalli, 2021

USA

N/A

5.

LeGoff, 2021

Paris (France)

6.

Lim, 2021

UK and Greece

Novemb Cross- 1718 er 2020 sectional symptomatic – & February asymptomati 2021 c samples N/A Cross- 198 Heated at 650C sectional samples for 30 minutes

Cross- 30 random sectional samples

Buffer TE Buffer

Index Test RNA Primer Extraction RNAeasy FIP/BIP, Mini Kita LF/LB, F3/B3 primers

WarmStart Colorimetric LAMP 2x Master Mixb

Taqman 2019-nCOV Assay Kit v1 for NP swab

Orf3a and E gene; FIP, BIP; Loop F, LoopB B3, B2 + B1C

WarmStart Colorimetric LAMP 2x Master Mixb

Superscript III Platinum One-Step qRT-PCR kit for NP swabc

WarmStart Colorimetric LAMP 2x Master Mixb

N/A

NEB-N2 and NEB-N1

WarmStart Colorimetric LAMP 2x Master Mixb

N/A

N/A

The EasyCov® (SkillCellAlcen, Jarry, France)

TaqPath 1Step RTqPCR Master Mix GC for NP swabc TaqPath 1Step RTqPCR Master Mix GC for salivac TaqPath TM COVID-19 CE IVD RT PCR kit for NP swab Altona RealStar SARS-CoV-2

60 L of AVE Buffer

QIAamp Viral RNA Mini Kita

TE Buffer (1:1)

N/A

Heated at 65 0C TE Buffer for 15 minutes, (1:1) or PBS 0 followed by 95 C for 5 minutes with proteinase K N/A N/A

PBS, DTT, TE, PK

Assay

Reference Test

QIAamp O117 Viral targeting RNA Mini Orf1ab

WarmStart Colorimetric


7.

Rubio, 2021

Spain

N/A

8.

Taki, 2021

Hokkaido N/A (Japan)

9.

Toppings Alberta , 2021 (Canada)

N/A

10.

Yamazaki Kyoto , 2021 (Japan)

May 2021 – March 2021

Cross- 57 positive sectional & 39 negative samples Cross- 34 positive sectional & 27 negative samples Cross- 30 positive sectional & 30 negative samples

Cross- 44 sectional suspected COVID19 samples Septem Cross- 741 ber sectional random 2020 samples

Heated at 950C for 5 minutes

5mM PBS

Heated at 950C for 5 minutes

N/A

Collected in Universal Transport Media (COPAN, Diagnostics Inc., Murrieta, USA) Heated at 950C for 5 minutes

560 L of a concentrated preparation of lysis buffer 2-fold series of PBS

Kita; RNasefree water N/A

N2 primer

QIAamp Viral N/A RNA Mini Kita mySPINT Targetin M 12c g S and RdRP gene

SemiAlkaline Protease

ORF 1ab, S, and ORF7a region AS1E primer set

LAMP 2x Master Mixb

RT-PCR kit for NP swab

WarmStart Colorimetric LAMP 2x Master Mixb Genelyzer Kit (Canon Medical system corp., Otawara, Japan) GspSSD2.0 Isothermal Mastermix (OptiGene Ltd., Horsham, UK)

RT-qPCR for NP swab

Suputazyme (Kyokuto Pharmaceutical industrial, Tokyo, Japan) WarmStart Colorimetric LAMP 2x Master Mixb

RT-qPCR for NP swab

1-Step RTqPCR Master Mix GC for NP swabc RT-qPCR for NP swab

Heated at 950C N/A N/A RT-qPCR for for 30 minutes; saliva transferred to 2x saliva stabilization solution Abbreviations: TE (Tris-EDTA); PBS (Phosphate Buffer Saline); DTT (Dithiotreitol); PK (Proteinase K); RT-qPCR (Reverse Transcription– quantitative Polymerase Chain Reaction); NP (Nasopharyngeal) a QIAGEN, Hilden, Germany; b New England Biolabs, Ipswich, MA, USA; c Thermo Fischer Scientific, Waltham, USA

11. Yang, 2021

Colorado (USA)


Table 2. Summary outcomes of included studies

Study Outcomes False False Positive Negative

No.

Authors, Year

Sensitivity (95%CI)

Spesificity (95%CI)

1.

Amaral, 2021

65

0

2

0

0.97 [0.90, 1.00]

Not estimable

2.

Chow, 2020

90

0

8

0

0.92 [0.85, 0.96]

Not estimable

3.

Ganguli, 2021

21

3

0

10

1.00 [0.84, 1.00]

0.77 [0.46, 0.95]

4.

Lalli, 2021

17

1

3

9

0.85 [0.62, 0.97]

0.90 [0.55, 1.00]

5.

LeGoff, 2021

40

48

48

1582

0.45 [0.35, 0.56]

0.97 [0.96, 0.98]

6.

Lim, 2021

119

5

13

61

0.90 [0.84, 0.95]

0.92 [0.83, 0.97]

7.

Rubio, 2021

39

0

18

39

0.68 [0.55, 0.80]

1.00 [0.91, 1.00]

8.

Taki, 2021

24

0

10

28

0.71 [0.53, 0.85]

1.00 [0.88, 1.00]

30

1

0

29

1.00 [0.88, 1.00]

0.97 [0.83, 1.00]

20

0

2

19

0.91 [0.71, 0.99]

1.00 [0.82, 1.00]

366

0

80

295

0.82 [0.78, 0.86]

1.00 [0.99, 1.00]

9. 10. 11.

Toppings,

2021 Yamazaki,

2021 Yang, 2021

True Positive

True Negative


3.2.1 Pool Sensitivity and Specificity of RT-LAMP Saliva By using summary points, we analyzed the pooled outcomes of interest. Figure 2 and Appendix 2 shows forest plot and SROC plot depicting sensitivity and specificity of involved studies ranging from 45% to 100% and 77% to 100% respectively. However, pooled analysis shows sensitivity of 88.7% (95% CI: 0.773-0.948) and specificity is 97.9% (95%CI : 0.9170.995) as shown in Appendix 2. 3.2.2 Subgroup Analysis of Sensitivity Optimization: RNA Extraction Six studies were further involved in this subgroup analysis. The summary and list of included studies, as well as the forest plot and SROC plot with sensitivity and specificity are shown in Figure 3 and Appendix 3. The RNA extraction protocols are able to improve the diagnostic accuracy of RT-LAMP saliva, with sensitivity of 92% (95% CI: 0.833-0.964) as depicted in Appendix 3. Nevertheless, the decline of specificity (96.4% [95%CI: 0.849-0.992]) might be due to lack of studies measuring specificity. 3.2.3 Subgroup Analysis of Sensitivity Optimization: RNA Extraction and Buffer Usage Furthermore, we also figured out that concurrent use of RNA extraction and buffer in RTLAMP saliva results in higher sensitivity (93.5% [95% CI: 0.887-0.964]) as presented in Appendix 4. Out of 5 studies, only 3 studies reported specificity value, which might potentially affect the result (95.6% [95%CI: 0.869-0.986]). The five included studies are depicted in Figure 4 and Appendix 4 using forest plot and SROC plot. 3.2.4 Quality Assessment The quality assessment of each study was done using updated QUADAS-2 tool, as shown in Appendix 1. There were 4 domains included in risk of bias judgement. From the patient selection aspect (first domain), 8 out of 11 studies did not have consecutively / randomly enrolled samples, therefore rated as high risk of bias. The second domain (index test) judgement was unclear in 7 studies, high risk in 2 studies, and low risk in 2 studies. A study was determined as high risk if the index test results were interpreted with the results of the reference test known. From the reference standard aspect, all studies were considered as low risk for using the gold standard (RT-PCR). The difference time in test between index and positive test indicated possible high risk of bias in 3 studies for the fourth domain. However, in applicability judgement, we determined most studies as low risk, since included patients, index test, and reference standard of each study matched the following review question.


Figure 2. Forest plot: Pooled sensitivity and specificity of Saliva RT-LAMP

Figure 3. Forest plot of subgroup analysis: RNA extraction

Figure 4. Forest plot of subgroup analysis: RNA extraction and Buffer usage 4.

DISCUSSION

4.1 Main principles, urgencies, and diagnosing method during COVID-19 Certain combinations of containment applied in the management of COVID-19 are intended to delay the significant consequences of the patients and high demand for care. Early diagnosis plays a vital role in controlling disease progression and limits viral spread in the population. This includes mitigation strategy series to stop further transmission and decrease demand in the healthcare system. As the urgency rises, the rapid and accurate early detection methods of COVID-19 are crucial.26

SARS-CoV-2 and its viral load spread on the respiratory tract, which also occur parallelly in the body fluids and tissues. This condition makes respiratory tract, serum, stool, and saliva samples have various amounts of virus. Therefore, to define an infection, a diagnostic test


should be performed and mainly place focus on two types: (1) Molecular detection (RNA / DNA) related to the suspected pathogen or (2) Serological test to detect antibodies against the pathogen.27

4.2 RT-LAMP as A Diagnostic Test in COVID-19 RT-LAMP is a technology to amplify the DNA at a constant temperature. This diagnostic testing method shows its best at point of care and diagnostic field to detect a wide range of RNA and DNA targets, e.g. filariasis in humans and insects, food and water quality, Zika virus in humans, as well as rapid detection of coronavirus (COVID-19). Performing RT-LAMP by exponentially amplifying the target to utilize six different sequences will simultaneously increase sensitivity and specificity.15

RT-LAMP is widely known for its remarkably rapid and simple independence without involving any expensive reagents or instruments for an extended method.28 This highly specific amplification reaction uses a strand-displacing DNA polymerase that initiates its synthesis to both primers forming a "loop" structure to promote a continuous amplification by extending and adding the annealing primers. To detect RNA viruses, such as SARS-CoV-2, this tool requires an additional heat-stable reverse transcriptase enzyme (RT-LAMP). The reverse transcriptase intends to change viral RNA to complementary DNA (cDNA) as the main target. 29

RT-LAMP engages two inner primers (FIP and BIP) and two outer primers (F3 and B3) that can be recognized in a total of six different regions in a specific DNA. FIP anneals on the inner primers will anneal to the template and extend by polymerase with displacement action such as Bst polymerase.29 This resulted in FIP's product being displaced by the F3 primer. Using an extension reaction such as BIP on the consequent product of FIP, a loop structure will be formed that eliminates denaturing steps. LAMP cycling one inner primer hybridized to the loop on the product comprising original stem-loop DNA and new stem-loop DNA with its inverted repeats with multiple loops by annealing between repetitions of the target in one same single strand.29,30 4.3 “Novel” RT-LAMP vs “Gold-Standard” RT-PCR RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) has been known as gold standard for diagnosing COVID-19 in recent years. RT-PCR enables genes to amplify that make numerous copies using primer sequence and DNA polymerase enzymes. The reliability of RT-


PCR in diagnosis is undoubtable. However, the process shows more complexity, longer in time, and more expensive. To an extent, RT-PCR needed more reagents, indicating the contradiction to a shortage of reagents or samples needed for sample collection and viral RNA extraction. Real time-PCR (rt-PCR) is the most common method of PCR to be used to diagnose because it is clinically more sensitive than the conventional method. This urgency situation forces worldwide to perform the available test. However, given the advantages above, PCR requires high demand of times, medical doctor specialists, and higher cost.31

Various extensive studies showed that RT-LAMP, over RT-PCR as a gold standard, for diagnosing COVID-19 gave significant differences and advantages. RT-LAMP is cheaper, smaller, simpler, and more portable to be carried by health care in the clinical setting. 31 WarmStart Colorimetric Kits, the most common kit used in included studies, have a base cost of approximately US$2-3 per reaction and US$10-15 per result, compared to US$51 of RTPCR test cost. Another advantage is time efficiency in detection of viral RNA, which requires only 1 hour to get the result, whilst PCR takes longer than 8 hours.32,33

Inhibitors during RNA extraction are also tolerated by the RT-LAMP diagnostic method rather than PCR, which requires purification steps when facing unstable reactions proning to inhibitors.34 The notable finding has shown how successful application of various RT-LAMP assays forms to detect displays. A few copies (1-10) of viral RNA template was sufficient to exhibit more successful detection, resulting in 100-fold sensitivity compared to gold standard.

Moreover, innovative solutions such as using saliva samples to detect SARS-CoV-2 are highly likely because of their flexibility to perform efficiently and non-invasive, reduce patient discomfort, and reduce cost reciprocally. Thus, solutive and alternative testing has to be established in accordance to the higher sensitivity, cost-effectiveness, and faster turnaround time than gold standard and diagnostic protocols current time such as LAMP.35 4.4 Sensitivity and Specificity Analysis of RT-LAMP Eleven studies included in this meta-analysis resulted in a notable pooled sensitivity of 88.7% (95% CI: 0.773-0.948) and specificity of 97.9% (95%CI : 0.917-0.995). Two studies19,21 gave a 100% sensitivity while four studies15,17,23,25 showed a sensitivity higher than 90%. In terms of specificity, a value of 100% was also reported in four18,22,25,36 studies and >90% specificity was found in other four studies16,17,20,21. Nonetheless, the use of saliva inevitably causes a


decrease in sensitivity and specificity. Compared to diagnosis using NP swabs, this value was lower. According to a meta-analysis done by Tsang, et al37, highest sensitivity gained when RT-PCR was done using NP swabs (95% [95% CI: 93–100]) as well as the specificity (99% [95% CI: 98-100%]). The study also reported a much lower sensitivity for RT-PCR done using saliva samples (85% [95%CI: 75-93%]) and relatively stable specificity of (99% [95% CI: 9899%]). This phenomenon was also observed with RT-LAMP. Subali, et al38 found a significant cumulative sensitivity (95.5% [95% CI: 90.8-97.9%]) and specificity (99.5% [95% CI: 97.799.9%]). Thus, considering the ease of use (easier technique and less invasive), reduction in time, cost, and human resources required, RT-LAMP using saliva samples has considerable potential to be used as a commercial diagnosis kit for SARS-CoV-2. 4.5 RT-LAMP Optimization: RNA Extraction and Buffer Usage Several studies have already attempted to use RNA extraction-free RT-LAMP for a lower cost, faster and easier procedure in SaRS-CoV-2 diagnosis. However, as expected, when compared to RT-LAMP that did RNA extraction before, the sensitivity of RT-LAMP without RNA extraction is lower. With an increment in sensitivity results, from 88.7% (95% CI: 0.773-0.948) to 92% (95% CI: 0.833-0.964), our results are aligned with this theory. Several studies are found to support the importance of RNA extraction in increasing sensitivity. 16,39 Amaral, et al15 found that the increased concentration of viral sequence in saliva samples cause a change in detection of SARS-CoV-2 positive patients from one to eight out of ten patients, improving sensitivity from 85% to 100%. Taki, et al36 further reported a decrease in sensitivity (from 94% [95%CI:71–100%] to 47% [95%CI: 23–72%]) of RT-LAMP when RNA extraction is not done. In contrast, a slight decrease in specificity (96.4% [95%CI: 0.849-0.992]) of RT-LAMP diagnosis may result from a decrease in the number of studies included.

Moreover, it is reported that several sample treatments done before the analysis can influence the RT-LAMP results22. False positive results can appear from acidic saliva samples as the RTLAMP method is based on the decrease in pH resulting from the amplification of a target. Thus, a use of a buffer at pH 7.7 is important in increasing saliva pH for acidic samples since saliva pH ranges from 6.2-7.6. In addition, it is found that the pH should not exceed 8 because it may inhibit the reaction. Rubio, et al18 stated that false negative results were found when phosphate buffer with pH 8.4 and borate buffer with pH 8.2 used. Buffering agents that tend to inhibit the pH change (e.g., tris-acetate or tris-borate) certainly should be avoided to prevent false negative signals. Aside from the buffer, a saliva stabilization solution, such as


ethylenediaminetetraacetic acid (EDTA)

at pH 8.0, dithiothreitol (DTT), and Tris(2-

carboxyethyl)phosphine (TCEP), is proven to play a role in establishing an optimal pH.18,22

The fact that buffer usage can influence RT-LAMP results is further proven with an increase in sensitivity [93.5% (95% CI: 0.887-0.964)]. As in RNA extraction combined RT-LAMP analysis, a slight reduction in specificity [95.6% (95%CI: 0.869-0.986)] was shown. 4.5 Challenges and Prospects Ahead Our study proposes saliva RT-LAMP as an alternative diagnosis method for SARS-CoV-2 as it gives a considerable sensitivity and specificity. However, several limitations conducted in those studies are the small sample size for diagnostic test accuracy, and unclear risk of bias in most studies in domain 2 (index test) because no information stated that the index test was interpreted after the reference test is known. Despite the limitations stated above, the included samples were geographically distributed, which is potentially applicable worldwide.

Furthermore, there will be some challenges waiting ahead through the development of the RTLAMP optimization method, hunting for the best sensitivity and specificity. However, if the researchers are able to overcome these limitations, this tool might have fascinating prospects during this ongoing pandemic or even as a preparation for future one. 5.

Conclusion and Recommendation

To summarize, saliva RT-LAMP is a promising diagnostic tool in COVID-19 situation, evident in remarkable pooled sensitivity and specificity compared to the gold standard. 5.1 Recommendations RT-LAMP methodology is well established for a massive population. However, before introducing it as a standard for diagnostic test, the fixed acceptable protocol containing the best method has to be assigned. This can be implied after several technical predicaments, especially for optimization methods, are solved. Therefore, future studies and updated systematic review are still needed to obtain the best one.


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Appendix Appendix 1. QUADAS-2 Assessment Scale (Cross-sectional studies)

Appendix 2. SROC plot and summary points: Pooled sensitivity and specificity of Saliva RT-LAMP


Appendix 3. SROC plot and summary points of subgroup analysis: RNA extraction

Appendix 4. SROC plot and summary points of subgroup analysis: RNA extraction and Buffer usage


Knowledge Rate of Adverse Effect Following Immunization in the Community and its Impact on Vaccine Hesitancy Annazwa Farahdilla1, Asniar Fauzia2, Rosalia Dewi Pratiwi3, Dea Alfahira4 Alkhairaat University


ABSTRACT Intro : The vaccination target in Indonesia is 208 million people. The COVID-19 vaccination has penetrated more than 100 million people who received the first dose in Indonesia. Adverse Event Following Immunization (KIPI) has become a social media community lately. We will investigate the level of knowledge about adverse effects after immunization (AEFI) and their impact on vaccine doubt. Objective: To determine the relationship between knowledge level of AEFIs and doubt for vaccines Method: This was a type of Analytical research using a quantitative approach. The research instruments in this study using an online questionnaire. The data is processed with using IBM Statistics 23. Results: Age characteristics of the majority of respondents based on age were 20 years as many as 72 respondents (70.6%), Gender characteristics of the majority of respondents based on gender were 77 respondents (75.5%), Professional characteristics of the majority of respondents based on professions are students as many as 87 respondents (85.3%), Domicile characteristics of respondents who filled out this questionnaire from 17 provinces in Indonesia the majority of respondents based on domicile came from Central Sulawesi as many as 39.2% respondents. The result show that Adverse event knowledge level following immunization was not related to vaccine doubt after being tested for correlation using SPSS IBM 23 with Pearson Correlation analysis.

This study was conducted with the aim of knowing the relationship between knowledge about AEFI (post-immunization follow-up events) and the level of doubt about vaccination. Where the research is carried out by distributing online questionnaires to collect the required data. Then the data is processed using IBM SPSS Statistics 23.

This question consists of 18 questions related to AEFI and 6 questions related to the level of vaccine doubt presented in the form of a score of 1-5.

Conclusion : On our findings showed that knowledge rate of adverse effect following immunization (AEFI) and its impact on vaccine hesitancy are not collarated.


Knowledge Rate of Adverse Effect Following Immunization in the Community and its Impact on Vaccine Hesitancy Annazwa Farahdilla1, Asniar Fauzia2, Rosalia Dewi Pratiwi3, Dea Alfahira4 Alkhairaat University


ABSTRACT Intro : The vaccination target in Indonesia is 208 million people. The COVID-19 vaccination has penetrated more than 100 million people who received the first dose in Indonesia. Adverse Event Following Immunization (KIPI) has become a social media community lately. We will investigate the level of knowledge about adverse effects after immunization (AEFI) and their impact on vaccine doubt. Objective: To determine the relationship between knowledge level of AEFIs and doubt for vaccines Method: This was a type of Analytical research using a quantitative approach. The research instruments in this study using an online questionnaire. The data is processed with using IBM Statistics 23. Results: Age characteristics of the majority of respondents based on age were 20 years as many as 72 respondents (70.6%), Gender characteristics of the majority of respondents based on gender were 77 respondents (75.5%), Professional characteristics of the majority of respondents based on professions are students as many as 87 respondents (85.3%), Domicile characteristics of respondents who filled out this questionnaire from 17 provinces in Indonesia the majority of respondents based on domicile came from Central Sulawesi as many as 39.2% respondents. The result show that Adverse event knowledge level following immunization was not related to vaccine doubt after being tested for correlation using SPSS IBM 23 with Pearson Correlation analysis.

This study was conducted with the aim of knowing the relationship between knowledge about AEFI (post-immunization follow-up events) and the level of doubt about vaccination. Where the research is carried out by distributing online questionnaires to collect the required data. Then the data is processed using IBM SPSS Statistics 23.

This question consists of 18 questions related to AEFI and 6 questions related to the level of vaccine doubt presented in the form of a score of 1-5.

Conclusion : On our findings showed that knowledge rate of adverse effect following immunization (AEFI) and its impact on vaccine hesitancy are not collarated.

A. INTRODUCTION


During the past 1 year, clinically-available COVID- 19 vaccines have been developed at an unprecedented speed. According to the latest data of World Health Organization (WHO), at least 10 kinds of COVID-19 vaccines based on multiple technologies, represented by inactivated vaccine, viral vector vaccine and mRNA vaccine, have been approved for emergency clinical use or conditional marketing. With COVID-19 vaccines for mass vaccination, one extremely important prerequisite is to illustrate their safety with confirmed clinical evidences. Vaccine hesitancy, which refers to the delay in acceptance or refusal of available vaccination, is a common public problem in the application and promotion of various vaccines. In particular, the accelerated development process of COVID-19 vaccines might raise more concerns regarding their potential safety problems, and thereby deepen the vaccine hesitancy among people. The vaccination target in Indonesia is 208 million people. As of Sunday (10/10) the COVID-19 vaccination has penetrated more than 100 million people who received the first dose. Adverse Event Following Immunization (AEFI) has become a social media community lately. We will investigate the level of knowledge about adverse effects after immunization (AEFI) and their impact on vaccine doubt. Vaccine production is done by modern biotechnology that is expected to produce good quality vaccines though none could be perfect. The use of large quantities of vaccines requires monitoring of Adverse Event Following Immunization (AEFI) -WHO, better known as Kejadian Ikutan Pasca Imunisasi (KIPI) in Indonesia." In the context of COVID-19 vaccination, surveillance systems need to be prepared for identifying and responding to both adverse events following immunization (AEFIs) and adverse events of special interest (AESIs) as well as other safety events that may cause public concern, including incidents of substandard or counterfeit vaccines. AEFIs and AESIs can be detected through passive and active surveillance, respectively. However, there are still many Indonesians who are hesitant to vaccinate, due to the high number of adverse event following immunization (AEFI) and lack of knowledge about the adverse event following immunization (AEFI). We will investigate the knowledge level of adverse event following immunization (AEFI) and its impact on vaccine doubt.

B. MATHERIAL AND METHOD

1. Study Design


This study used an analytic design with a cross sectional design. This study is a quantitative study by distributing forms of knowledge level of Post-Immunization Adverse Events (AEFI) and the level of doubt about vaccines. 2. Inclusion Criteria In this study, the inclusion criteria were individuals over 18 years old, the general public, physically and mentally healthy and willing to be respondents. 3. Exclusion Criteria In this study, the exclusion criteria were respondents who did not complete the questionnaire completely. 4. Instrument The research instruments in this study were In this study, using an online questionnaire via Google Form, namely the Adverse Event Following Immunization (AEFI) knowledge level test and the doubt scale about vaccines with the respondent's level of knowledge. The Adverse Event Following Immunization (AEFI) knowledge level test in the form of multiple choice consists of 18 questions with 2 answer choices made by the researcher. Test the level of knowledge using a Likert scale. Knowledge level difficulty test, validity and reliability test on vaccine doubt scale conducted twice, namely on Sunday, November 7, 2021 (49 respondents) and Thursday, November 11, 2021 (39 respondents). Subjects answered a test containing 18 multiple choice questions with 2 answer choices without being given a time limit. analysis was then performed using IBM Statistics 23. Difficulty level test carried out on 18 item questions to determine the level of difficulty each item tested. Problems that are too easy will make the effort expended by the respondent to think about the answer is not optimal, on the other hand, a question that is too difficult will make the respondent choose the answer at random. The results of the difficulty level test of 18 item items obtained 12 questions in the easy category, and 6 questions with medium category. The results of the validity test based on the output "Correlations", it is known that the value of Sig. (2-tailed) for the relationship or correlation of the vaccine hesitancy scale is 0.000 < 0.05 and the Pearson Correlation has a positive value of 0.555, it can be concluded that the vaccine hesitancy scale is valid. Because the scale item was declared valid, the item was used as an accurate data collection tool in this study.


The results of the reliability test are known to have N of items (the number of items or statements in the questionnaire) there are 6 items with a Cronbach's Alpha value of 0.907. Because the Cronbach Alpha value is 0.907> 0.60, as the basis for taking the reliability test above, it can be concluded that the 6 or all items for the vaccine hesitancy questionnaire are consistent. 5. Data Analysis This data is processed through several stages, starting from the distribution of questionnaires where this questionnaire is a tool used to collect data so that it is possible to carry out related analyzes so that information can be obtained that can be implemented, then the data is processed using SPSS IBM 23 with analyze Kolmogorov Smirnov normality test after the results are obtained then we continune analysis with Pearson bivariate correlation analysis. The results of the normality test based on the SPSS output table are known to have a significance value of Asiymp.Sig (2-tailed) of 0.13 which is greater than 0.05. then according to the basis of decision making in the Kolmogorov-Smirnov normality test, it can be concluded that the data are normally distributed. Thus the assumptions or requirements for normality in the regression model have been met. The independent variable in this study is about AEFI (post-immunization follow-up events) while the dependent variable is COVID-19 vaccination. Based on the Significance value of sig.(2.tailed): from the output table, it is known that the value of sig.(2.failed) between AEFI (VAR1) and the level of vaccine doubt (Unstandardized Residual) is briefly 0.1000 > 0.05, which means there is no significant correlation between the AEFI variable (VAR1) and the level of vaccine doubt (Unstandardized Residual). Furthermore, the relationship between Vaccine (VAR2) and the level of vaccine doubt (Unstandardized Residual) has a sig value. (2.Tailed) of 0.000 < 0.05, which means that there is a significant correlation between the Vaccine variable (VAR2) and the level of vaccine doubt (Unstandardized Residual).

C. RESULT AND DISCUSSION Vaccine hesitancy has been a developing mission for public health in current decades. Vaccine hesitancy refers to delay in acceptance or refusal of vaccination despite availability of vaccination services. Vaccine hesitancy is complex and context


specific, varying across time, place and vaccines. Among factors contributing to vaccine hesitancy, knowledge regarding Adverse Event Following Immunization (AEFI) play the leading role. But, the results showed that the survey of knowledge level of AEFI (post-immunization co-occurrence) had no effect on the level of vaccine doubt, because knowledge about AEFI among the community is lower, but the average community has completed the vaccination program.

D. CONCLUSSION AND RECOMENDATION This study was conducted with the aim of knowing the relationship between knowledge about AEFI (post-immunization follow-up events) and the level of doubt about COVID-19 vaccination. and the results of this study explain that there is no relationship between knowledge about AEFI (post-immunization follow-up events) and the level of doubt about COVID-19 vaccination. For further research, it is hoped that researchers will see more specific problems regarding AEFI.

E. REFERANCE 1. Chen M, Yuan Y, Zhou Y, Deng Z, Zhao J, Feng F, et al. Safety of SARS-CoV-2 vaccines: a systematic review and meta-analysis of randomized controlled trials. Infect Dis Poverty [Internet]. 2021;10(1):1–12. Available from: https://doi.org/10.1186/s40249-021-00878-5

2. Bralianti PD, Akbar FN. Covid-19 Vaccines and its Adverse Events Following Immunization( AEFI) In Indonesia| bralianti | The Avicenna Medical Journal. Vol. 2, The Avicenna Medical Journal. 2021. p. 19–27

3. WHO. Monitoring and Responding To Adverse Events Following Immunization (Aefis). Covid-19 Vaccines Saf Surveill Man [Internet]. 2020;26. Available from: https://www.who.int/docs/default-source/covid-19-vaccines-safety-surveillancemanual/covid19vaccines_manual_aefi_20210104

4. MacDonald NE, Eskola J, Liang X, Chaudhuri M, Dube E, Gellin B, et al. Vaccine hesitancy: Definition, scope and determinants. Vaccine. 2015;33(34):4161–4.


F. APPENDIX

A. AREA FOR THE STANDARD NORMAL DISTRIBUTION

One-Sample Kolmogorov-Smirnov Test Unstandardiz ed Residual N

45

Normal Parametersa,b

Mean Std. Deviation

.0000000 4.35505948

Most Extreme

Absolute

.150

Differences

Positive

.098

Negative

-.150

Test Statistic

.150 .013c

Asymp. Sig. (2-tailed)

B. CORRELATIONS VAR1 VAR Pearson 1

VAR2 1

Correlation Sig. (2-tailed)

.249

N VAR Pearson 2

Correlation

-.175

98

45

-.175

1

Sig. (2-tailed)

.249

N

45

45

C. QUESTIONNAIRES VACCINE HESITANCY Variabel

Aspek

Indikator

Item

Rating 1 2 3 4 5

Komentar


Vaccine Hesitancy

Confidence: Belief in the effectiveness and safety of vaccines including the reliability and competence of healthcare services

Trust in vaccine safety

Belief in vaccine effectiveness

I have completed the stage 1 vaccination program I'm not afraid to get vaccinated after knowing AEFI By knowing AEFI I feel safe to join the COVID19 vaccine program After knowing AEFI I feel no hesitation about getting vaccinated I invite friends, family and relatives to join the vaccination program After knowing AEFI I support the vaccination program


PCC EAMSC 2022 : EGYPT

IMPACT OF TELEMEDICINE ON PATIENTS’ SATISFACTION: A SYSTEMATIC REVIEW

Authors : Azzahra Fatinnuha Azmi Prayogi Putri (23181) Farrel Abiel Prazov (22832) Farrel Alfaza Marsetyo (22946) Umar Surya Kusuma Atmaja (22870)

AMSA-UNIVERSITAS GADJAH MADA 2021


ABSTRACT Introduction Since COVID-19 was declared as the global pandemic, the offline healthcare service system has been revised in response to health protocols suggesting people to stay more often at home and reduce unnecessary travels. To overcome the difficulty in getting heatlhcare services, telemedicine is introducted as an alternative choice for patients, especially those who have only mild symptomps. This review was conducted based on reviewer’s curiosity about patients' satisfaction level on the use of telemedicine, which began to be widely used during the COVID-19 pandemic. Method The systemic review was performed on three databases namely PubMed, Liebertpub, and Sagepub using PRISMA-P model. A total of 124 records were obtained in the preliminary search, and the final 10 studies were included. To assess bias, trustworthiness, and relevance of each journal, the Joanna Briggs Institute’s critical appraisal tools and validated quality assessment tools were selected.

Results & Discussion All of the studies included in the data analysis agreed that the majority of patients using telemedicine services were satisfied with what they experienced. The lowest patients satisfication rate is 74% while the highest even scored 100%. Some factors that affected patients’ satisfaction in using telemedicine were economic factors, convinience and ease of access, and decreased risk of covid-19 infection

Conclusion After reviewing ten articles, it was concluded that most patients were satisfied with treatment that they got from telemedicine. The result was influenced by several factors such as: economic factors, convenience and ease of access, and decreased risk of COVID-19 infection.


PCC EAMSC 2022 : EGYPT

IMPACT OF TELEMEDICINE ON PATIENTS’ SATISFACTION: A SYSTEMATIC REVIEW

Authors : Azzahra Fatinnuha Azmi Prayogi Putri (23181) Farrel Abiel Prazov (22832) Farrel Alfaza Marsetyo (22946) Umar Surya Kusuma Atmaja (22870)

AMSA-UNIVERSITAS GADJAH MADA 2021


INTRODUCTION Health services aim to not only provide education but also carry out preventive, curative, and rehabilitative activities. To achieve this goal, solid support between health workers and available health facilities is urgently needed. The health care facilities themselves can be grouped into several types as type 1, type 2, and type 3. Type 1 is intended to treat patients with general illnesses, type 2 serves patients with a need for specialist doctors, and type 3 is for patients with acute illness and those who require a sub-specialist doctor. The form of health facilities can generally be found in the form of independent practices, health centers, clinics, and hospitals. Similar to health services, health care facilities also have basic indicators, namely prioritizing and striving to provide patient satisfaction1. Access to healthcare services is normally available in every district. When ill, patients can set an appointment to meet the providers. However, since COVID-19 was declared as the global pandemic, this offline service has been revised in response to health protocols suggesting people to stay more often at home and reduce unnecessary travels. What is more is the fact that patients with only mild symptoms are not prioritized as the service is allocated to patients with COVID-19. As the number of people getting infected is rising, not only do healthcare services suffer from the medical supply shortages but also medical practitioners from working extra hours. This chaotic situation has led to more emergency health policies, one of which is the introduction of telemedicine, designed for patients who carry mild symptoms. Telemedicine applications such as Halodoc and Alodokter surge to a record high to cater the needs. Telemedicine is basically the use of technology including applications, web, telephone by health workers to communicate with their patients 2. Doctors can diagnose the illness and prescribe medication using this application. They can also make online visits using the available apps if the disease suffered by the patient is still on the green to early orange color scale. Besides, writing a health referral can be performed if serious cases are detected. That is why, utilization of telemedicine will greatly help many patients, especially those in the green zone. This research was conducted based on reviewer’s curiosity about patients' satisfaction from the use of telemedicine, which began to be widely used during the COVID19 pandemic. The author see that telemedicine can be put to better use and its relation in examining what long-term effects can be obtained from using telemedicine.


MATERIAL & METHODS Systematic review using the PRISMA statement’s flow diagram and checklist were employed in order to enhance the quality of the report. PRISMA diagram includes a checklist of twenty seven points and a four-phases flow diagram3. The checklist items are considered critical in systematic review transparency. A. Data Collection Technique Search strategy The systemic review was performed on three databases namely PubMed, Liebertpub, and Sagepub. A set of keywords was used to find articles that discussed the patient satisfaction on telemedicine, for instance (satisfaction OR pleasure OR fulfillment) AND (patient) AND (telemedicine OR telehealth). Study selection The included studies fulfilled several inclusion criteria. The PICO model was adapted for inclusion criteria. The participants of the studies must be the users of telemedicine; the context must be in community; and the aim of the research should be related to patient satisfaction on telemedicine taking place in the USA. The method was limited to a cross-sectional method because this method explains the relationship between exposure to study participants (users of telemedicine) and the outcome (patient satisfaction on telemedicine) which corresponded with the purpose of this study4. The study would be excluded if (1) not written in English; (2) inaccessible; and (3) published before 2016. A considerable time limit was set to find the most relevant studies. In addition, review papers were also excluded. Risk of bias assesment To assess bias, trustworthiness, and relevance of each included journal, review triangulation technique was selected. Two reviewers were invited to assess all included studies independently and to avoid individual bias . Both reviewers also 7

evaluated the journals using a critical appraisal checklist from the Joanna Briggs Institute’s critical appraisal tools and validated quality assessment tools consisting of a checklist of 8 criteria5. For each criteria fulfilled, each journal was given one score. Journals that scored >= 6 were regarded as high quality and were then included in the data extraction phase.


B. Data Analysis Data from included studies were extracted to obtain data about the patients’ satisfaction rate in using telemedicine. The following data were extracted from eligible studies : author’s name, year of publication, mean age, valid measurement tool, and outcome. C. Literature Search Timeframe The literature search was conducted from October 2021 to November 2021. RESULTS & DISCUSSION RESULT

Identification

A. Study Search Result Records identified through database searching (N=124) PubMed (n=99) Sagepub (n=21) Liebertpub (n=4)

Screening

Record excluded due to duplications (N=19) Records screened based on inclusionexclusion criteria (N=105) 1. 2. 3. Eligibility

4. Records underwent full-text eligibility screening (N=27)

Record excluded due to reasons below (N=78) Published before 2016 (n=15) Incomptible study design (n=28) Data does not correlate with the topic (n=25) Full article not retrieved (n=10)

Included

Record excluded after full-text & eligibility screening (N=17) 5. Incompatible study design (n=5) 6. Data does not correlate with the topic (n=7) 7. Insufficient data (n=5) Studies included to the systematic review (N=10)

Figure 1. PRISMA Flow Chart Diagram


B. Risk of Bias Assesment A total of 10 studies passed our initial screening, inclusion and exclusion criteria. These studies were then subjected to rigorous assessment using the appropriate appraisal tools for each method. Table 1 shows the result of the critical appraisal process using the Joanna Briggs Institute’s Critical Assessment Tools. From this process, the author deduced that all 10 studies were of high quality; thus they were included in the data extraction. C. Characteristic of Cross-Sectional Studies There were 65,579 participants from 10 articles of cross-sectional study that had been obtained. The mean range of the participants was 18-60 years old. All studies addressed the patient satisfaction rate in using telemedicine. The characteristics of each cross-sectional study are described in Table 2. D. Outcome & Data Analysis All of the studies included in the data analysis agreed that the majority of patients using telemedicine services were satisfied with what they experienced. In a study conducted by Yoon et al., it was found that 97.1% of telemedicine users in their study were satisfied with their treatment6. Research conducted by Hentati et al. also supports the patient satisfaction on telemedicine by 80% of patients that use telemedicine were satisfied7. Phenicie et al. reported that the rate of patient satisfaction on telemedicine is 87%8. The study conducted by Tenforde et al. show that 86.8% were satisfied with telemedicine so that they want to use it again in the future9. Rawaswamy et al. also reported that 93.4% of patients were satisfied with telemedicine10. Mustafa et al., also supported by his study that nearly 97% of patients were satisfied with their telemedicine encounter11. The research conducted by Mortezavi et al. showed that the majority of the patients (74%) were satisfied with their virtual visit12. Study conducted by Fraint et al. reported that most telemedicine users (75.5%) were satisfied with their telemedicine, including 69% who indicated they would favor telemedicine visits over traditional in person appointments in the future whenever feasible13. Research conducted by Xu et al. showed an impressive result that all of the telemedicine users (100%) were satisfied with their telemedicine


treatment14 and this is supported by a study conducted by Martinez et al. that show 85% of patients were satisfied with telemedicine15. Overall, these ten articles show that most patients were satisfied with their telemedicine treatment. DISCUSSION The author established that most patients that use telemedicine are satisfied with their experience. But in order to ensure that universal high-quality care via telemedicine is always delivered, it is important for healthcare providers to know the factors that affect patients’ satisfaction in using telemedicine. A. Economic Factors Our findings suggest that economic factors play a significant role in increasing patient’s satisfaction while using telemedicine. Telemedicine services save a considerable amount of cost compared to in person visits 16,18. This is especially important for people that are uninsured, since they are able to spend less to get equally good healthcare8. Giving coupons for telemedicine services also increases patients satisfaction, possibly because it gives patients a chance to get acquainted with telemedicine thus increasing their satisfaction afterwards 25. Additionally, with telemedicine, patients in rural areas won’t have to spend additional money to travel to the nearest clinic, thus cutting prices significantly21. B. Convenience and Ease of Access Convenience is a major factor that drives patient satisfaction in using telemedicine, especially with the prevalence of smart handheld devices worldwide. Telemedicine allows patients to access healthcare from the comfort of their own homes, eliminating the time and money required to travel to a clinic, and reducing risks of accidents along the way19,21. Additionally, high satisfaction and usage of telemedicine by women are associated with the perception of shorter wait times, as women tend to hold multiple domestic responsibilities8,9. C. Decreased Risk of COVID-19 Infection The surge in cases of COVID-19 worldwide has forced many clinics to transition to telemedicine in providing health services towards patients 19,20. Satisfaction in telemedicine use is reported to be higher during the COVID-19 pandemic than before10. This increase could possibly be attributed to telemedicine’s


ability to connect people and maintain a sense of belonging that could increase overall patients quality of life17.

Hopes for future use of telemedicine Telemedicine has been used to deliver healthcare to patients for a long time, but has recently experienced a surge in usage like never before due to the pandemic. With the majority of patients that have used telemedicine are likely to recommend it to others and are likely to use it again in the future, this trend won’t likely to be stopped in the near future. Although telemedicine has many benefits, advantages, and is highly satisfying for patients, telemedicine has its own share of uncertainty and doubts regarding security. We hope that these issues could be tackled immediately so that universal and more affordable healthcare could be achieved. Strengths and Limitation of the Study Telemedicine is a topic that is currently still hot to raise, especially in the current era of the COVID-19 pandemic. The use of telemedicine is increasing and more and more people are familiar with online health services. However, this also raises another weakness, namely the lack of articles discussing patient satisfaction with the use of telemedicine itself. It is quite difficult to find articles whose data is in accordance with what the reviewers want to raise in this systematic review. Therefore, the authors only included 10 articles using the cross-sectional study method. Hence, studies with more rigorous methods such as randomized controlled trials still need to be carried out in this area CONCLUSION After reviewing ten articles, it was concluded that most patients were satisfied with treatment that they got from telemedicine. The result was influenced by several factors such as: economic factors, convenience and ease of access, and decreased risk of COVID-19 infection. In addition, there were very few primary studies that were related to patient satisfaction on telemedicine, especially for particular areas. For future research, primary studies that discuss patient satisfaction on telemedicine are needed. The interventions could be based on the factors that influence the patients satisfaction on telemedicine that have been discussed in this study. For practice, the authors recommend that better management is


needed to improve telemedicine. With better management, the higher rate of patient satisfaction on telemedicine can be achieved.


REFERENCES 1. Kichloo A, Albosta M, Dettloff K, Wani F, El-Amir Z, Singh J et al. Telemedicine, the current COVID-19 pandemic and the future: a narrative review and perspectives moving forward in the USA. Family Medicine and Community Health. 2020;8(3):e000530 2. Peraturan Menteri Kesehatan Republik Indonesia Nomor 75 Tahun 2014 tentang Pusat Kesehatan Masyarakat 3. Moher D. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. Annals of Internal Medicine. 2009;151(4):264. 4. Setia MS. Methodology Series Module 3: Cross-sectional Studies. Indian J Dermatol. 2016;61(3):261–4. 5. The Joanna Briggs Institute. CRITICAL APPRAISAL TOOLS [Internet]. 2020 [cited 2021 Nov 12]. Available from: https://joannabriggs.org/critical-appraisaltools 6. Yoon E, Tong D, Anton G, Jasinski J, Claus C, Soo T et al. Patient Satisfaction with Neurosurgery Telemedicine Visits During the Coronavirus Disease 2019 Pandemic: A Prospective Cohort Study. World Neurosurgery. 2020;145:e184-e191 7. Hentati F, Cabrera C, D'Anza B, Rodriguez K. Patient satisfaction with telemedicine in rhinology during the COVID-19 pandemic. American Journal of Otolaryngology. 2021;42(3):102921. 8. Phenicie R, Acosta Wright R, Holzberg J. Patient Satisfaction with Telehealth During COVID-19: Experience in a Rural County on the United States–Mexico Border. Telemedicine and e-Health. 2021;27(8):859-865. 9. Tenforde A, Borgstrom H, Polich G, Steere H, Davis I, Cotton K et al. Outpatient Physical, Occupational, and Speech Therapy Synchronous Telemedicine. American Journal of Physical Medicine & Rehabilitation. 2020;99(11):977-981. 10. Ramaswamy A, Yu M, Drangsholt S, Ng E, Culligan P, Schlegel P et al. Patient Satisfaction With Telemedicine During the COVID-19 Pandemic: Retrospective Cohort Study. Journal of Medical Internet Research. 2020;22(9):e20786. 11. Mustafa S, Yang L, Mortezavi M, Vadamalai K, Ramsey A. Patient satisfaction with telemedicine encounters in an allergy and immunology practice during the coronavirus disease 2019 pandemic. Annals of Allergy, Asthma & Immunology. 2020;125(4):478-479.


12. Mortezavi M, Lokineni S, Garg M, Chen Y, Ramsey A. Rheumatology Patient Satisfaction With Telemedicine During the COVID-19 Pandemic in the United States. Journal of Patient Experience. 2021;8:237437352110088. 13. Fraint A, Stebbins G, Pal G, Comella C. Reliability, feasibility and satisfaction of telemedicine evaluations for cervical dystonia. Journal of Telemedicine and Telecare. 2019;26(9):560-567. 14. Xu T, Pujara S, Sutton S, Rhee M. Telemedicine in the Management of Type 1 Diabetes. Preventing Chronic Disease. 2018;15. 15. Martinez K, Rood M, Jhangiani N, Kou L, Rose S, Boissy A et al. Patterns of Use and Correlates of Patient Satisfaction with a Large Nationwide Direct to Consumer Telemedicine Service. Journal of General Internal Medicine. 2018;33(10):17681773. 16. Nord G, Rising K, Band R, Carr B, Hollander J. On-demand synchronous audio video telemedicine visits are cost effective. The American Journal of Emergency Medicine. 2019;37(5):890-894. 17. Pappot N, Taarnhøj G, Pappot H. Telemedicine and e-Health Solutions for COVID19: Patients' Perspective. Telemedicine and e-Health. 2020;26(7):847-849. 18. Courneya P, Palattao K, Gallagher J. HealthPartners’ Online Clinic For Simple Conditions Delivers Savings Of $88 Per Episode And High Patient Approval. Health Affairs. 2013;32(2):385-392. 19. Dorsey E, Okun M, Bloem B. Care, Convenience, Comfort, Confidentiality, and Contagion: The 5 C’s that Will Shape the Future of Telemedicine. Journal of Parkinson's Disease. 2020;10(3):893-897. 20. Jalali MS, Landman A, Gordon WJ. Telemedicine, privacy, and information security in the age of COVID-19. Journal of the American Medical Informatics Association 21. Buvik A, Bergmo T, Bugge E, Smaabrekke A, Wilsgaard T, Olsen J. CostEffectiveness of Telemedicine in Remote Orthopedic Consultations: Randomized Controlled Trial. Journal of Medical Internet Research. 2019;21(2):e11330.


TABLE AND FIGURES Table 1. Risk of Bias Assesment

et a.,

e et al.,

e et al.,

2020

2021

2021

2020

1

1

1

1

1

0

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

Were confounding factors identified?

1

1

1

1

1

1

1

1

1

1

Were strategies to deal with confounding

1

1

1

1

1

1

1

0

0

0

1

1

1

1

1

1

1

1

1

1

Was appropriate statistical analysis used?

1

1

1

1

1

1

1

1

1

1

Total (borderline score = 6)

8

8

8

8

8

7

8

7

7

7

et al., 2020

et al., 2020

zavi et al., 2021

Fraint

Xu et

et al.,

al.,

2019

2018

Marti

et al.,

wamy

Mustafa

Morte

Hentati

Were the criteria for inclusion in the

Phenici Tenford

Rawas

Yoon

nez et al., 2018

sample clearly defined? Were the study subjects and the setting described in detail? Was the exposure measured in a valid and reliable way? Were objective, standard criteria used for measurement of the condition?

factors stated? Were the outcomes measured in a valid and reliable way?


Table 2. Characteristics of Cross-sectional Studies Author

Sample size (n)

Mean age (years)

Yoon et al.,

310

60.9 ± 13.60

(2020)

Telemedicine service(s) provided Telemedicine visits for Neurosurgery outpatients clinic

Percentage of satisfied responders 97,1%

via Google Meet and Facetime (Apple Inc, Cupertino, California)

Hentati et

45

53,5

al., (2021) Phenicie et

Rhinology Virtual Visits using Doxy.me (Doximity Inc.)

80%

or MDLive (MDLive Inc.). 562

34,4

205

32

Chiricahua Community Health Centers

87%

al., (2021) Tenforde et al., (2020) Ramaswam

Telerehabilitation programs for Physical (PT),

86,8%

Occupational (OT), and Speech Therapy (SLP) 38609

58,8

177

33

Synchronous video visits

93,4%

y et al., (2020) Mustafa et al., (2020)

Telemedicine encounters using third party apps : Epic Warp (Epic Systems Corp, Verona, Wisconsin); Skype (Skype Communications, Palo Alto, California); FaceTime (Apple Inc, Cupertino, California); and Doximity (Doximity, San Francisco, California)

97%


Mortezavi

359

59

Telephone and video calls

74%

46

18

Computer-based visit

75,5%

54

53,5

The Atlanta VAMC Endocrinology Telehealth Clinic

100%

24.040

34,2

Direct to consumer (DTC) telemedicine

85%

et al., (2021) Fraint et al., (2019) Xu et al., (2018) Martinez et al., (2018)


Relationship Between PrEP Use in High-Risk HIV Individuals and The Incidence of Other STIs: A Systematic Review Bhumika Raisinghani1, Jocelyn Nathania Susanto1 1

Faculty of Medicine, Pelita Harapan University, Tangerang, Banten, Indonesia ABSTRACT

Introduction: Human Immunodeficiency Virus (HIV) is a global public health issue responsible for the worldwide HIV/AIDS pandemic. Pre-Exposure Prophylaxis (PrEP) is used as prevention for individuals at high risk for HIV infection, such as men who have sex with men (MSM). Concerns are still present regarding the potential increase in Sexually Transmitted Infections (STIs) following PrEP initiation as change in sexual risk behaviors may influence STI incidence. Objective: This study aims to evaluate the association between PrEP use in individuals at high risk for HIV infection and increased incidence of other STIs. Methods: In this review, we performed a literature search using Pubmed, Pubmed Central (PMC), Science Direct, Link Springer, and Google Scholar databases; along with suitable MeSH term “Human Immunodeficiency Virus”, “Pre-Exposure Prophylaxis” and “Sexually Transmitted Infections”. The inclusion criteria for this study included observational studies, cohort studies, high-risk HIV individuals, and oral PrEP, while the exclusion criteria included systematic reviews, meta-analyses, animal studies, and children. Relevant studies focused on chlamydia, gonorrhea and syphilis as “other STIs”. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the chosen studies. Results: Overall, 5569 studies were identified before the screening procedure. Five cohort studies were confirmed after the selection with a total of 752 patients. Every study fulfilled the NOS criteria, with all 5 studies proving to be of good quality. Our results show that there was a significant increase in STIs in high-risk individuals during PrEP use. Conclusion: In conclusion, the use of PrEP contributes to a significant increase in the incidence of several STIs including chlamydia, gonorrhea, and syphilis, despite lowering HIV incidence.


Relationship Between PrEP Use in High-Risk HIV Individuals and The Incidence of Other STIs: A Systematic Review Bhumika Raisinghani1, Jocelyn Nathania Susanto1 1

Faculty of Medicine, Pelita Harapan University, Tangerang, Banten, Indonesia


Introduction Human Immunodeficiency Virus (HIV) is a retrovirus that has contributed to the worldwide HIV/AIDS pandemic since its first outbreak in 1981. It is now a global public health issue responsible for the 19th leading cause of mortality in 2019, claiming a total of 36.3 million lives thus far.1 The symptomatic stage, Acquired Immunodeficiency Syndrome (AIDS), due to untreated HIV has the potential to develop certain cancers, infections, or more severe, long-term clinical manifestations. At the moment, there is no cure for HIV. Pre-exposure prophylaxis (PrEP) acts as a prevention for individuals at high risk for HIV infection, such as men who have sex with men (MSM). PrEP is proven to be highly effective (>95%) for preventing HIV, reducing the risk of getting HIV by at least 74% when prescribed.2,3 Concerns are still present regarding the potential increase of Sexually Transmitted Infections (STIs) following PrEP initiation, as behaviors of individuals may influence the prognosis of STI transmission including condom use and the number of sexual partners.4 High rates of STIs are observed among PrEP users, and high rates of condomless sex, and hence, increase rates of STIs over time.5 This study included chlamydia, gonorrhea and syphilis as the other STIs in question due to their high morbidities. In an open-label clinical cohort study in California, 50% of individuals on PrEP were diagnosed with an STI within 12 months following PrEP initiation. Moreover, high levels of STI incidence were also observed in the PrEP Demo Project, with an overall STI incidence rate of 90 per 100 person-years.3 Another cohort study included 211 individuals in Los Angeles, which gives a strong result in the association between PrEP and increased STIs incidence. This association is stronger in more recent studies and in studies with longer follow-up, which could reflect increasing confidence among PrEP users in PrEP efficacy and more widespread use of PrEP among at-risk populations.6 Therefore, screening for STIs is essential during PrEP followup and monitoring immediate detection and treatment of STIs. This study aims to evaluate the association between PrEP use in individuals at high risk for HIV infection and increased incidence of other STIs.


Materials and Methods A literature search was performed from several databases including Pubmed, Pubmed Central (PMC), Science Direct, Link Springer, and Google Scholar databases; along with suitable MeSH terms “Human Immunodeficiency Virus”, “Pre-Exposure Prophylaxis”, and “Sexually Transmitted Infections”. The inclusion criteria were observational study, cohort study, high-risk HIV individuals, and oral PrEP, whereas the exclusion criteria were systematic review, meta-analysis, animal study, and children. Relevant studies included those that focused on chlamydia, gonorrhea and syphillis as “other STIs”. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the chosen studies.


Results and Discussion A study by Beymer et al. consisting of 275 individuals, where the majority were between the ages of 30 and 39 at baseline, reported a higher STI testing rate (n=908) during the afterPrEP period than the before-PrEP period (n=755). Although the study showed no change in the overall prevalence of chlamydia, it reported an increase in syphilis from 1.5% in the before-PrEP period to 3.5% in the after-PrEP period and a decrease in the overall prevalence of gonorrhea from 11.7% to 10.3%. The rate ratio for urethral chlamydia was 1.17 (95% CI 0.52 to 2.61). However, there was no statistical significance (P=0.71). The same trends go for urethral gonorrhea (P=0.95), rectal gonorrhea (P=0.33), and pharyngeal gonorrhea (P=0.65). However, there was a 29% increase in rectal chlamydia (rate ratio=1.83; 95% CI 1.13 to 2.98; P=0.01) and a 164% increase in syphilis (rate ratio=2.97; 95% CI 1.23 to 7.18; P=0.02) diagnoses between periods. Their second model reported a significant increase in any STI (rate ratio=1.36; 95%CI 1.06 to 1.74; P=0.02) from the before-PrEP period to the after PrEP period. Beymer et al. study interpreted the discussion section of their paper as risk compensation, which was suggested due to higher STI numbers in a small segment of PrEP consumers in the year following PrEP initiation. Several limitations in this study include the exclusion of individuals with previous PEP or PrEP use, inability to account for individuals who failed to take prescribed medications after PrEP initiation but still tested for STIs, testing for pharyngeal chlamydia despite it not being a standard test for non-PrEP patients. This case-crossover study design is observational and nonrandomized in nature and unavailability of STI testing visits for a full 365-day period for several subjects. However, it is to be noted that this study has several strengths including the PrEP protocol design that required patients to return every 3 months to renew their prescription and STI testing data was collected, both before and after PrEP initiation, on the same individuals who were enrolled in the study.7 Hevey et al. stated in their study that, of 139 patients between the ages of 19 to 71 (mean=37.5) who made appointments between December 2010 and July 2016 at the Infectious Diseases clinic at the academic medical center, 106 patients (76%) were tested for chlamydia, 106 patients (76%) were tested for gonorrhea, and 110 (79%) for syphilis. 11 (10%) of those tested were diagnosed with chlamydia, 8 patients (8%) with gonorrhea and 5 patients (5%) with syphilis. The study reported that 19 patients (17%), of those tested, had at least one STI at baseline, where 17 patients (27%) were diagnosed with chlamydia, 7 patients (11%) diagnosed


Authors Beymer et al.

Study Cohort

Year 2018

Subject 275 individuals majority of which between the ages of 30 and 39 at baseline, White or Latino, gay/MSM and reported having a college degree or higher

Result Statistically significant increase in rectal chlamydia and syphilis

Hevey et al.

Cohort

2018

139 patients between the ages of 19 to 71, 131 males, 71% White, 95% identified as MSM

Significant increase in diagnoses of at least one STI, with overall increase in chlamydia and gonorrhea incidence

Nguyen et al.

Cohort

2018

109 PrEP users, median age 36 years old minimum 18 years, MSM

A 72% increase in overall STIs was observed during 12 months after PrEP initiation relative to 12 months prior

Azarnoosh et al.

Cohort

2021

46 individuals; 69.4% participants were 30–49 years old, and 19.8% were aged ≥50 years, median age at PrEP initiation was 39 years (IQR, 35-48) minimum 18 years, MSM

Significant increase in the number of positive samples for STI after PrEP initiation

Montano et al.

Cohort

2019

183 patients of mean age 31.2 years (SD = 8.9) were included, majority were white (55.7%), MSM

Statistically significant increase in mean number of STI diagnoses per person during PrEP use relative to prior to PrEP use, decrease in condom use during PrEP use also observed

Note: PrEP = Pre-Exposure Prophylaxis STI = Sexually Transmitted Infections MSM = Men who have sex with men

with gonorrhea, and 3 patients (4%) diagnosed with syphilis. During follow-up, it was seen that the number of patients diagnosed with at least one STI increased to 25% (20 of 80 patients). This study found that no other factors were associated with an STI diagnosis except for the duration of


PrEP use. Those who were on PrEP for a longer duration were more likely to have an STI diagnosis than those who were on PrEP for a shorter duration (B = 0.09, SE = 0.04, OR = 1.10, p < 0.05). Given the retrospective nature of the study, data supplied by the patient and the provider may be limited, presenting this characteristic as a limitation towards the study. Another limitation was the lack of PrEP adherence data and the relatively low percentage of patients of African American and Latino descent.8 The study by Nguyen et al. included a total of one hundred and nine PrEP and 86 PEP users. The median age was 36 and 34 among PrEP and PEP users, respectively. This study examined the association of PrEP with STIs in the 12 months following PrEP initiation relative to the 12 months prior to PrEP. 72% increase was observed overall in STIs, 12 months after PrEP initiation relative to the 12 months prior (IRR: 1.72, 95% CI: 1.22-2.41; aIRR: 1.39, 95% CI 0.98-1.96). 30% of PrEP users contracted one STI, 12% contracted two STIs and 9% contracted three or more STIs. By counting the STIs and STIs frequency per 100 person-years of follow up for C. trachomatis, N. gonorrhoeae, syphilis, HCV, 83.5 STI cases per 100 personyears were detected following PrEP prescription, as compared with 48.6 cases per 100 personyears in 12 months prior to PrEP. However, during the 12-month study period, the risk of STIs was higher among PrEP patients relative to PEP controls (IRR: 2.18, 95% CI 1.46-3.24; aIRR: 1.76, 95% CI 1.14-2.71), yielding higher results in the significant association between prescription of PrEP and counted STI cases. However, limitations are still present including incompleteness of follow-up behavioural risk data on condom use and changes in numbers of sexual partners during the study period. Participants may also not report diagnosed STIs outside of the study site.5 In the study by Azarnoosh et al., 46 individuals initiated with PrEP were included, and followed during the first 6 months after PrEP initiation in the Region of Southern Denmark. 69.4% of participants were 30-49 year old, and 19.8% were aged ≥50 years. The median age at PrEP initiation was 39 years (IQR, 35-48). In the post-PrEP period, we measured incident cases, and participants were routinely screened every 3 months. The results observed 20 participants (43.5%) were diagnosed with at least one STI (42% increase), 14 with a single case, and six with more. In the pre-PrEP period, prevalent cases were recorded, and participants were screened in case of symptoms or risk of infection as well as at the onset of PrEP, and screening frequency in the two periods were thus not the same. During the 6 months prior to PrEP initiation, fourteen


(30.4%) participants were diagnosed with at least one STI, 13 participants were diagnosed with one STI, and one participant with multiple STI. The results show a significant increase in the number of positive samples for STI after PrEP initiation (IRR 1.83; 95% CI: 1.03, 3.26). The study found a significant increase of 83% in the incidence of positive rectal samples for chlamydia, and a 56% increase in the incidence of gonorrhea positive samples. In the post-PrEP period, 20 participants (43.5%) were diagnosed with at least one STI (42% increase), 14 with a single case, and six with more. There is an increased incidence of positive samples for STI in the post-PrEP period relative to the pre-PrEP period (IRR 1.69; 95% CI: 0.91, 3.13). There are still a few limitations in this study. The sample size was small which minimized the detection of any difference in incidence between periods. Therefore, reliable conclusions are weak in the study.6 Of the 376 individuals evaluated, 183 patients of mean age 31.2 years (SD = 8.9) were included in the study by Montano et al. Prior to PrEP initiation, 35.0% of patients were diagnosed with any STI. However, this increased to 49.2% in the period of PrEP use. The study reported an increase in mean number of STI diagnoses per person during PrEP use relative to prior to PrEP use, from 0.5 to 1.1 (p <0.001). According to Montano et al., 33 (18%) of the 183 patients were diagnosed with at least one STI both prior to and during PrEP use, whereby the mean number of STI diagnoses per person prior to PrEP was lower than during PrEP use (1.5 vs. 2.6; p = 0.002) Moreover, this study calculated the adjusted relative risk for nonuse of condoms within the 12 months after PrEP initiation compared to prior to visitation, which was 1.46 (95% CI 1.13, 1.88); there was nearly a 50% increase in condomless anal sex, contradicting findings found in previous studies that discovered no evidence in changes of sexual behaviors among PrEP users. This study interpreted several limitations. First, the study included MSM that are at higher risk of HIV and other STIs compared to the general MSM population. Therefore, the results may not generalize the entire MSM population. Second, there is a decrease in participants reporting some sexual behaviours between 9 and 12 months, which may result in decreased sample size. Third, it is difficult to determine whether STIs incidence rates would still be high relative to a comparison group with the absence of PrEP use. Fourth, there may be selection bias in the comparison of GC and syphilis diagnosis as the criteria of PrEP initiation includes the diagnosis of rectal GC or syphilis in the prior 12 months.4 Every study fulfilled the Newcastle-Ottawa Scale (NOS), with all 5 studies proving to be of good quality.


In this study, we evaluated sexual risk behaviors and its effect on other STIs, particularly chlamydia, gonorrhea and syphilis amongst PrEP users, prior to and during usage of PrEP. Most participants enrolled in the studies were males who have sex with males (MSM) as they represent high risk individuals. The results may be explained by the phenomena of risk compensation, a theory suggesting that individuals adjust their behaviours in response to perceived levels of risk. Several older studies, such as in the study done by Marcus et al. and the PROUD study, have shown no evidence of changes in sexual behaviours amongst PrEP users prior to and during the use of PrEP.9,10 However, newer studies including the studies done by Beymer et al., Hevey et al., Nguyen et al., Azarnoosh et al., and Montano et al. show sexual risk compensation through the increase in number of STI diagnoses, not attributed to other factors such as race, sexual positions, alcohol consumption, education level, and age but rather to decreased condom use and increased sexual partners. Given that every study had their respective limitations, further research is, therefore, needed into the topic, especially in the clinical setting. Conclusion and Recommendation The use of PrEP contributes to a significant increase in the incidence of several STIs, including chlamydia, gonorrhea, and syphilis, showing the STIs in focus for this review despite lowering HIV incidence. Therefore, when implementing PrEP in the community, the role played by sexual risk compensation should not be ignored and should be taken into account.


References: 1.

HIV/AIDS [Internet]. [cited 2021 Nov 15]. Available from: https://www.who.int/newsroom/fact-sheets/detail/hiv-aids

2.

Pre-Exposure Prophylaxis (PrEP) | HIV Risk and Prevention | HIV/AIDS | CDC [Internet]. [cited 2021 Nov 15]. Available from: https://www.cdc.gov/hiv/risk/prep/index.html

3.

PrEP Modeling Study | Success Stories | NEEMA | NCHHSTP | CDC [Internet]. [cited 2021 Nov 15]. Available from: https://www.cdc.gov/nchhstp/neema/successstories/prepmodeling.html

4.

Montaño MA, Dombrowski JC, Dasgupta S, Golden MR, Duerr A, Manhart LE, et al. Changes in Sexual Behavior and STI Diagnoses Among MSM Initiating PrEP in a Clinic Setting. [cited 2021 Nov 15];1:3. Available from: https://doi.org/10.1007/s10461-0182252-9

5.

Nguyen VK, Greenwald ZR, Trottier H, Cadieux M, Goyette A, Beauchemin M, et al. Incidence of sexually transmitted infections before and after preexposure prophylaxis for HIV. AIDS [Internet]. 2018 Feb 20 [cited 2021 Nov 15];32(4):523. Available from: /pmc/articles/PMC5865505/

6.

Azarnoosh M, Johansen IS, Martin-Iguacel R. Incidence of Sexually Transmitted Infections After Initiating HIV Pre-Exposure Prophylaxis Among MSM in Southern Denmark. Am J Mens Health [Internet]. 2021 May 26 [cited 2021 Nov 15];15(3). Available from: https://journals.sagepub.com/doi/10.1177/15579883211018917

7.

Beymer M, DeVost M, Weiss robert, Dierst-Davies rhodri, Shover chelsea, landovitz raphael J, et al. Does HIV pre-exposure prophylaxis use lead to a higher incidence of sexually transmitted infections? A case-crossover study of men who have sex with men in Los Angeles, California. Sex Transm Infect. 2018;0:1–6.

8.

Hevey MA, Walsh JL, Petroll AE. DELIVERY OF PREVENTIVE CARE IN A CLINICBASED COHORT HEVEY ET AL. PREP CONTINUATION, HIV AND STI TESTING RATES, AND DELIVERY OF PREVENTIVE CARE IN A CLINIC-BASED COHORT. AIDS Educ Prev. 2018;30(5):393–405.

9.

Marcus JL, Glidden D V., Mayer KH, Liu AY, Buchbinder SP, Amico KR, et al. No


Evidence of Sexual Risk Compensation in the iPrEx Trial of Daily Oral HIV Preexposure Prophylaxis. PLoS One [Internet]. 2013 Dec 18 [cited 2021 Nov 15];8(12):e81997. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0081997 10.

Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial | Elsevier Enhanced Reader [Internet]. [cited 2021 Nov 15]. Available from: https://reader.elsevier.com/reader/sd/pii/S0140673615000562?token=495F90793845102B 23B022A9236A39D1D7CB22CADD1648E622BFA1573979905D4C7E4DA588B0ECA 60BC58731A51D19A9&originRegion=eu-west-1&originCreation=20211115123707


THE POTENTIAL OF NON-STRUCTURAL PROTEIN 1 AS AN EARLY DIAGNOSTIC TOOLS TO DETECT PLASMA LEAKAGE IN DENGUE SHOCK SYNDROME: A SYSTEMATIC REVIEW STUDY OF RANDOMIZED CONTROLLED TRIAL Fladys Jashinta Mashadi1* ,Stefanny Sartono1, Gladys Ariella2 1. 1st Year Medical Student, Fladys Jashinta Mashadi, Universitas Tarumanagara 2. 2rd Year Medical Student, Gladys Ariella, Universitas Tarumanagara *fjashinta@gmail.com Introduction : The case of COVID-19, which was initially recognized with symptoms of fever, cough with phlegm, weakness, and shortness of breath became difficult to distinguish from other viral infections, especially dengue. Dengue fever and COVID-19 have similar clinical and laboratory characteristics that are difficult to distinguish.1 Dengue is an acute mosquito-borne viral infection which is currently regarded as the most important arboviral disease internationally. The virus and its arthropod vector, Aedes aegypti, are endemic to over 100 countries around the world including the United States. It is responsible for an estimated 50 million to 100 million infections annually, with over 24,000 deaths resulting, predominantly in children under 14 years of age Objective : To aim more study and knowledge Method : PRISMA, Rov, Database Online Research Result : To detect NS1 Protein Antigenemia in Plasma Leakage, the total of 5 randomized-controlled trial studies with diverse drugs that compared to placebo, Ivermectin compared to Placebo which scores 71.5 with CI (59.9 - 84.0), p Value 0.014 in total 203 patients, 400 µg/kg doses (Suputtamongkol et al., 2021). Meanwhile Lovastatin scored 7.8 with CI (6.9–8.6), p Value 0.38 in total 300 patients, 80mg/ doses (Whitehorn et al., 2015), Low-Dose Balapiravir scored 8.91 with CI (7.50–10.63) in total 42 patients,1500 mg/doses (Nguyen et al., 2013), Low-Dose Prednisolone discord 8.77 with CI (8.23–9.47), p Value 0.09 in total 150 patients, 0.5 mg/kg doses (Tam et al., 2012) and Chloroquine 8.77 with CI (8.23–9.47), p Value 0,47 in total 307 patients, 600mg (4 x 150mg tablets) in day 1 and 2, and 300 mg in day 3 for doses (Tricou et al., 2010). Conclusion : Plasma Cell Free that detect NS1 Protein are able used for early diagnosis in Plasma Leakage that happen in Dengue Haemoragghic Syndrome Keywords : NS1 Protein, Plasma Leakage, Plasma Cell F


THE POTENTIAL OF NON-STRUCTURAL PROTEIN 1 AS AN EARLY DIAGNOSTIC TOOLS TO DETECT PLASMA LEAKAGE IN DENGUE SHOCK SYNDROME: A SYSTEMATIC REVIEW STUDY OF RANDOMIZED CONTROLLED TRIAL Fladys Jashinta Mashadi1* ,Stefanny Sartono1, Gladys Ariella2 1. 1st Year Medical Student, Fladys Jashinta Mashadi, Universitas Tarumanagara 2. 2rd Year Medical Student, Gladys Ariella, Universitas Tarumanagara *fjashinta@gmail.com

Introduction: The case of COVID-19, which was initially recognized with symptoms of fever, cough with phlegm, weakness, and shortness of breath became difficult to distinguish from other viral infections, especially dengue. Dengue fever and COVID-19 have similar clinical and laboratory characteristics that are difficult to distinguish.1 Dengue is an acute mosquito-borne viral infection which is currently regarded as the most important arboviral disease internationally. The virus and its arthropod vector, Aedes aegypti, are endemic to over 100 countries around the world including the United States. It is responsible for an estimated 50 million to 100 million infections annually, with over 24,000 deaths resulting, predominantly in children under 14 years of age. infection with dengue virus can result in a relatively benign, acute febrile illness (dengue fever) or in severe disease with abnormalities in vascular permeability (dengue hemorrhagic fever [DHF]) which can sometimes lead to sudden and often fatal hypovolemic shock (dengue shock syndrome [DSS]).2,3,4 The genome is translated as a single endoplasmic reticulum (ER)-bound polyprotein, which is co- and posttranslationally processed by both viral (NS2b and NS3) and cellular proteases into at least 10 separate proteins. These proteins are three structural proteins (C, prM, E) and seven nonstructural proteins (NS1, NS2a, NS2b, NS3, NS4a, NS4b, NS5), encoded by genes in the order (from 5′ to 3′).5,6,7 NS1 Ag is produced in membrane viruses with high concentration during the early clinical phase of the disease. MAC ELISA kits are available but they cannot be used for early diagnosis, because IgM is not detectable until 5-10 days after the onset (Dussart). Limfosit Blue Plasma (LPB): can be used in early diagnosis so we want to do the research. Another diagnostic tool like virus isolation, reverse transcription. PCR (RT -PCR) needed complicated and expensive technique so the NS1 Ag test we chose to be the basis for the research is the gold standard.8 NS1 was first described as a soluble complement-fixing (SCF) antigen in infected cell cultures.. The sera level of secreted DENV nonstructural protein 1 (NS1) is correlated with the development of DHF, it has been shown to trigger cytokine release and contributes directly to vascular leak through binding TLR4 and engaging the


endothelial glycocalyx.9,10,11,12 The NS1 antigen test (non-structural protein 1) is a test for the diagnosis of Dengue Virus Infection which detects quickly on the first day of fever, before the appearance of antibodies (about 5 days or more) which has high sensitivity and specificity. On a positive NS1 examination on days 1-3, it can be ascertained that the patient is infected with the dengue virus. NS1 in modern medical science as a therapeutic modality. This is very helpful in establishing the diagnosis of dengue virus infection within the first 4 days of fever.13 Our goal is to know more about an appropriate and rapid laboratory examination to support the diagnosis, so that the follow-up of DHF patients is fast. For this reason, accurate, fast, precise and efficient diagnosis is needed so that early detection of dengue virus infection with NS1 DENV . is needed to knowing the advantages of detecting NS1 antigen, namely to determine the presence of dengue infection in these patients in the early phase of fever, without waiting for the formation of antibodies. So that they can immediately carry out supportive therapy, monitor patients, reduce the risk of complications (dengue shock syndrome) which can result in death. Method: We conducted a scientific review of systematic reviews of randomized controlled trial studies conducted using PRISMA guidelines. The study design that became our inclusion was a Randomized Controlled Trial (RCT) using online databases such as Cochrane, Google Scholar, Hindawi, NJCM, Ovid, PubMed, and ScienceDirect. Risk of bias assessment; We used Rov to do Risk of Bias Assessment ;Overall bias, Selection of the reported results, Measurement of the outcome, Missing outcome data, Deviations from intended interventions, Randomization process. Search engine : (((((((((((((((((((Plasma Cell Free) OR (Cell Free DNA)) OR (cfDNA)) OR (Cell Free Nucleic Acids)) OR (Circulating Plasma cell-Free DNA)) OR (pcf-DNA)) OR (NS1)) OR (Nonstructural protein 1)) OR (Non structural protein 1)) OR (Non structural glycoprotein NS1)) OR (Extracellular fluid)) AND (Dengue Virus)) OR (DENV))) OR (Dengue Hemorrhagic Fever)) OR (DHF)) OR (Dengue Shock Syndrome)) OR (DSS)) OR (Dengue Fever)) OR (DF). Results & Discussion : NS1 Protein Antigenemia To detect NS1 Protein Antigenemia in Plasma Leakage, the total of 5 randomized-controlled trial studies with diverse drugs that compared to placebo, Ivermectin compared to Placebo which scores 71.5 with CI (59.9 - 84.0), p Value 0.014 in total 203 patients, 400 µg/kg doses (Suputtamongkol et al., 2021). Meanwhile Lovastatin scored 7.8 with CI (6.9–8.6), p Value 0.38 in total 300 patients, 80mg/ doses (Whitehorn et al., 2015), Low-Dose Balapiravir scored 8.91 with CI (7.50–10.63) in total 42 patients,1500 mg/doses (Nguyen et al., 2013), Low-Dose Prednisolone discord 8.77 with CI (8.23–9.47), p Value 0.09 in total 150 patients, 0.5 mg/kg doses (Tam et al., 2012) and Chloroquine


8.77 with CI (8.23–9.47), p Value 0,47 in total 307 patients, 600mg (4 x 150mg tablets) in day 1 and 2,

and 300 mg in day 3 for doses (Tricou et al., 2010).

Time to negative NS1 Protein From Suputtamongkol et al., 2021, with p Value 0.001 which is below 0.5 means significant, stated that Ivermectin compared to Placebo scored 72, CI 72.0 %. In the other hand, Whitehorn et al., 2015 with significant 0,6 p Value, Lovastatin scored 4, CI 3-5 %; Nguyen et al., 2013 indicating a non significant study with p Value 0.852 Low-Dose Balapiravir scored 3, CI 3-14 %; Tam et al., 2012 with significant p Value 0.08, Low-Dose Prednisolone scored 5, CI 3-11 % and the last study; Tricou et al., 2010 , Chloroquine scored 3.25, CI 2.75-4.19 % with significant p Value 0.11. Sensitivity AUC From 5 studies that we used, only 4 studies with 4 different drugs compared to placebo provide the data of sensitivity AUC (Suputtamongkol et al., 2021, Whitehorn et al., 2015, Nguyen et al., 2013, Tam et al., 2012). While the standard AUC score was 0.5 means able to diagnose patients with and without the disease or condition, 0.7-0.8 means acceptable, 0.8-0.9 indicates excellent, and above 0.9 indicates outstanding quality. The study with Ivermectin stated 2 data, the first AUC was 7.53 ± 4.04 (p Value 1 = 0.652) and the second6 AUC was 11.13 ± 5.7 (p Value 2 = 0.858). The second drug, Lovastatin, scored 16.1, CI 11.5-20.2 % (p Value = 0.56). The third drug, Low-Dose Balapiravir, scored 29.63, CI 27.41-39.86% (p Value = 0.623). The last drugs, Low-Dose Prednisolone, scored 21.56, CI 17.99-24.18 % (p Value = 0.76) Conclusion : NS1 Protein recommended to used References : 1. Yan G, Lee CK, Lam LTM, Yan B, Chua YX, Lim AYN, et al. Covert COVID-19 and false-positive dengue serology in Singapore Yan. The Lancet Infectious Diseases, 2020; 1473-3099(20)30158-4 2. Murray NEA, Quam MB, Wilder-Smith A. Epidemiology of Dengue: Past, present and future prospects. Clinical epidemiology. Dove Medical Press; 2013 [cited 2021Nov16]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3753061/ 3. Young PR, Hilditch PA, Bletchly C, Halloran W, Paul R. YoungSir Albert Sakzewski Virus Research Centre TRCH, Paige A. HilditchDepartment of Microbiology and Parasitology TUof Q, et al. An antigen capture enzyme-linked immunosorbent assay reveals high levels of the dengue virus protein NS1 in the sera of infected patients [Internet]. Journal of Clinical


Microbiology. 2000 [cited 2021Nov16]. Available from: https://journals.asm.org/doi/full/10.1128/JCM.38.3.1053-1057.2000 4. Ashour J, Laurent-Rolle M, Shi P-Y, [email protected] Adolfo García-Sastre, Joseph AshourDepartment of MicrobiologyView all articles by this author, Maudry Laurent-RolleDepartment of MicrobiologyView all articles by this author, et al. NS5 of dengue virus mediates STAT2 binding and degradation [Internet]. Journal of Virology. 2009 [cited 2021Nov16]. Available from: https://journals.asm.org/doi/full/10.1128/JVI.02188-08 5. San Martín JL, Brathwaite O, Zambrano B, Solórzano JO, Bouckenooghe A, Dayan GH, et al. The Epidemiology of Dengue in the Americas over the last three decades: A worrisome reality [Internet]. The American journal of tropical medicine and hygiene. The American Society of Tropical Medicine and Hygiene; 2010 [cited 2021Nov16]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2803522/ 6. Young PR, Hilditch PA, Bletchly C, Halloran W, Paul R. YoungSir Albert Sakzewski Virus Research Centre TRCH, Paige A. HilditchDepartment of Microbiology and Parasitology TUof Q, et al. An antigen capture enzyme-linked immunosorbent assay reveals high levels of the dengue virus protein NS1 in the sera of infected patients [Internet]. Journal of Clinical Microbiology. 2000 [cited 2021Nov16]. Available from: https://journals.asm.org/doi/full/10.1128/JCM.38.3.1053-1057.2000 7. Ashour J, Laurent-Rolle M, Shi P-Y, [email protected] Adolfo García-Sastre, Joseph AshourDepartment of MicrobiologyView all articles by this author, Maudry Laurent-RolleDepartment of MicrobiologyView all articles by this author, et al. NS5 of dengue virus mediates STAT2 binding and degradation [Internet]. Journal of Virology. 2009 [cited 2021Nov16]. Available from: https://journals.asm.org/doi/full/10.1128/JVI.02188-08 8. Avirutman P, et all,2006. Vascular leakage in severe dengue virus infection; A potential role for the for the non structural viral protein NS1 and complement. Pubmed, J infect Dis, 193(8): 1078-88 9. Young PR, Hilditch PA, Bletchly C, Halloran W, Paul R. YoungSir Albert Sakzewski Virus Research Centre TRCH, Paige A. HilditchDepartment of Microbiology and Parasitology TUof Q, et al. An antigen capture enzyme-linked immunosorbent assay reveals high levels of the dengue virus protein NS1 in the sera of infected patients [Internet]. Journal of Clinical Microbiology. 2000 [cited 2021Nov16]. Available from: https://journals.asm.org/doi/full/10.1128/JCM.38.3.1053-1057.2000 10. Avirutnan P, Zhang L, Punyadee N, Manuyakorn A, Puttikhunt C, Kasinrerk W, et al. Secreted NS1 of dengue virus attaches to the surface of cells via interactions with heparan sulfate and chondroitin sulfate E [Internet]. PLOS Pathogens. Public Library of Science; [cited 2021Nov16]. Available from: https://journals.plos.org/plospathogens/article?id=10.1371%2Fjournal.ppat.0030183


11. Jayathilaka D, Gomes L, Jeewandara C, Jayarathna GSB, Herath D, Perera PA, et al. Role of NS1 antibodies in the pathogenesis of acute secondary dengue infection [Internet]. Nature News. Nature Publishing Group; 2018 [cited 2021Nov16]. Available from: https://www.nature.com/articles/s41467-018-07667-z 12. Narayan R, Raja S, Kumar S, Sambasivam M, Jagadeesan R, Arunagiri K, Krishnasamy K, Palani G. "ELISA tidak langsung untuk diagnosis demam berdarah" . The Indian Journal of Medical Research . 144 (1): 128–133. doi : 10.4103 / 0971-5916.193300 . PMC 5116886 . PMID 27834337 . 2016.


Towards a Cholera-free 2030: Updates on the Profile of Oral Bivalent Cholera Vaccine in Endemic and Non-endemic Countries Muhammad Fathi Athallah Zaky¹, Nasim Amar², Muhammad Azri Ismail², Krisanto Tanjaya² ¹Universitas Brawijaya, Third Year Medical Student ²Universitas Brawijaya, Second Year Medical Student Abstract Introduction: Cholera is caused by the bacteria V. cholerae through contaminating food or water, resulting in dehydration and severe watery diarrhea. Cholera outbreaks kill up to 143,000 people every year. While recently occurring in African countries, non-endemic countries may also be at risk for outbreaks that often are unpredictable. The oral cholera vaccine (OCV) has been one of the main outbreak prevention methods besides improving sanitation. Objective: This systematic review focuses on the updates of efficacy, safety, and cost-effectiveness of oral bivalent cholera vaccine (OBCV) in which may aid WHO in updating the guidelines. Method: This study was done following PRISMA guidelines, while the literature search process was done in seven databases. Four outcomes of interest consist of two primary outcomes (seroconversion >4x increase post first and second vaccination dose) and two secondary outcomes (Adverse effect and cost-effectiveness). The included studies were analyzed using the ROBINS-I tool for its quality assessment. Results: OBCV are able to induce adaptive and innate immunity. Vibriocidal antibody is an adaptive immunity directed against LPS O antigen that showed a significant increase and is associated with a reduced risk of getting cholera. Increase of ≥4-fold antibody titer rises in both endemic and non-endemic populations, post first and second vaccination dose each, average 60%70% (Median = 68%-75%). Mild adverse effects are noted. Cost per DALY averted after vaccine program implementation from recent studies is US$ 391 and $1,000 (in Malawi and Bangladesh, with GDP of US$ 625.3 and US$ 1.968,8 per November 2021, respectively) Conclusion: OBCV is still relevant, safe, effective, cost-effective, and is feasible to be implemented across cholera endemic and non-endemic countries. The authors recommend further research on said profiles with a strong randomized control study design. Keywords: cholera, bivalent, oral cholera vaccine, immunogenicity


Towards a Cholera-free 2030: Updates on the Profile of Oral Bivalent Cholera Vaccine in Endemic and Non-endemic Countries

Author: Muhammad Fathi Athallah Zaky Nasim Amar Muhammad Azri Ismail Krisanto Tanjaya

Faculty of Medicine Brawijaya University Asian Medical Students’ Association Indonesia 2021


Towards a Cholera-free 2030: Updates on the Profile of Oral Bivalent Cholera Vaccine in Endemic and Non-endemic Countries Muhammad Fathi Athallah Zaky¹, Nasim Amar², Muhammad Azri Ismail², Krisanto Tanjaya² ¹Universitas Brawijaya, Third Year Medical Student ²Universitas Brawijaya, Second Year Medical Student Abstract Introduction: Cholera is caused by the bacteria V. cholerae through contaminating food or water, resulting in dehydration and severe watery diarrhea. Cholera outbreaks kill up to 143,000 people every year. While recently occurring in African countries, non-endemic countries may also be at risk for outbreaks that often are unpredictable. The oral cholera vaccine (OCV) has been one of the main outbreak prevention methods besides improving sanitation. Objective: This systematic review focuses on the updates of efficacy, safety, and cost-effectiveness of oral bivalent cholera vaccine (OBCV) in which may aid WHO in updating the guidelines. Method: This study was done following PRISMA guidelines, while the literature search process was done in seven databases. Four outcomes of interest consist of two primary outcomes (seroconversion >4x increase post first and second vaccination dose) and two secondary outcomes (Adverse effect and cost-effectiveness). The included studies were analyzed using the ROBINS-I tool for its quality assessment. Results: OBCV are able to induce adaptive and innate immunity. Vibriocidal antibody is an adaptive immunity directed against LPS O antigen that showed a significant increase and is associated with a reduced risk of getting cholera. Increase of ≥4-fold antibody titer rises in both endemic and non-endemic populations, post first and second vaccination dose each, average 60%70% (Median = 68%-75%). Mild adverse effects are noted. Cost per DALY averted after vaccine program implementation from recent studies is US$ 391 and $1,000 (in Malawi and Bangladesh, with GDP of US$ 625.3 and US$ 1.968,8 per November 2021, respectively) Conclusion: OBCV is still relevant, safe, effective, cost-effective, and is feasible to be implemented across cholera endemic and non-endemic countries. The authors recommend further research on said profiles with a strong randomized control study design. Keywords: cholera, bivalent, oral cholera vaccine, immunogenicity


Introduction

and was prequalified by WHO on September,

Cholera is a disease caused by the

29th 20114. The oral bivalent cholera vaccine

bacteria Vibrio cholerae serogroups of O1 or

(OBCV) brought up in this study is an OBCV

O139. During the last few years, Cholera is

made by Shantha Biotechnics (Hyderabad,

still a disease that spreads up to 1.3 million to

India) Sanofi Company with the trade name

4 million sufferers and kills about 21,000 to

Shanchol™.

143,000

people

annually1.

Until

now,

There are several available guidelines

Cholera is a disease that has managed to form

regarding the usage of OBCV. Firstly,

a pandemic seven times, starting in 1817,

according to a study conducted on 706

1829, 1852, 1863, 1881, 1889, and 19612.

Haitians, two doses of this OBCV can

Recent cholera outbreaks are still frequently

provide up to 76% protection for an average

occurring, such as the most recent one in

of all ages up to 4 years after vaccination.

Yemen which infected 167,278 people with

This type of OBCV is a vaccine in the form

48 deaths. Recent cholera outbreaks are still

of a suspension containing 1.5ml single-dose

frequently occurring, such as the most recent

vials. The dose of this vaccine is two doses

one in Yemen, which infected 167,278

with a gap of 2 weeks between doses. For

people with 48 deaths. There are also 1407

now, there are still no serious side effects that

suspected cases until mid-September 2021,

arise from the use of this vaccine5.

with 6.4% suspected death in Borno State, Nigeria3. Until now, there are only three types

Lastly, according to guidance from WHO on how to access OBCV from ICG 2013

describes

some

specifications

of vaccines that have been prequalified by

Shanchol™, it is stated that this vaccine is a

WHO, namely Dukoral®, Shanchol™, and

type of killed bivalent vaccine (O1 and O139

Euvichol®. In this systematic review, we

serogroups) whole-cell vaccine suspension.

focus on Shanchol™ OBCV because of

This vaccine does not require buffering and

several considerations such as many studies

begins to protect up to 67% for two years

have been conducted, many users, good

after 7—10 days of the second vaccine dose.

efficacy, and low price. Oral Cholera

Vaccinations can last up to 30 months in a

Vaccine is a vaccine made from killed

refrigerator at 2-8°C and are stable for up to

bivalent (O1 and O139) whole cells. This

14 days at room temperature or 37°C6. The

vaccine was first licensed in India in 2009

safety of this vaccine is also quite good and


safe to be given to pregnant or lactating

papers are extracted independently and

women, according to the Summary of the

verified by other authors before being

WHO Position on Cholera vaccines in 2017.

selected and summarized in Google Sheets,

The price of this vaccine is also quite low,

while duplicates were removed.

clocking in at 1.85$ per dose6. This systematic review focuses on the latest update of the OBCV profile since the position paper of WHO in 2017, which will continue to suggest giving OBCV to certain communities that play a major role in the emergence of new outbreaks that may aid WHO in renewing the guidelines.

Eligibility Criteria The inclusion criteria are clinical trial papers that include OBCV given as a double dose for its intervention. We exclude pregnant

women,

patients

with

immunocompromised conditions from our paper due to outcome consideration which may serve as a confounding factor to the

Materials & Methods

outcome of interest, as well as vaccines that

Search Strategy

were given as a single dose also due to

This

systematic

review

was

conducted with Preferred Reporting Items for Systematic

Reviews

and

Meta-analysis

(PRISMA) statement guidelines to identify the efficacy of double dose OBCV in both endemic

and

non-endemic

populations.

Population, Intervention, Comparison, and Outcome (PICO) questions were also used to formulate the inclusion criteria for this systematic review.

Study Outcomes The outcome of interest in this systematic review consists of primary and secondary outcomes. The primary outcomes are 1) seroconversion increase >4 fold, 14 days after the first inoculation, and 2) seroconversion increase >4 fold, 14 days after the second inoculation. There should be a minimum of 14 days interval between the

The literature search was done from October 28th to November 8th from six databases and one reference: PubMed, ScienceDirect,

outcome considerations.

CENTRAL,

ProQuest,

EBSCO, Francis and Taylor, and Google Scholar using the search strategy mentioned in Table 1 (see Appendix). The selected

first and second inoculation as per the protocol of the cholera vaccine double dose. Other than that, the secondary outcomes of this systematic review are 1) adverse effects of vaccination and 2) costeffectiveness of OBCV. The inclusion of


secondary

outcomes

is

to

study

the

Following the analysis of included

effectiveness of OBCV in endemic and non-

papers’ quality as shown in Table 3 (see

endemic countries to prevent cholera.

Appendix), three out of 7 included papers were labelled moderate risk of bias while the

Quality Assessment The collected data were screened and selected

following

the

PRISMA

flowchart Figure 1 (see Appendix) and underwent quality assessment using Risk of Bias in Non-randomised Studies - of Interventions (ROBINS-I) which covers seven risks of bias domains. The included papers are then labelled as low, moderate, serious, and critical risk of bias following the given algorithm of the ROBINS-I tool8. The usage of ROBINS-I is due to the heterogeneity of the included clinical trials paper, which consists of open-labelled and randomised controlled studies. Both are analyzed using ROBINS-I, including the randomised controlled trial because of the mechanism of ROBINS-I, which is based on the RoB tool of RCT by Cochrane, rendering the analysis of RCT plausible8,9. Details on ROBINS-I assessment are as listed in Table 2 (see Appendix). All authors did the process of data extraction and quality analysis while differing opinions were resolved through discussion and all authors’ consent. Result & Discussion Risk of Bias Assessment

rest were labelled low risk of bias. The confounding factors that were agreed upon prior to the analysis were done as required by the ROBINS-I tool include 1) pregnant women

or

those

who

have

immunocompromised conditions and 2) people that have received antibody boosters or had a history of cholera and its symptoms8. All of the papers have a low risk of bias due to confounding because all confounding factors serve as the exclusion criteria in all papers. All included papers were labelled as low risk for other domains due to their study design, which elicited bias in selecting participants, selecting reported outcomes, missing data, classification of intervention, and deviation of intended intervention, except on the bias in measurement outcome. It was found in all open-labelled studies that the participants and outcome assessors were aware of the given interventions, which led to the classification as “moderate risk of bias” in three papers. Mechanism of Action of OBCV Knowledge

about

cholera

pathogenesis and mechanisms of immune


induction by OCV has provided new insights

LPS antibody) in the intestinal mucosa could

into

is

effectively protect against cholera infection

characterized by severe watery diarrhea due

and disease. In addition, the oral cholera

to infection by the Vibrio cholerae bacteria

vaccine also involves other complex specific

its

effectiveness.

contaminating

food

or

Cholera

water10.

After

immunity, including vibriocidal antibody,

ingestion, V. cholera bacteria colonize the

serum IgA, IgG, and of special importance

surface of intestinal epithelial cells and

for long-term protection, memory B cells,

secrete cholera toxin, which has five subunits

and T cells12. Vibriocidal antibodies are of

of B protein that binds to the host cell

interest in various studies because of their

receptor and one subunit of A protein as an

strong correlation with adaptive immunity

active toxin. Both of these cholera toxins will

against V. cholera bacteria. In this systematic

bind to the GM1 ganglioside receptor and

review, vibriocidal antibodies, mainly IgM

enter the cell by endocytosis. The toxin from

directed against the LPS O antigen, showed a

A subunit binds to the G protein adenylate

significant increase with age, especially in

cyclase in the cytoplasm. It triggers excessive

endemic cholera areas and are associated

cyclic AMP (cAMP) that leads to the

with a reduced risk of getting cholera

secretion of chloride, bicarbonate, water from

disease.13.

intestinal cells and blocks sodium chloride

Interestingly, OBCV also stimulates

and water uptake from villous cells, resulting

innate immunity, e.g., nitric oxide, TNF- α,

in watery diarrhea, dehydration, and acidosis

NF-κB and IL-1, which are critical for

that is typical of severe cholera11.

promoting mucosal IgA immune responses.

Various studies have described the

Synergistically,

adaptive

and

innate

novel design of OBCV as being able to

immunity can protect against disease by

induce innate and adaptive immunity.

inhibiting bacterial colonization and toxin

Immune protection after oral immunization is

binding, a major cholera problem12.

mediated mainly by secretory IgA antibodies, which in experimental studies were able to

Efficacy of OBCV OBCV is deemed as efficient when

prevent cell surface of LPS O antigen (Inaba & Ogawa) and the cholera toxin from binding to intestinal cells. The appearance of these specific antibodies (sIgA antitoxin and anti-

the vaccine elicits a higher antibody titer, resulting in a more immunized patient, along with

being

able

to

maintain

its

immunogenicity in a certain amount of time.


All of the studies included came to a

regime of OBCV, where both adults and

consensus in which the vaccine elicits a

children undergo a significant increase in

significant amount of vibriocidal antibody

titers from baseline16. Coming to comparison

titers

its

with placebo, a study in Ethiopia found that

immunogenicity on a certain percentage up to

the seroconversion rates both on O1 Ogawa

five years on all age groups14, on all age

and O1 Inaba were significantly higher in

groups14, amongst endemic and non-endemic

vaccine

patients. Variables accounted for regarding

percentages were 75%, 90%, and 70%

the efficacy across all patients are the

compared to placebo of 0%, 6%, and 13% (in

baseline vibriocidal geometric mean titers

the same age group of 1—5, 6—17, and ≥ 18

(GMT), the geometric mean fold (GMF) rise

years old, respectively). For O1 Inaba, the

in

the

percentages following the first and second

seroconversion rates of ≥4-fold rise in titers

doses were 74% and 77% in children and

from baseline to 14 days after each

70% and 81% in adults17. To round the

administration.

statements up, a study by Franke et al. stated

and

titers

are

from

able

to

maintain

baseline,

and

groups.

For

O1

Ogawa,

the

Our studies on endemic countries

that after four years follow up from the last

were conducted regarding the efficacy. A

dose, the vaccine's effectiveness lasts for

study in Bangladesh found that there was a

76% with a 95% CI of 59-86, p<0,000118.

significant increase of vibriocidal titer at day

Another two studies from non-

14 in all age groups, both for Ogawa

endemic countries. From the Philippines, a

(younger children 51%, older children - 70%,

study conducted by Capeding et al. stated that

adults - 64%) and Inaba (younger children

high seroconversion rates ranging from 69%-

75%, older children 89%, adults - 64%).

92% were achieved following both doses in

Although comparatively lower, there was

all age groups (14, 5—14, and ≥15 years old)

another increase at day 28 for O1 Ogawa

against O1 Ogawa and O1 Inaba serotypes

(younger children - 45%, older children 47%,

(86-92%,

adults - 54%) and O1 Inaba (adults - 45%,

respectively19. Additionally, another study

younger children - 54%, older children

from the Dominican Republic found that the

65%)15.

prior,

GMTs were increased from baseline to day

Kanungo et al. also found that the 28-day

28, against all serotypes and in all age groups.

dose was non-inferior to the 14-day dose

The percentages for O1 Ogawa ranged from

Echoing

the

statement

86-88%,

and

69-83%),


87.0% to 90.9%, and for O1 Inaba of 87.9%

by differences in GMT between individuals

to 90.9% (in age groups 1—4 and 5—14

in cholera endemic and non-endemic areas21.

years old, respectively)20. Details on the list

High GMT in endemic areas suggests recent

of variables discussed in each study

exposure by V. cholera leads to higher

concerning the efficacy are summarized

natural priming immunity than individuals in

in Table 3 (see Appendix). Other than the

less exposed areas. Due to the high GMT

consensus aforementioned, also of note

baseline

would be that the results from both endemic

seroconversion appears to be lower than in

and non-endemic countries align to one

non-endemic areas. These results indicate

another, opening the window of possibilities

that the two doses of OBCV are an effective

for the vaccine to be implemented in the non-

dose in inducing immunogenicity in cholera

endemic countries, which will be discussed

non-endemic areas. Two doses regimen of

further in the paper.

OBCV had high seroconversion rates both in cholera

Differences in Antibody Titer Level Based on the table, it is known that populations lacking repeated exposure to cholera have a stronger vibriocidal response than endemic areas after receiving a two-dose regimen of OBCV. A study by Desai in nonendemic areas of Ethiopia demonstrated a 70% seroconversion rate after the first and 81% after the second dose of vaccination17. Similar to this, Baik et al. also found high immunogenicity based on seroconversion, reaching 83% and 76.3% after the first and second

vaccinations,

respectively11.

In

contrast, a study by Kanungo in the endemic area

of

Kolkata

in

India

showed

seroconversion rates after vaccination were 69%

and

55%16.

These

different

immunogenicity results could be explained

in

cholera

endemic

endemic

and

areas,

non-endemic

areas11,16,19. An important difference that can be seen in the majority of studies is how the vaccine has a higher seroconversion rate after the first vaccination than the second. Studies by Baik et al. on adults in cholera nonendemic areas and studies by Capeding (2017)

in

endemic

areas

showed

seroconversion after the first vaccination was 83.80% and 83%, however, after the second vaccination, seroconversion was 76.30% and 78.4%, respectively11,19. This finding might be attributed to a blocking function of the activated immune system in the gut on antigen uptake after the first dose. This is the reason for the decreased serum vibriocidal titers in response to the second dose which


vibriocidal antibodies are generally in the

factor

form of IgM isotype. In contrast, the

enteropathy, and micronutrient deficiencies

intestinal

was

can serve as contributing factors to explain

substantially increased after the second

lower observed immune response in this age

vaccination indicating the protective efficacy

group.

of the OBCV13.

cholera non-endemic areas with lower

IgA

antibody

response

All studies listed in the table show

such

as

helminth

coinfection,

Especially young children from

recurrent exposure to cholera have a lower

that O1 Inaba and O1 Ogawa strain antigens

probability

had significantly higher seroconversion rates

immunity11,17,20. The role of various health

than O139 strain. The robust response against

workers, especially public health, is needed

O1 strain is of particular interest as it

to campaign for immunization with OBCV in

comprises

major

both cholera endemic and non-endemic

outbreaks17. Meanwhile, there has not been

areas. In addition, it also needs to be

any report of causing cholera due to O139

accompanied by improving water quality,

since the 1990s. Lower response to O139

sanitation and hygiene (WASH) as a part of a

may suggest that the vaccine could elicit an

comprehensive strategy to prevent and

inadequate immune response or whether it

control cholera outbreaks throughout the

reflects the difference in test sensitivity

world21.

the

main

cause

of

of

establishing

natural

remains an aspect that needs further exploration16. Another study by Baik stated that the lower immune response to O139 may be due to the content of O139 antigen in bivalent killed OBCV being much lower than

and

toddlers

are

an

interesting part of the discussion regarding the effectiveness of OBCV because children aged 2—9 years have a high risk of infection and

a

high

burden

of

There were little to no immediate or serious adverse events (AEs) found in the studies concerning the safety of OBCV along with generally mild existing AEs. In a study

Inaba and Ogawa O1 strain antigen22. Children

Safety of OBCV

disease22.

Seroconversion rates are high in children and toddlers, even though an important host

conducted by Desai et al., only one adverse event was reported within 14 days of the administration, which resolved following medication and continued being enrolled in the study21. Another common theme in AEs across several studies with similar age groups include fever, headache, coughing, and GI disturbances (vomiting, diarrhea, abdominal


pain)16,19,20. One study on the vaccine's safety

effectiveness

in pregnant women also stated that the

mathematically24.

vaccine administration does not correlate with

adverse

pregnancy

of

vaccination

programs

In Malawi, both direct and indirect

outcomes

protection of the vaccine results in being

(miscarriages, stillbirths)10. Details on the list

cost-effective. The net cost per DALY

of AEs are as summarized in Table 4 (see

averted would be US$738 and US$391

Appendix).

(assuming vaccine efficacy of 58% and 93% through direct and indirect protection, both

Cost-Effectiveness of OBCV

respectively)25. Meanwhile, in Bangladesh,

Through the bigger picture, a study may account for the cost-effectiveness of implementing OBCV program in a country by utilizing the cost-effectiveness thresholds of a health intervention provided by the World Health Organization (WHO) and Vaccine

Introduction

(VICE)

calculator

Cost-Effectiveness (available

online

on www.stopcholera.org), in which has been seen in the studies discussed hereinafter. WHO-CHOICE

classifies

the

cost-

effectiveness of health intervention into three categories,

which

are

(1) very

cost-

effective (below GDP per capita), (2) costeffective (up to three times the GDP per capita, and (3) not cost-effective (above three times the GDP per capita) of a country23. On the other hand, the VICE calculator is a Microsoft Excel-based program that allows its user to have full control describing the epidemiology of a population, vaccine characteristics, enabling

them

and to

economic estimate

the

values, cost-

the study was done considering five subpopulations rather than solely depending on the whole country's population of its own; namely (1) non-selective mass vaccination; (2)

children

in

Bangladesh,

epidemiologically having a higher incidence of cholera compared to adults; (3) cholera "hotspots", which considers geographical locations; (4) populations with relatively low access to care, resulting in poor sanitation, hygiene,

and

medical

care;

and

(5)

accounting for indirect protection, as a result of mass vaccination. All in all, the indirect protection has been mathematically proven in this study to be the most cost-effective approach, clocking in at almost US$1.500 (assuming the vaccination efficacy of near 100%)24. Details of the cost-effectiveness would be as summarized in Table 5 (see Appendix). The studies discussing the costeffectiveness of implementing the OBCV


program are all done in a relatively low GDP

international workers of cholera-affected

setting. Specifically, Bangladesh and Malawi

countries not be vaccinated. Whereas,

are ranked 165th and 201st internationally per

historically speaking, cholera has affected

November 2021, respectively26,27. Also, both

many people across the world. Beginning in

studies implement the same brand of OBCV,

most African countries, the seven pandemics

Shanchol,

WHO.

of cholera —though most resolved after

Meaning, by implementing the same methods

improving sanitation in certain countries—

used in these two studies, other countries in

were mostly, if not all, spread through

need can determine the cost-effectiveness of

travelling.

prequalified

by

the

implementing the OBCV program on their

In addition, after 100 years of being

own, along with —though it may not be

cholera-free

directly comparable— experiencing similar

pandemic, the American countries were hit

results.

with a consistent barrage of outbreaks, such

since

the

sixth

cholera

as Ecuador, Chile, Brazil, and many Future Implications of OBCV Several points are to be addressed regarding the updates that have been discussed in this paper compared to the guideline of cholera outbreaks from WHO. Firstly, OBCV is still proven to be efficient, safe, and cost-effective through recent studies. It is important to note that even though the endpoint of antibody titer varies and that there still has not been any specific vibriocidal antibody titer threshold for seroprotection, this paper has shown that the vaccine is also effective in populations from non-endemic countries with cumulative protective efficacy against confirmed cases of above 60% up until after five years of follow up14. Secondly, WHO recommends that both short or long-term travelers and

others28,29. One epidemic outbreak of note would be during 1991-1997 in Peru, South America, where more than 1 million cases were identified, causing almost 9.000 deaths. Using a mathematical model, one recent study suggested that the cause of this specific multi-wave epidemic, other than poor water sanitation

and

the

possibility

of

the

inadequacy of the public health infrastructure at the time30, would be that V. cholerae were autochthonous

to

planktons

normally

existing in the water there31. This shows that cholera is capable of affecting all sorts of countries despite its sanitation level and its record of whether the countries were endemic to cholera.


In the end, vaccination is a prevention

heterogeneous and also studies regarding the

secondary to improving WASH, as proven

OBCV and its comparison with other types of

both by the cessation of all seven cholera

cholera vaccines are still limited.

pandemics and previous studies. It is

Hence,

the

authors

recommend

important for health policy makers to

further research on both the profile and the

understand specific needs and conditions of

comparison between similar types of OBCV

each

in

country,

because

focusing

on

cholera

endemic

and

non-endemic

eliminating cholera outbreaks in endemic

countries with strong randomized controlled

countries is one thing. However, doing so

trials and homogenous study designs.

while also holistically tackling countries with high risk and/or has a history of cholera outbreaks even though said countries are

References 1.

known to be non-endemic to achieve a cholera-free world in 2030.

2.

Conclusion & Recommendation This paper has proven that OBCV is still

relevant,

safe,

cost-effective,

and

effective for use across people both in endemic

and

Potentially,

non-endemic OBCV

may

countries. also

3.

be

recommended to be implemented in nonendemic countries and for international workers and travelers to be vaccinated prior

4.

to departure. Other than that, this paper has the advantage of being the first systematic review to discuss the updated safety, efficacy and cost-effectiveness profile of OBCV in cholera endemic and non-endemic areas. The authors acknowledge the limitations faced, where the design in several studies is still

5.

Cholera [Internet]. [cited 2021 Nov 16]. Available from: https://www.who.int/news-room/factsheets/detail/cholera Clemens JD, Nair GB, Ahmed T, Qadri F, Holmgren J. Cholera. Lancet (London, England) [Internet]. 2017 Sep 23 [cited 2021 Nov 16];390(10101):1539–49. Available from: https://pubmed.ncbi.nlm.nih.gov/2830 2312/ [Internet]. Reliefweb.int. 2021 [cited 16 November 2021]. Available from: https://reliefweb.int/sites/reliefweb.int /files/resources/borno_state_cholera_ outbreak_response_sitrep_no_4_20_0 9_21.pdf PRESS RELEASE. [cited 2021 Nov 16]; Available from: http://www.gavi.org/support/nvs/chol era-vaccine/ Matias WR, Falkard B, Charles RC, Mayo-Smith LM, Teng JE, Xu P, et al. Antibody Secreting Cell Responses following Vaccination with Bivalent Oral Cholera Vaccine among Haitian Adults. PLoS Negl Trop Dis [Internet]. 2016 Jun 16 [cited 2021 Nov 16];10(6). Available from:


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https://pubmed.ncbi.nlm.nih.gov/2730 8825/ Guidance on how to access the Oral Cholera Vaccine (OCV) from the ICG emergency stockpile. Summary of the WHO Position Paper on Cholera vaccines: WHO position paper. 2017; Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in nonrandomised studies of interventions. BMJ [Internet]. 2016 Oct 12 [cited 2021 Nov 16];355. Available from: https://www.bmj.com/content/355/bm j.i4919 Sterne JAC, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ [Internet]. 2019 [cited 2021 Nov 16];366. Available from: https://pubmed.ncbi.nlm.nih.gov/3146 2531/ Khan AI, Ali M, Lynch J, Kabir A, Excler JL, Khan MA, et al. Safety of a bivalent, killed, whole-cell oral cholera vaccine in pregnant women in Bangladesh: Evidence from a randomized placebo-controlled trial. BMC Infect Dis. 2019;19(1). Baik YO, Choi SK, Olveda RM, Espos RA, Ligsay AD, Montellano MB, et al. A randomized, noninferiority trial comparing two bivalent killed, whole cell, oral cholera vaccines (Euvichol vs Shanchol) in the Philippines. Vaccine [Internet]. 2015 Nov 17 [cited 2021 Nov 16];33(46):6360–5. Available from: https://pubmed.ncbi.nlm.nih.gov/2634 8402/ Holmgren J. An Update on Cholera Immunity and Current and Future

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14.

15.

16.

17.

Cholera Vaccines. Trop Med Infect Dis [Internet]. 2021 [cited 2021 Nov 16];6(2). Available from: https://pubmed.ncbi.nlm.nih.gov/3392 5118/ Chowdhury F, Ali Syed K, Akter A, Rahman Bhuiyan T, Tauheed I, Khaton F, et al. A phase I/II study to evaluate safety, tolerability and immunogenicity of Hillchol®, an inactivated single Hikojima strain based oral cholera vaccine, in a sequentially age descending population in Bangladesh. Vaccine. 2021;39(32). Fong Y, Halloran ME, Park JK, Marks F, Clemens JD, Chao DL. Efficacy of a bivalent killed wholecell cholera vaccine over five years: A re-analysis of a cluster-randomized trial. BMC Infect Dis. 2018;18(1). Chowdhury F, Bhuiyan TR, Akter A, Bhuiyan MS, Khan AI, Hossain M, et al. Immunogenicity of a killed bivalent whole cell oral cholera vaccine in forcibly displaced Myanmar nationals in cox’s bazar, Bangladesh. PLoS Negl Trop Dis. 2020;14(3). Kanungo S, Desai SN, Nandy RK, Bhattacharya MK, Kim DR, Sinha A, et al. Flexibility of Oral Cholera Vaccine Dosing—A Randomized Controlled Trial Measuring Immune Responses Following Alternative Vaccination Schedules in a Cholera Hyper-Endemic Zone. PLoS Negl Trop Dis. 2015;9(3). Desai SN, Akalu Z, Teshome S, Teferi M, Yamuah L, Kim DR, et al. A randomized, placebo-controlled trial evaluating safety and immunogenicity of the killed, bivalent, whole-cell oral cholera vaccine in Ethiopia. Am J Trop Med Hyg. 2015;93(3).


18.

19.

20.

21.

22.

23.

24.

Franke MF, Ternier R, Jerome JG, Matias WR, Harris JB, Ivers LC. Long-term effectiveness of one and two doses of a killed, bivalent, wholecell oral cholera vaccine in Haiti: an extended case-control study. Lancet Glob Heal. 2018;6(9). Capeding MRZ, Gonzales MLAM, Dhingra MS, D’Cor NA, Midde VJ, Patnaik BN, et al. Safety and immunogenicity of the killed bivalent (O1 and O139) whole-cell cholera vaccine in the Philippines. Hum Vaccines Immunother. 2017;13(10). Cordero De Los Santos L, FerisIglesias J, Aloysia D’Cor N, Midde VJ, Patnaik BN, Thollot Y, et al. Bivalent oral cholera vaccine in participants aged 1 year and older in the Dominican Republic: A phase III, single-arm, safety and immunogenicity trial. Hum Vaccines Immunother. 2018;14(6). Desai SN, Akalu Z, Teferi M, Manna B, Teshome S, Park JY, et al. Comparison of immune responses to a killed bivalent whole cell oral cholera vaccine between endemic and less endemic settings. Trop Med Int Heal. 2016;21(2). Baik YO, Choi SK, Kim JW, Yang JS, Kim IY, Kim CW, et al. Safety and Immunogenicity Assessment of an Oral Cholera Vaccine through Phase I Clinical Trial in Korea. J Korean Med Sci [Internet]. 2014 Apr 1 [cited 2021 Nov 16];29(4):494–501. Available from: https://synapse.koreamed.org/articles/ 1101602 Marseille E, Larson B, Kazi DS, Kahn JG, Rosen S. Thresholds for the cost–effectiveness of interventions: Alternative approaches. Bull World Health Organ. 2015;93(2). Troeger C, Sack DA, Chao DL.

25.

26.

27.

28.

29.

30.

31.

Evaluation of targeted mass cholera vaccination strategies in Bangladesh: a demonstration of a new costeffectiveness calculator. Am J Trop Med Hyg [Internet]. 2014 Dec 1 [cited 2021 Nov 16];91(6):1181–9. Available from: https://pubmed.ncbi.nlm.nih.gov/2529 4614/ Ilboudo PG, Mengel MA, Gessner BD, Ngwira B, Cavailler P, Le Gargasson JB. Cost-effectiveness of a reactive oral cholera immunization campaign using ShancholTM in Malawi. Cost Eff Resour Alloc. 2021;19(1). GDP per capita (current US$) | Data [Internet]. [cited 2021 Nov 16]. Available from: https://data.worldbank.org/indicator/ NY.GDP.PCAP.CD Woods B, Revill P, Sculpher M, Claxton K. Country-Level CostEffectiveness Thresholds: Initial Estimates and the Need for Further Research. Value Heal. 2016;19(8). Glass RI, Libel M, Brandling-Bennett AD. Epidemic cholera in the Americas. Vol. 256, Science. 1992. Ries AA, Vugia DJ, Beingolea L, Palacios AM, Vasquez E, Wells JG, et al. Cholera in Piura, Peru: A modern urban epidemic. J Infect Dis. 1992;166(6). Tickner J, Gouveia-Vigeant T. The 1991 Cholera Epidemic in Peru: Not a Case of Precaution Gone Awry. Risk Anal [Internet]. 2005 Jun 1 [cited 2021 Nov 16];25(3):495–502. Available from: https://onlinelibrary.wiley.com/doi/ful l/10.1111/j.1539-6924.2005.00617.x Smirnova A, Sterrett N, Mujica OJ, Munayco C, Suárez L, Viboud C, et al. Spatial dynamics and the basic reproduction number of the 1991–


1997 cholera epidemic in Peru. PLoS Negl Trop Dis. 2020;14(7).


Appendix Table 1. Search Strategy

Database

Keyword

Result

PubMed

"bivalent" AND "cholera" AND "vaccine" (filters: from

35

2015-2021)

("Vibrio cholerae"[Mesh] OR "Cholera"[Mesh]) AND

8

("Cholera Vaccines"[Mesh] OR "shanchol" [Supplementary Concept] OR "ORCVAX") AND ("Endemic Diseases"[Mesh] OR "Disease Outbreaks"[Mesh] OR "Nonendemic" OR "Non endemic") AND "Antibody"

CENTRAL

“Bivalent” AND (“Oral Cholera Vaccine” OR “OCV”) AND

37

“Cholera”

"Vibrio cholerae" OR "Cholera") AND ("Cholera Vaccines" OR "shanchol" OR "ORCVAX") AND ("Endemic Diseases" OR "Disease Outbreaks" OR "Nonendemic" OR "Non-endemic") AND "Antibody"

9


Table 1. Search Strategy (cont.)

Database

Keyword

Result

Google

("Vibrio cholerae" OR "Cholera") AND ("Cholera Vaccines"

1240

Scholar

OR "shanchol" OR "ORCVAX") AND ("Endemic Diseases" OR "Disease Outbreaks" OR "Non-endemic" OR "Non endemic")

Science

("Vibrio cholerae" OR "Cholera") AND ("Cholera Vaccines"

Direct

OR "shanchol" OR "ORCVAX") AND ("Endemic Diseases" OR

259

"Disease Outbreaks" OR "Non-endemic" OR "Non endemic")

EBSCO

("Vibrio cholerae" OR "Cholera") AND ("Cholera Vaccines"

127

OR "shanchol" OR "ORCVAX")

Taylor &

[[All: "vibrio cholerae"] OR [All: "cholera"]] AND [[All:

Francis

"cholera vaccines"] OR [All: "shanchol"] OR [All: "orcvax"]]

24

AND [[All: "endemic diseases"] OR [All: "disease outbreaks"] OR [All: "non-endemic"] OR [All: "non endemic"]]

ProQuest

("Vibrio cholera" OR "Cholera") AND ("Cholera Vaccines" OR "shanchol" OR "ORCVAX") AND ("Endemic Diseases" OR "Disease Outbreaks" OR "Non-endemic" OR "Non endemic")

211


Table 2. ROBINS-I Risk of Bias Assessment Table 2. ROBINS-I Risk of Bias Assessment (Cont.)


Table 2. ROBINS-I Risk of Bias Assessment (Cont.)


Table 2. ROBINS-I Risk of Bias Assessment (Cont.)


Table 3. Summary of Efficacy


Table 3. Summary of Efficacy (Cont.)


Table 4. Summary of Adverse Effects


Table 5. Comparison of the Cost Effectiveness of OBCV Program from Recent Studies


Figure 1. PRISMA Flowchart

* Done independently by all authors, then combined. Result from authors with same search strategy keyword & database are excluded due to duplication. **By adding the keyword “clinical trial” on the search strategy.


The Potential Novel of Human Umbilical Cord Stem Cell As An Alternative Therapeutic in SARS-CoV-2: A Systematic Review of Randomized Controlled Trials Puspa Gracella T.1*, Monika Wulan Siswadi1, Michelle Erenestine K.1, Nathalia Angelina1 1

Faculty Medicine, Tarumanagara University, Indonesia *

gracella.micho@gmail.com

ABSTRACT Introduction: Coronavirus disease 2019 (COVID-19), a highly contagious viral illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There are some immunotherapeutic approaches that have been used for COVID-19 treatment. Numerous studies have shown that human umbilical cord mesenchymal stem cells (hUC-MSCs) have significant immune modulation and tissue repair functions due to their low immunogenicity. Method: A systematic review of randomised controlled trial was conducted with PRISMA and Cochrane tool for assessing risk of bias in randomised trials (RoB 2.0). Result: There 4 clinical trials that show the most significant difference between the use of hUC-MSCs as a treatment for COVID-19 compared to the control group. Critically ill patients are given IV hUC-MSCs.

Lymphocytes are involved in this study, such as CD90 of 97.9% ± 2.6% CD105 of 98.1% ± 1.4% CD34/CD45 of 2.2% ± 4.9%. Comorbidites: diabetes 17 (26,15%) and Hypertension (18,46%) complications used significantly less exogenous after hUC-MSC infusion than usual. No significant of adverse event. Conclusion: hUC-MSC as a non-invasive treatment has the potential to provide a safe, effective therapeutic for critically ill COVID-19 patients, which could help mitigate the devastating economic and public health consequences caused by the rapid worldwide spread of SARS-CoV-2.


receptor antibody therapy.9-12 In any case,

Introduction

the side impacts and variable treatment Coronavirus disease 2019 (COVID-

adequacy have required advance considers

19), a highly contagious viral illness caused

recognizing the security and viability of

by severe acute respiratory syndrome

elective immune-modulation regimens.13

coronavirus 2 (SARS-CoV-2), COVID-19

Mesenchymal stem cells, or too

has had a disastrous effect on the world’s

known as mesenchymal stromal cells

demographics resulting in more than 3.8

(MSCs), have been appeared to modulate

million deaths worldwide.1 Coronaviruses

overactive resistant and hyperinflammatory

are positive-sense RNA viruses having an

forms, advance tissue repair, and discharge

extensive and promiscuous range of natural

antimicrobial molecules.14 MSC treatment

2,3

has been used in patients infected with, it

Coronaviruses can cause clinical diseases

significantly inhibits the immune cell-

in humans that may extend from the

mediated

common cold to more severe respiratory

reducing further lung damage.15,16

hosts and affect multiple systems.

diseases like SARS and MERS.4,5

inflammatory

response

and

Embryo mesenchymal stem cell is

This virus has been proposed to be

a pluripotent progenitor cell which divides

designated/named severe acute respiratory

many times and whose progeny eventually

syndrome coronavirus 2 (SARS-CoV-2),

gives rise t o skeletal tissues: cartilage,

which determined the virus belongs to

bone, tendon, ligament, marrow stroma,

the Severe acute respiratory syndrome-

connective tissue.17 MSC are fusiform,

related coronavirus category and found

fibroblast-like cells. During their initial

this virus is related to SARS-CoVs.6 SARS-

growth in vitro, they form colonies (termed

CoV-2

in analogy with HSC: colony forming unit-

is

a

order Nidovirales,

member

of

the

family Coronaviridae,

fibroblasts [CFU-f]).17 for

The cells are

subfamily Orthocoronavirinae, which is

negative

hematopoietic

surface

subdivided into four genera, which is

markers: CD34, CD45, CD14 and positive

Alphacoronavirus, Betacoronavirus, Gam

for a variety of markers: Stro-1, CD29, CD

macoronavirus,and Deltacoronavirus.7,8

73, CD90, CD105, CD166 and CD44.17

There are some immunotherapeutic

Numerous studies have shown that

approaches that have been used for

human umbilical cord mesenchymal stem

COVID-19

cells

glucocorticoid

treatment, therapy,

including convalescent

plasma therapy, and anti-interleukin (IL-6)

(hUC-MSCs)

have

significant

immune modulation and tissue repair functions

due

to

their

low


immunogenicity.18-20 HUC-MSCs is an

strategy for attenuating the cytokine storm

ideal candidate for allogenic adoptive

and

transfer therapy, have been appeared to play

outcome.26

ultimately

improving

patients'

a defensive part in A/H5N1 associated

After intravenous infusion, MSCs

intense lung injury.21 MSc’s role in

get trapped in the inflamed lung and exert

orchestrating

tissue

immunomodulatory function via direct

maintenance, and repair, mainly producing

inter-action with respiratory epithelial cells

several growth factors is unquestionable.22

and immune cells, or release of a wide

Due

development,

to

the

consideration

of

variety of soluble mediators, ultimately

umbilical cord as a medical waste, the

reducing the inflammation and protecting

collection of MSC from UC needs no

the alveolar epithelial cells. 26

ethical approval.23 Global re-searchers are

MSC exposure results in a decline

interested in the umbilical cord blood for its

of pro-inflammatory cytokines including

stem cell property.31 The four forms of stem

IL-1α, IL-1β, IL-6, IFN-γ, and TNF-α and

cells identified in UC are: 1) Whole UC-

an increase in anti-inflammatory cytokines

MSCs 2) UCWJ (Wharton jelly), UCA

such as IL-4, IL-5, and IL-10.26 The

(artery) and UCV (vein) MSCs (obtained as

restored, noninflamed microenvironment

a result of mincing after removing

aids in the repair of pulmonary epithelial

umbilical vessels), 3) UC lining and sub

cell damage and promotes alveolar fluid

amnion-derived MSCs, 4) UC perivascular

clearance, thus restoring lung function with

stem cells (UCPVC) UC-MSCs are faster

enhanced

at

reduced alveolar thickening, and decreased

self-renewal and differentiation than

bone marrow derived MSCs.24,25 The

alveolar

air-space

volume,

markers of inflammation.26

immunomodulatory effect of UC-MSCs is

This

due to secretion of galectin-1, HLA-G5 and

randomized

PGE2 molecules.23

describes the potential role of the umbilical

One

of

the

most

systematic controlled

review trials

of study

harmful

cord mesenchymal stem cells and their

consequences of SARS-CoV-2 infection is

effect on healing COVID-19 patients and

the excessive and aberrant host immune

reducing the risk of cytokine storms.

response, accompanied by a cytokine storm and the subsequent ARDS, resulting in

Method

multiple organ failure and death.26 MSCs have

a

powerful

immunomodulatory

ability, it offers a promising innovative

A systematic review was conducted Preferred Reporting Items for Systematic


Review and Meta-Analysis (PRISMA)

(mesenchymal cell*)) OR (extracellular

guidelines for objective studies for a

vesicle*))

relevant analysis in both screening and

(secretome)) OR (*umbilical cord)) OR

research.

(*UC)) AND (covid*)) OR (corona*)) OR

(Moher D, Liberati A, Tetzlaff J, Altman DGPRISMA Group. Preferred reporting items for systematic reviews and metaanalyses: the PRISMA statement. BMJ 2009;339:b2535.

.

doi: 10.1136/bmj.b2535 pmid: 19622551 )

OR

OR

(sars*cov*2*)

OR

(2019*nCov*)

OR

(SARS*Cov*)

OR

(COVID*19)

OR

(pandemic)

NOT

(wharton*jelly))))))))))))))). All citations were downloaded into an electronic citation manager using Mendley. Reviewers collect information on study design, hUC-MSC administration,

Eligibilty criteria

(exosome*))

sample

demographic,

survival rate, lymphocyte subpopulation, We included only randomised controlled

C-reactive protein, protein IL-6, protein IL-

trials study of umbilical cord mesenchymal

10, respiratory support, comorbidities

stem cell. No restriction were applied based

(diabetes and hypertension), PaO2/FiO2,

on severity of illness or setting.

and adverse events. Reviewers resolve discrepancies by discussion and, when

Information sources

necessary, with adjudication by a third

We searched the following literature sources for relevant studes with he database

party Risk of bias within individual studies

includes: Medline (Ovid and PubMed), PubMed

Central,

PsycInfo,

Cochrane

For each eligible trial and outcome,

Library, ScienceDirect, Portal Regional de

reviewers,

BVS, WHO ICTRP, BMC, Wiley Online

calibration exercises, use a revision of the

and Clinicaltrial.gov.

Cochrane tool for assessing risk of bias in

Data collection

following

training

and

randomised trials (RoB 2.0)28 to rate trials as (a) at low risk of bias; (b) some concerns,

Literature based research was being done

probably at low risk of bias; (c) some

independently by PG, MW, ME, and NA.

concerns, probably at high risk of bias; or

The databases using the boolean operator

(d) high risk of bias, across the following

with the format: (((((((((((((((((((MSC*))

domains:

OR (stem cell*)) OR (stroma cell*)) OR

randomisation process; bias owing to

bias

arising

from

the


departures from the intended intervention;

p Value of 0.642, some of the patients also

bias from missing outcome data; bias in

have comorbidities such as diabetes (1

measurement of the outcome; bias in

person), hypertension (3 people). Patients

selection of the reported results, including

are given IV 1x10^6/kg body weight UC-

deviations from the registered protocol;

MSC in 100 ml saline (0.9%), and the

bias due to competing risks; and bias arising

progress is monitored.

from early termination for benefit. We rate trials at high risk of bias overall if one or

The results are; many lymphocytes

more domains were rated as (c) some

are involved in this study, such as CD4,

concerns, probably high risk of bias or as

CD8, CD34, CD56, CD73, CD90 ; with the

(d) high risk of bias, and as low risk of bias

p Value for UC-MSC 0.064. We also

overall if all domains were rated as (b)

evaluate that in patients treated with MSCs,

some concerns, probably low risk of bias or

there is a decrease in inflammatory factors

(a) low risk of bias. Reviewers resolve

IL-6 (p Value 0.023) and increased anti

discrepancies by discussion and, when

inflammatory factors IL-10 (p Value 0.66),

necessary, with adjudication by a third

also for inflammatory factors like CRP p

party.

Value for UC-MSCs is 0.827]. Patients use the respiratory support intubation, and they use it for 16.63 ± 5.4 days.All these results

Result

are way better than the control group, but reported that there are some adverse events After screening 19.999 titles and

journals, 273 that evaluated the effect of hUCMSCs as a therapy for COVID-19 there are 4 clinical trials that show the most significant difference between the use of hUC-MSCs as a treatment for COVID-19 compared to the

like

disseminated

Coagulation

(DIC),

Intravascular thromboembolism.

This study results in a survival rate of 40 patients, 26 male and 14 female with p Value = .049.

control group with a very good results.

Another study is written by Shu et A multicentered, double-blind, randomized

al., 2020 , a single-center open-label,

clinical trial by Dilogo et al., 2021, included

individually

patients with COVID-19 that were treated

treatment-controlled trial, there are 12

with hUC-MSCs. There are 20 patients, 15

patients in this trial, with the age

of them are male and 5 are female with the

approximately 61.00 ± 17.87 and p Value

randomized,

standard

= 0,576. Patients also have comorbidities; 3


people have diabetes (25%) and 3 people

cardioversion,

have hypertension (33,3%). These patients

tachycardia, ventricular fibrillation, or

are given IV in right cubital veins 2x10^6

asystole, no transfusion-related infection

cell/kg

and no Cardiac arrest or death within 24 h

MSCs

in

100ml

saline.

Lymphocytes play a significant role in this

no

new

ventricular

postinfusion.

study, which is CD73, CD90, CD105, CD34, CD45, CD14 or CD11b, CD79α,

Study

CD19. The value of CRP is 0-75 mg/L, and

Randomized,

IL-6 is 0-37pg/mL. Patient uses ventilation

controlled phase 2 trial. The study was done

and the results are 3 (25%), p Value= 0.139.

between

27

design;

We

double-blind, October

2021

conducted

placebo and

16

November 2021 study included patients 1/2a

treated with MSCs. That was administered

randomized controlled trial, included 12

to 65 patients, 37 among that was Male

people, divided to 5 Male (41.7%), 7

(56.92%) also the rest 28 people was female

Female (58.3%)); and had signifcantly

(43.08%) to receive either UC-MSCs (4 ×

lower [P Value = 0.41]. People are given

107 cells per infusion) or placebo and had

100 ± 20x10^6 UC-MSCs in order to

no significantly lower . The baseline

achieve 50mL infusions of vehicle solution

characteristics

(human

and

between the two groups of patients in the

heparin). Many lymphocytes are involved

mITT population. Many lymphocytes are

in this study, such as CD90 of 97.9% ±

involved in this study, such as CD4 T cells

2.6% CD105 of 98.1% ± 1.4% CD34/CD45

(/μl) with the p Value : (641.00 (482.00,

of 2.2% ± 4.9%. The results of lymphocytes

760.00); CD8 T cells (/μl) with the p Value

subpopulation is CD90 of 97.9% ± 2.6%

: 371.00 (275.00, 520.00) in UC-MSC

CD105 of 98.1% ± 1.4% CD34/CD45 of

group also CD4 T cells (/μl) with the p

2.2% ± 4.9. Patients use high flow oxygen

Value: 734.00 (502.00, 1031.00) CD8 T

and result 0 [p Value= 0.05] After all, here

cells (/μl) with the p Value: 401.00 (307.00,

we provide the data set of survival rate 91%

593.00) in control group CRP were

in UC-MSC group, 42% in control group [P

matched in the two groups, baseline was

value = 0,015]. There are some adverse

1.95 (0.84, 3.53) (39.00, 51.00) days in the

effect occur in this stud ;Increase in

MSC group, and 1.38 (0.68, 2.26) in control

vasopressor dose, no infusion-associated

group. In common we analyzed Protein IL-

adverse events, no worsening hypoxemia,

6 or IL-10,in UC-MSC group IL-6= 7.86

no new cardiac arrhythmia requiring

(5.63, 9.84) and IL-6= 8.76 (6.54, 11.77) in

The

double-blind,

serum

phase

albumin

were

highly

consistent


control group. Respiratory support went to

high TF/CD142 has the potential to cause

1 (1.54%) and 0 (0.00%) in UC-MSC group

the patient to become hypercoagulable.24

and in control group with Ventilation or

MSS-TP) increments the survival rate

oxygen devices as instrument. Also we

of patients with basically sick COVID-19 by

discovered an interesting new fact about

2.5 times higher than the bunch that does not

diabetes 17 (26,15%) was ratio in UC-MSC

get MSS-TP. In reality, in basically sick

group and 10 (28,57%) was ratio in control group.

Another

was

Hypertension,12

(18,46%) was ratio in UC-MSC group and 5 (14,29%) was ratio in control group. PaO2/FiO2

in

UC-MSC

MSS-TP treatment can increment the survival rate 4.5 times higher than those who don't get this treatment. 25 There was no distinction between the

was

two gatherings of patients for CD4 T-

discovered 97.10 (1.31) and 96.97 (1.29) in

lymphocytes, neither in level of lymphocyte nor

control group. Either Adverse Events was

in outright number, but for CD8 T-cells the

increaseing in lactic acid dehydrogenase,

distinctions were huge for the two boundaries

elevation

alanine

which were in decrease in ICU patients. There

aspartarte

was a firm relationship between's the most

Hyperuricemia Grade 3 pneumothorax (1

noteworthy upsides of irritation pointers with

of

aminotransferase

group

COVID-19 patients with comorbidities, this

serum and

the lessening in level of CD8 T-lymphocytes.

case).

This impact was not seen with CD4 cells. IL-6 is largely described as a mediator of

Discussion

inflammation and autoimmunity. The positive

effect of hUC-MSCs on severe COVID-19 is

Umbilical cord-derived MSCs are

clear, but the specific molecular mechanism of

reported to be the most used stem cells, and

hUC-MSCs is not clear and still needs to be

the main route of administration is IV. In

further illustrated. The non-old style favorable

contrast

to incendiary impacts of IL-10 as a driver of

to

infusions

of

immature

microorganisms, which are utilized to target

cytokine

storms

during

COVID-19

and

explicit regions like a physical issue or a

consider protection from IL-10's traditional

dangerous joint for restricted recuperating,

mitigating activity as an elective novel

undeveloped cells directed intravenously can

instrument hidden raised IL-10 levels in

possibly arrive at each organ in body. UC-

patients with extreme COVID-19.

MSC can be given intravenously infusion.

It has been reported that diabetes is a

Intravenous administration is more suitable

risk factor for death in COVID-19 patients, so

for low TF/CD142. which when given a

for patients with severe COVID-19 with diabetes, hUC-MSC therapy may be the most


ideal

treatment.

complications

Patients used

with

diabetes

significantly

less

exogenous insulin after hUC-MSC infusion than usual.27

2. Weiss SR, Leibowitz JL. Coronavirus pathogenesis. Advances in virus research [Internet]. 2011 [cited 2021 Nov 15];81:85–164. Available from: https://pubmed.ncbi.nlm.nih.gov/2209408

Limitation The limitation in this review is that there are still a few published journals with RCT study designs with a UC-MSC focused on COVID-19 because they are still in the development process and registered trials are still in progress.

0/ 3. Li G, Fan Y, Lai Y, Han T, Li Z, Zhou P, et al. Coronavirus infections and immune responses. Journal of medical virology [Internet]. 2020 Apr 1 [cited 2021 Nov 15];92(4):424–32. Available from: https://pubmed.ncbi.nlm.nih.gov/3198122 4/

Conclusion hUC-MSC as a non-invasive treatment has the potential to provide a safe, effective therapeutic for critically ill COVID-19 patients, which could help mitigate the devastating economic and public health consequences caused by the rapid worldwide spread of SARS-CoV-2.

4. Cheng VCC, To KKW, Tse H, Hung IFN, Yuen KY. Two years after pandemic influenza A/2009/H1N1: what have we learned? Clinical microbiology reviews [Internet]. 2012 [cited 2021 Nov 15];25(2):223–63. Available from: https://pubmed.ncbi.nlm.nih.gov/2249177

Acknowledgment and Conflict of Interest

1/ 5. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and

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Anosmia and Ageusia As Prognostic Factor in COVID-19 in COVID-19 Patients: A Systematic Review Theresia Feline Husen* , Ruth Angelica**, R. Muhammad Kevin Baswara*** * Second Year Medical Student, AMSA-UI (felinetheresia@gmail.com) ** Second Year Medical Student, AMSA-UI (ruthangelicahou@gmail.com) *** Second Year Medical Student, AMSA-UI (kevinbaswara28@gmail.com)

Abstract Introduction : COVID-19 manifests in various clinical symptoms. Aguesia and anosmia are prominent olfactory and gustatory dysfunction in COVID-19 patients. Some studies has been done to examine ageusia and anosmia as a prognostic factors in COVID-19 patients Objective : This systematic review

aims to evaluate anosmia and ageusia as prognostic factors in

COVID-19 patients. Methods : This review selects cohort studies found by database using previously determined inclusion, such as COVID-19 patients with anosmia and ageusia, and exclusion criteria such as review papers. This review was arranged based on PRISMA guideline. Results : Four cohort studies were included in this systematic review, published between 2020 until 2021. These studies were compiled then assessed for risk of bias by using Newcastle-Ottawa Quality Assessment Scale converted by AHRQ. The results showed very low bias throughout the studies. Discussion: Anosmia and ageusia were mainly known as symptoms for COVID-19. These symptoms play a significant role in early diagnosis of SARS-CoV-2 infection. In our study, these factors have shown high prevalence to predict a prognosis for the COVID-19 infection. Although COVID-19 prognosis also depends on the other lying condition of the patients, patients with anosmia or ageusia had a lower mortality risk due to the lower body mechanism and cell inflammation mechanism toward the viral load that may not lead into the maladaptive cytokine release in response to infection generally called as a cytokine storm. Conclusion : This study has proven that anosmia and ageusia indicate a good prognosis in COVID-19 patients. COVID-19 patients with anosmia and ageusia have lower trajectory of the severity of the disease, hospitalization risk, and mortality. Thus, it is necessary to evaluate the clinical symptoms of the patients in order to predict the prognosis. Keywords : Anosmia, Ageusia, Prognostic COVID-19, Mortality COVID-19, COVID-19 hospitalization risk


ANOSMIA AND AGEUSIA AS PROGNOSTIC FACTOR IN COVID-19 PATIENTS: A SYSTEMATIC REVIEW Scientific Paper

Author : Theresia Feline Husen Ruth Angelica R. Muhammad Kevin Baswara Faculty of Medicine Universitas Indonesia Asian Medical Students’ Association Indonesia 2021


Introduction COVID-19 is an infectious respiratory disease caused by a virus called SARS-CoV2 (severe acute respiratory syndrome-coronavirus). The first case was reported in December 2020 in the capital city of Hubei province, Wuhan, China. Spreading all over the world, the COVID-19 outbreak has brought tremendous attention worldwide. The probable leading transmission of SARS-CoV2 is through droplet-borne transmission, either indirectly or directly, whereas airborne transmission is still unclear.1 According to World Health Organization data on November 7th 2021, There are 248,467,363 total cases of COVID-19 infection with 5,027,183 death cases. In Indonesia, there are 4,246,802 total cases with 143,500 death cases.2 The case fatality rate (CFR) caused by COVID-19 infection varies in countries around the world. The CFR in China was 2,3% and the CFR rate in Italy was 7,2%. The CFR increases as the age group increases. Respectively, the CFR of age groups in Italy for ≥ 80 years and 70-79 years is 12.8% and 20,2%. Based on a cohort study conducted in Italy, the CFR of 687 patients who were ≥ 90 years was 22%.

1

COVID-19 manifests in various clinical presentations.1 Some of the symptoms are cough, fever, hard to breathe, sore throat, nausea, myalgia, diarrhea, and neurological symptoms.3,4 Two of prominent symptoms in COVID-19 infection are anosmia and ageusia. These olfactory and gustatory dysfunctions are suggested to be caused by invasion of the olfactory bulb. The possible mechanism of COVID-19 neurotropism is by using the ACE2 receptor, which is easily found in nasal epithelial cells.1 A retrospective review with a multi-hospital database shows that 4% of 2892 COVID-19 inpatients report taste or smell loss.5 Another study also shows that olfactory and gustatory dysfunction happens in 5,6% and 5,1% in inhospital COVID-19 patients. However, A review states a significant data of anosmia in COVID19 patients, which is 62% of all COVID-19 patients from a meta-analysis.1 There is a different prevalence of COVID-19 patients with anosmia and ageusia between moderate-severe cases and asymptomatic-mild cases.The prevalence of mild-moderatie COVID-19 patients having anosmia and ageusia are 85,6% and 88,0% respectively whereas only 4,0% of in hospital patients with moderate to critical condition develop anosmia and ageusia.5,6 This number shows that anosmia and ageusia is found more often in asymptomatic and mild cases. Two studies have proven that there is a significant correlation between anosmia and ageusia in COVID-19 patients with reduced severe cases, in-ICU care, and mortality.7,8


Disturbance of smell and taste function is significantly higher in females than males with COVID-19 infection . A study states that the proportion of females to males experiencing smell and taste disturbance is 63,2% and 36,8% respectively. Smell and taste dysfunction also appears higher in younger group age, which in a study states that this feature has highest proportion in age group 10-20. The majority of COVID-19 patients reporting smell and taste dysfunction lack comorbidities.5 Taste and smell dysfunction has been suggested to be early symptoms of COVID-19 infection and manifested earlier than other symptoms especially in asymptomatic-mild cases.5,6,9 These clinical presentations perhaps have association with a milder disease and reduced mortality rate. Emergent research is starting to show a tendency that male have a higher incidence of developing severe cases than females. A study in Spain points out that hospitalized COVID-19 patients have a significant lower rate of taste and smell dysfunction than non hospitalized COVID-19 patients. Another study found that anosmia was greatly identical with outpatient care, while normosmia could be a predictor of hospital admission.5 There is accumulating evidence showing the relationship of taste and smell dysfunction and good prognosis of COVID-19. However, based on our knowledge, there is still no systematic review that summarizes the relationship of anosmia and ageusia and COVID-19 prognosis. Therefore, we thought a review about anosmia and ageusia and COVID-19 prognosis is needed to enhance our knowledge. Thus, this systematic review will investigate anosmia and ageusia in COVID-19 patients and their associations with COVID-19 prognosis. Materials & Method This systematic review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist.10 Search Strategy A comprehensive literature search was performed by three independent reviewers with multiple electronic databases, such as PubMed, Scopus, Wiley, and ScienceDirect up to 3 November 2021. The keywords used in the pursuit were “Anosmia” AND “Ageusia” AND “Prognostic COVID-19”. Where applicable and available, appropriate advanced search techniques were applied to narrow the search. Study Eligibility Criteria Studies were screened according to the following inclusion and exclusion criteria. Our inclusion criteria were (1) COVID-19 patients with anosmia and ageusia, (2) cohort study, and (3) assess anosmia and ageusia as prognostic factors. Exclusion criteria: (1) A review paper, (2) Studies that did not have a full-text version, and (3) written in languages other than English were excluded from this review. Furthermore, duplicates removal was performed using Mendeley software. Screening of titles and abstracts of studies was carried out according


to criteria of accessibility by three independent reviewers. Any disagreements were discussed into consensus. The planned procedure is illustrated in Figure 1.

Quality Assessment Each included study was assessed using the Newcastle Ottawa Scale designed for cohort studies. This tool consists of quality and risk of bias assessment based on every section of the included studies including selection, compatibility and outcome with a total of 9 stars. Studies with higher stars indicate better quality of cohort studies which show that the study has lower risk of bias.11 After total stars are calculated, the total accumulated stars are converted to the Agency Healthcare Research and Quality standards: good, fair and poor. 12 Thresholds for converting the Newcastle-Ottawa scales to AHRQ standards (good, fair, and poor):12 ● Good quality: 3 or 4 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome/exposure domain.12 ● Fair quality: 2 stars in selection domain AND 1 or 2 stars in comparability domain AND 2 or 3 stars in outcome/exposure domain.12 ● Poor quality: 0 or 1 star in selection domain OR 0 stars in comparability domain OR 0 or 1 stars in outcome/exposure domain.12 The quality assessment was done by three reviewers with each other blinded on others’ scoring, then discussed until consensus was reached. Summary Measures and Data Analysis Evidence-based analysis was conducted in this systematic review. Outcome assessment was done by three reviewers independently, then discussed further into a table. Data was extracted from the included studies based on following aspects: author and year of publication, study location, study design, participants, range/mean age, study period,symptoms, and outcome related to prognostics are stated in factors with its respective odds ratio and p-value. The results of the study were stated as suboptimal and optimal using odds ratio (p<0.05). Odds ratio (OR) with a 95% confidence interval and p-value below 0.05 was used to determine the association between anosmia and/or ageusia with good prognostic factors. Results Search Results and Study Selection


Initial search from PubMed, Scopus, Wiley, and ScienceDirect using search strategy mentioned above resulted in a total of 72 studies. Among them, 0 were deduplicated, while the other 64 studies were excluded after screening the titles and abstracts in terms of anosmia and ageusia as good prognostic factors studies. In addition, 4 studies were further excluded since 1 was a review paper, 1 only had an abstract available, 1 was a cross-sectional study and 1 did not assess OR. The search yielded in a final four studies, consisting of all cohort studies to be included in qualitative synthesis.The result of the study selection process is shown in Figure 1.

Figure 1: Flowchart of Study Selection in Accordance to PRISMA Statement Study Characteristic and Design The studies included with their data extracted are seen in TABLE 1. In total, there are 8,962 subjects included in our review. Study locations varied around two continents (Europe (n=2), America (n=2), and South America (n=1). These studies were conducted across a variety of ages with a minimum age of 10 years old. Qualitative

Analysis

of

Anosmia

and

Ageusia

Our study indicated that anosmia and ageusia could be used as the indicator for the good prognostic associated with lower mortality and ICU admission. The result significantly met minimum requirements for the scientific paper on the study that we have conducted besides our study consists of studies with considerable heterogeneity. This paper shows a cumulative of different fixed ratio and p-value that each study has presented. According to this paper, anosmia and ageusia in patients with COVID-19 infection indicated as a good predictor for the progressive prognostic for the patients health and wellbeing. To conclude, p value and the


odds ratio for the overall study shows a significant level of study of anosmia and ageusia as the symptoms for the good prognostic. Publication Bias Critical appraisal was done using Newcastle - Ottawa Quality assessment scale for cohort study to qualitatively assess the bias of the included studies. The score is converted to AHRQ standards which is divided into good, fair, and poor. All of our studies included in our review obtain good standards. Gonzáles 2021 obtains the lowest score (n=8) whereas the other three studies obtain higher scores (n=9). Table 1. Study Characteristics

Discussion Anosmia Anosmia is the inability or decreased ability to perceive smell/odor that could lead into a temporary or permanent damage of the nasal function caused by head injury, infection, inflammation, or the blockage of the nose.15 Nowadays, the reduction of smell is recognized as one of the cardinal symptoms of COVID-19; it was mentioned in one of the studies from China to affect about 5% of the COVID-19 patients, The direct viral infection targets the nasal epithelium and olfactory bulb, notably at the ACE2 receptor.16 On the other hand, some studies also determined anosmia in the case of COVID-19 as the marker of a COVID-19 infection, mostly after recovery.17 Anosmia was mainly known as a condition that is caused by a disturbance or blockage in the nasal pathway that may lead to the intrusion of the perception for someone to smell. In the case of COVID-19 infection, there are some factors that may results in the manifestation of anosmia, for instance inflammatory and obstructive disorders, head trauma, aging and neurodegenerative processes, congenital conditions, infective conditions, and also toxic agent that may lead into prohibition of the olfactory signal pathway and dysfunction of smelling.


The data shows that 50%—70% cases reported by anosmia was mainly caused by inflammation of the mucous membrane that indicated as the direct obstruction because of the complex biological response of body cells and tissue to protect themself from a harmful stimuli, such as viral infection, bacteria, and other pathogens. 18 Physiologically, the process of smelling begins with the entry of odorant molecules into the nasal cavity lined with olfactory epithelium. There are 5 types of cells in the epithelial lining: olfactory sensory neurons, sustentacular cells, microvillar cells, duct cells of Bowman's gland, and basal cells. The odorants bind to their receptors on the cilia, which are extensions of the olfactory sensory neurons to the mucus layer. The receptor is a G-protein coupled receptor, so this binding will activate Golf. Golf activation stimulates adenylyl cyclase, forming cyclic adenosine monophosphate. This causes the opening of chloride channels and an efflux of chloride ions, generating an action potential. The axons of these second-order neurons of the olfactory system are then projected to various areas of the central nervous system. 18 There are several mechanisms that are thought to explain olfactory disorders in COVID-19 patients. First, olfactory disturbances can be caused by nasal obstruction or congestion. In viral infections, patients often experience nasal congestion and runny nose, thereby interfering with the binding of odorants to their receptors on the olfactory epithelium. Obstruction can be caused by excess mucus or by inflammation of the lining of the nasal cavity. However, it is possible that this mechanism is not the main mechanism of anosmia, because it was found that most patients with anosmia do not experience nasal congestion and there is no evidence of swelling of the nasal mucosa.16,19 A second possible mechanism is the damage to the olfactory sensory neurons induced by viral infection. However, this mechanism is also debatable, as anosmia in COVID-19 generally improves in less than 1-2 weeks, while regeneration of olfactory neuron cells can take more than 2 weeks. In addition, the study also showed that olfactory sensory neuron cells did not express ACE2 and TMPRSS2, proteins that play an important role in the process of virus entry into cells. However, involvement or cell death of olfactory neurons can still be considered in cases of long-term anosmia. 16,19 Third, SARS-CoV-2 may also cause anosmia by disrupting olfactory centers such as the olfactory bulb and cortex via the axonal pathway. However, as with the previous mechanism, because olfactory neurons do not have ACE2 and TMPRSS2, this mechanism is still being questioned. Previous studies with transgenic mice with human ACE2 found that these mice developed brain infections after intranasal inoculation with SARSCoV virus through the olfactory bulb, so it is possible that SARS-CoV-2 could also enter through other structures or cells in the nasal cavity before entering the nasal cavity. to olfactory neurons. 16,19


Fourth, the mechanism of anosmia may be mediated by sustentacular cell damage. Sustentacular cells function as support cells and help the olfactory neurons by detoxifying harmful odorants, supporting the bonding of odorants with their receptors, and providing nutrients to support the work of the olfactory neurons. Although the target of the SARS-CoV-2 virus is absent on the olfactory sensory neurons, ACE2 and TMPRSS2 are expressed in large numbers on the sustentacular cells of the olfactory epithelium. In addition, the regeneration of sustentacular cells is also faster than that of olfactory neurons, so they are more in line with the time frame for the appearance and disappearance of anosmia. However, what remains a question is whether sustentacular cell damage alone is sufficient to cause olfactory disturbances, so the mechanism still requires further study. 16,19

The fifth hypothesized mechanism is inflammation-related anosmia. Cytokine storms in COVID-19 are closely related to various organ dysfunctions, so olfactory neurons are thought to be one of the affected.19 Based on a study by Torabi et al, it was found that olfactory epithelial biopsies taken from COVID-19 patients had significantly higher levels of TNF- than the control group.20 Another proinflammatory cytokine, IL-6, was also found to have a significant correlation with olfactory function; decreased IL-6 levels correlated with improvement in anosmia symptoms.21 However, the exact mechanism by which these cytokines cause anosmia is not fully understood.19 Ageusia Gustatory dysfunction can be categorized into loss of taste sensation, which includes ageusia (loss of the ability to taste) and hypogeusia (decreased ability to taste), and changes in taste, called dysgeusia. The mechanism of ageusia will be further discussed in the next paragraph.22 There are several hypotheses that try to explain the mechanism of ageusia in COVID-19 patients. First, it is suspected that the virus can use the ACE2 receptor which is expressed on the taste buds of the tongue and salivary glands. SARS-CoV-2 infection is thought to be able to directly damage cells in the taste buds that express ACE2, or cause an inflammatory reaction which then leads to taste disturbance.19 The second mechanism is hypothesized to be due to dysfunction of the cranial nerves. There is a close relationship between anosmia and ageusia, so it is suspected that ageusia is a continuation effect of olfactory disorders. However, several studies have found a higher prevalence of ageusia in COVID-19 than anosmia, so there may be other mechanisms by which SARS-CoV-2 can induce gustatory disorders.6,23 In addition, dysgeusia can also occur when there are disorders of other cranial nerves that also play a role in gustatory transmission, such as cranial nerves VII, IX and X, but especially cranial nerves VII. The virus initially colonized the nasopharynx, then through the Eustachian tube can enter the middle ear and cause damage to the chorda tympani, resulting in dysgeusia symptoms.19,22


Third, SARS-CoV-2 can also cause ageusia through interaction with sialic acid receptors. Sialic acid is a component of saliva and plays a role in protecting the glycoproteins that carry gustatory molecules into the taste buds from degradation by enzymes. A decrease in sialic acid in saliva is associated with an increase in the taste threshold. Thus, binding of SARS-CoV-2 to the sialic acid receptor may interfere with its action and accelerate the degradation of gustatory molecules.19,22 There is also a hypothesis that ageusia in COVID-19 is related to zinc deficiency. Zinc is thought to be an important mineral in carbonic anhydrase that plays a role in maintaining taste sensations.19 What's more, there are studies showing that zinc levels in COVID-19 patients are significantly lower than the normal group.24 Previous studies have also shown that zinc supplementation can improve gustatory function in dysgeusia patients.25 However, the exact mechanism that links zinc with dysgeusia in COVID-19 is not yet known, so this hypothesis still requires further study.19 Prognostic of COVID-19 The prognosis of COVID-19 mainly is dependent on factors that include the patient’s age, the severity of the infection, comorbidities, treatment, and response to the treatment, even though some studies mention that the saturation of peripheral oxygen measurement through pulse oximetry may be an independent factor that could be used as an accurate marker for the prediction of COVID-19 infection.26,27 WHO currently estimates the global fatality rate by COVID-19 infection is 2,2% that is affected by other lying conditions, such as severity of the illness. Some studies stated that this mortality rate from COVID-19 closely related to acute respiratory distress syndrome (ARDS).27 In the study that we have conducted, the prognosis of COVID-19 corresponds with the manifestation of anosmia and ageusia. Patients with anosmia or ageusia had a significantly good prognosis for the COVID-19 patients that indicated a lower body mechanism and inflammation toward the viral load because the low level of cell inflammation results in low risk of cytokine storm. One of the studies from a group of patients show that the symptoms of anosmia tend to have significantly low levels of IL-6 that plays a central role in the cytokine storm.27 Anosmia and Ageusia as A Diagnosis and Prognostic Anosmia and ageusia mainly correlated only as the symptoms or common findings in COVID-19 patients, despite the fact that smell and taste disorders can be challenging to diagnose some kind of illness. These factors are an essential key point in the diagnosis of COVID-19 infection, but our studies also show that it could be an important factor to see the prognosis of patients so the therapeutic treatment could be made more specific and systematically. Study by Talavera et al, which assessed hospitalized COVID-19 patients with anosmia,


stated that anosmia was correlated with lower mortality and ICU admission due to the distinct clinical presentation and less severe inflammatory response. The mortality rate of the participants with anosmia was only 22.0%.8 On the other hand, the study conducted by Porta-Etessam et al shows a significant result with the symptoms of anosmia and ageusia that were inversely related to the risk of death (OR 0.26 and Z-score 5.05).13 Study by Husain et al also show the mortality rate in COVID-19 patients with anosmia and ageusia was significantly lower than those without anosmia and ageusia (P<0.001) due to the milder disease trajectory.5 The last study that we have read shows another prognosis in patients with anosmia and ageusia related to the lower risk of hospitalization with the odds ratio of 0.08.14 To conclude, we present a study that not only evaluates the prognosis of anosmia and ageusia in COVID-19, but also a review in the severity and mortality rate that may help clinicians worldwide. Strength Limitation In our knowledge, this is the first systematic review assessing anosmia and ageusia as prognostic factors in COVID-19 infection. The results of this systematic review showed a significant correlation between anosmia and ageusia as a good prognostic factor in COVID-19 patients. Despite the challenge and the data that we have shown before, this study also has several limitations according to those inherent study databases, including the potential for selection, information, and recall bias. We conducted this study by gathering the data from several cohort studies from the studies that they have done before. Therefore, maybe some of the values for the specific study variable could be missed out and excluded by the control of a humanly biased point of view. Also, the population in all the studies were not comparable in terms of ages, sex distribution, comorbidities, environmental factors, and other things that we could not state more. Conclusion and Recommendation In conclusion, this systematic review shows that anosmia and ageusia in COVID-19 patients has a good prognosis in COVID-19 patients. COVID-19 patients with anosmia and ageusia have lower trajectory of the severity of the disease, hospitalization risk, and mortality. Anosmia and ageusia is found more frequently in mild COVID-19 cases. Thus, it is necessary to evaluate the clinical symptoms of the patients in order to predict the prognosis. Acknowledgement We have nothing to declare. Conflict of Interest We declare that we have no competing intention for completing this review.


References 1. Chowdhury SD, Oommen AM. Epidemiology of COVID-19. J Dig Endosc. 2020;11(01):03–7. 2. World Health Organization. WHO coronavirus (COVID-19) dashboard - situation by region, country, territory & area [Internet]. Geneva: World Health Organization; [cited 2021 Nov 7]. Available from: https://covid19.who.int/table 3. Cascella M, Rajnik M, Aleem A, Dulebohn SC, Napoli RD. Features, evaluation, and treatment of coronavirus (COVID-19) [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan [updated 2021 Sep 2; cited 2021 Nov 9]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK554776/ 4. Mesquita RR, Silva LCF Jr, Santana FMS, de Oliviera TF, Alcântara RC, Arnozo GM, et al. Clinical manifestations of COVID-19 in the general population: systematic review. Wien Klin Wochenschr. 2021;133(7–8):377–82. 5. Husain Q, Kokinakos K, Kuo Y, Zaidi F, Houston S. Characteristics of COVID-19 smell and taste dysfunction in hospitalized patients. Am J Otolaryngol .Nov-Dec 2021;42(6):103068. doi: 10.1016/j.amjoto.2021.103068. 6. Lechien JR, Chiesa-Estomba CM, De Siati DR, Horoi M, Le Bon SD, Rodriguez A, et al. Olfactory and gustatory dysfunctions as a clinical presentation of mild-to-moderate forms of the coronavirus disease (COVID-19): a multicenter European study. Eur Arch Oto-Rhino-Laryngology [Internet]. 2020;277(8):2251–61. Available from: https://doi.org/10.1007/s00405-020-05965-1 7. Purja S, Shin H, Lee JY, Kim EY. Is loss of smell an early predictor of COVID-19 severity: a systematic review and meta-analysis. Arch Pharm Res [Internet]. 2021;44(7):725–40. Available from: https://doi.org/10.1007/s12272-021-01344-4 8. Talavera B, García-azorín D, Martínez-pías E, Trigo J, Hernández-pérez I, Valle-peñacoba G, et al. Anosmia is associated with lower in-hospital mortality in COVID-19. J Neurol Sci. 2020 Dec 15; 419: 117163. 9. Tong JY, Wong A, Zhu D, Fastenberg JH, Tham T. The Prevalence of Olfactory and Gustatory Dysfunction in COVID-19 Patients: A Systematic Review and Meta-analysis. Otolaryngol - Head Neck Surg (United States). 2020;163(1):3–11.


10. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372. 11. Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, Tugwell P. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2013 [cited 2021 Nov 7]. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. 12. AHRQ. Assessing the risk of bias of individual studies in systematic reviews of health care interventions.

2021

[cited

2021

Nov

7].

Available

from:

https://effectivehealthcare.ahrq.gov/products/methods-guidance-bias-individual-studies/methods 13. Porta-Etessam J, Núñez-Gil IJ, González García N, Fernandez-Perez C, Viana-Llamas MC, Eid CM, Romero R, Molina M, Uribarri A, Becerra-Muñoz VM, Aguado MG, Huang J, Rondano E, Cerrato E, Alfonso E, Mejía AFC, Marin F, Roubin SR, Pepe M, Feltes G, Maté P, Cortese B, Buzón L, Mendez JJ, Estrada V. COVID-19 anosmia and gustatory symptoms as a prognosis factor: a subanalysis of the HOPE COVID-19 (Health Outcome Predictive Evaluation for COVID-19) registry. Infection. 2021 Aug;49(4):677-684. 14. González C, García-Huidobro FG, Lagos AE, Aliaga R, Fuentes-López E, Díaz LA, García-Salum T, Salinas E, Toro A, Callejas CA, Riquelme A, Medina RA, Palmer JN. Prospective assessment of smell and taste impairment in a South-American coronavirus disease 2019 (COVID-19) cohort: Association with the need for hospitalization and reversibility of dysfunction. Int Forum Allergy Rhinol. 2021 Aug;11(8):1273-1277. 15. Li X, Lui F. Anosmia. [Updated 2021 Sep 25]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK482152/ 16. Butowt R, von Bartheld CS. Anosmia in COVID-19: Underlying Mechanisms and Assessment of an Olfactory Route to Brain Infection. Neuroscientist. 2020 Sep 11:1073858420956905. doi: 10.1177/1073858420956905. Epub ahead of print. PMID: 32914699; PMCID: PMC7488171. 17. Touisserkani SK, Ayatollahi A. Oral Corticosteroid Relieves Post-COVID-19 Anosmia in a 35-YearOld Patient. Baba Y, editor. Case Rep Otolaryngol [Internet]. 2020;2020:5892047. Available from: https://doi.org/10.1155/2020/5892047 18. Han, A. Y. et al. (2020) ‘Anosmia in COVID-19: Mechanisms and Significance’, Chemical Senses, 45(6), pp. 423–428. 19. Mutiawati E, Fahriani M, Mamada SS, Fajar JK, Frediansyah A, Maliga HA, Ilmawan M, Emran TB, Ophinni Y, Ichsan I, Musadir N, Rabaan AA, Dhama K, Syahrul S, Nainu F, Harapan H. Anosmia and dysgeusia in SARS-CoV-2 infection: incidence and effects on COVID-19 severity and mortality, and the possible pathobiology mechanisms - a systematic review and meta-analysis. F1000Res. 2021 Jan 21;10:40.


20. Torabi A, Mohammadbagheri E, Dilmaghani NA, Bayat A, Fathi M, Vakili K, et al. Proinflammatory cytokines in the olfactory mucosa result in COVID-19 induced anosmia. ACS Chemical Neuroscience [Internet].

2020

Jun

11

[cited

2021

Nov

9];11(13):1909-13.

Available

from:

10.1021/acschemneuro.0c00249. 21. Cazzolla AP, Lovero R, Muzio LL, Testa NF, Schirinzi A, Palmieri G, et al. Taste and smell disorders in COVID-19 patients: role of interleukin-6. ACS Chemical Neuroscience [Internet]. 2020 Jun 11 [cited 2021 Nov 9];11(17):2774-81. Available from: doi.org/10.1021/acschemneuro.0c00447 22. Lozada-Nur F, Chainani-Wu N, Fortuna G, Sroussi H. Dysgeusia in COVID-19: possible mechanisms and implications. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology [Internet]. 2020 Sep [cited 2021 Nov 9];130(3):344-6. Available from: 10.1016/j.oooo.2020.06.016. 23. Giacomelli A, Pezzati L, Conti F, Bernacchia D, Siano M, Oreni L, et al. Self-reported olfactory and taste disorders in patients with severe acute respiratory coronavirus 2 infection: a cross-sectional study. Clinical Infectious Diseases [Internet]. 2020 Jul 28 [cited 2021 Nov 9];71(15):889-90. Available from: 10.1093/cid/ciaa330 24. Jothimani D, Kailasam E, Danielraj S, Nallathambi B, Ramachandran H, Sekar P, et al. COVID-19: poor outcomes in patients with zinc deficiency. International Journal of Infectious Diseases [Internet]. 2020 Nov [cited 2021 Nov 9];100:343-9. Available from: 10.1016/j.ijid.2020.09.014. 25. Guan G, Mei L. A case series: zinc deficiency as a potential contributor to oral dysgeusia. Modern Approaches in Dentistry and Oral Health Care [Internet]. 2018 June 18 [cited 2021 Nov 10];2(5):2005. Available from: 10.32474/MADOHC.2018.02.000146 26. Heckmann SM, Hujoel P, Habinger S, Friess W, Wichmann M, Heckmann JG, et al. Zinc gluconate in the treatment of dysgeusia—a randomized clinical trial. Journal of Dental Research [Internet]. 2005 Jan 1 [cited 2021 Nov 9];84(1):35-8. Available from: 10.1177/154405910508400105 27. Jang JG, Hur J, Choi EY, Hong KY, Lee W, Ahn JH. Prognostic factors for severe coronavirus disease 2019 in Daegu, Korea. Journal of Korean Medical Science [Internet]. 2020 Jun 15 [cited 2021 Nov 9];35(23):1-10. Available from: 10.3346/jkms.2020.35.e209


Appendix 1. Studies quality assessment based on Newcastle-Ottawa Quality Assessment Scale11 Selection

Talavera et al, Porta-Etessam

Husain et al, Gonzáles et al,

2020

et al, 2020

2021

1) Representativen ess

of

the

exposed cohort a)

truly √

representative of the average COVID-19 patiens in the community *

b)

somewhat

representative of the average COVID-19 patiens in the community * c)

selected

2020


group of users eg

nurses,

volunteers

d)

no

description

of

the

derivation

of the cohort 2) Selection of the non exposed cohort a) drawn from √ the

same

community as the

exposed

cohort * b) drawn from a different source c)

no

description

of

the

derivation

of

the

non

exposed cohort

3)

a) secure record √

Ascertainment

(eg

of exposure

records) * b)

surgical

structured

interview * c) written self


report d)

no

description 4)

a) yes *

Demonstration that outcome of interest was not present at start of study b) no Comparability

1) Comparability of cohorts on the basis of the design

or

analysis

a) controls

study for

Anosmia and/or Ageusia *

b)

study

controls for any additional factor * (This criteria

could

be modified to indicate specific control


for a second important factor.)

Outcome

1) Assessment of outcome

a) independent

blind assessment *

b)

record

linkage *

c) self report

d)

no

description

2) Was followup long enough for outcomes to occur

a) yes (select an adequate follow up period for


outcome

of

interest) *

b) no

3) Adequacy of follow

up

of

cohorts

a)

complete

follow up - all subjects accounted for *

b) subjects lost to follow up unlikely

to

introduce bias small

number

lost - > 95 % follow up, or description provided

of

those lost) *

c) follow up rate

<

95%

(select

an

adequate

%)

and

no


description

of

those lost

d) no statement

Total stars

9

9

9

8

Appendix 2. Studies quality assessment based on Newcastle-Ottawa Quality Assessment Scale-AHRQ Standards 12 Cohort

Selection

Comparability

Outcome

Quality Assessment based on AHRQ

Talavera, 2020

****

**

***

Good

Porta-Etessam et al, ****

**

***

Good

2020 Husain, 2021

****

**

***

Good

Gonzáles, 2020

***

**

***

Good


Misdiagnosis between Dengue Fever and Coronavirus Disease 2019 (COVID-19) in Utilizing Serological Examination: A Systematic Review Yong Yee Wen1, Ester Elita1, Satria Budi Nugraha1, Raesha Fachira Isfianto1 1

Faculty of Medicine, Pelita Harapan University, Tangerang, Indonesia

Abstract Introduction : Dengue is a mosquito-borne viral infection which is found in tropical and subtropical climates worldwide and Coronavirus disease 2019 (COVID-19) is respiratory illness caused by severe acute respiratory syndrome. Dengue and COVID-19 are difficult to distinguish due to shared clinical and laboratory features. There are similar symptoms and laboratory findings with both dengue fever and COVID-19, misdiagnosis of serological examination, can cause dangerous possibilities such as incorrect or delayed initial treatment. Objective: Our objective in this study is to find out about the misdiagnosis between Dengue Fever and COVID-19 Disease by using serological examination Material and Methods : This systematic review was independently extracted by authors, studies filtered from 2016 to 2021 from online databases such as NCBI, PubMed, springer link, research gate, and Google Scholar by using MeSH terminology of keywords Misdiagnosis between Dengue Fever and COVID-19 Disease. The studies extracted were compared and selected according to our criteria where there is misdiagnosis between Dengue Fever and COVID-19 disease. Exclusions in this study include, Meta-analysis, Literature Review, Casecontrol Study, Systematic Review, Case Report, Animal Study. The quality of the studies were then assessed using the Newcastle-Ottawa scale. Results and Discussion : We used the PICO method and MeSH terminology and obtained 4 studies, which consists of 3 randomized controlled trials and 1 retrospective study that will be analysed and reviewed. The initial search yielded 19 results from PubMed, 42 results from NCBI, and 58 results from Publisher. All these studies informed that the usage of serological examination can cause the misdiagnosis between dengue fever and COVID-19 disease. Conclusion : From 4 studies that we evaluated, all of the study ended up with the conclusion that there is misdiagnosis between COVID-19 and Dengue in Utilizing serological detection. Keywords : Misdiagnosis, Serological examination, Dengue, DENV infection, COVID-19, SARS-CoV-2 infection


Misdiagnosis between Dengue Fever and Coronavirus Disease 2019 (COVID-19) in Utilizing Serological Examination: A Systematic Review Yong Yee Wen1, Ester Elita1, Satria Budi Nugraha1, Raesha Fachira Isfianto 1 1

Faculty of Medicine, Pelita Harapan University, Tangerang, Indonesia

Introduction Dengue is a mosquito-borne viral infection which is found in tropical and sub-tropical climates worldwide, mostly in urban and semi-urban areas. Dengue virus is transmitted via female mosquitoes mainly Aedes aegypti and Aedes albopictus. These mosquitoes are also vectors of chikungunya, yellow fever and Zika viruses. Dengue is most influenced by rainfall, temperature, relative humidity in some places, and unplanned rapid urbanization.1 Dengue can cause a lot of kinds of disease. Which can range from subclinical disease to severe flu-like symptoms in those infected. When people develop severe dengue, sometimes they can have complications associated with severe bleeding, organ impairment, and plasma leakage. Today, severe dengue affects most Asian and Latin American countries and has become a leading cause of hospitalization and death among children and adults in these regions. Coronavirus disease 2019 (COVID-19) is a serious respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) COVID-19 presents as a respiratory syndrome, mostly characterized by fever and cough disease.2 In 2020 the threat of extremely contagious SARS CoV-2 or COVID-19 in Indonesia emerged, which has infected more than 4 million persons by November 14th , 2021, and expected to grow exponentially except there are strict government policy that regulate behavior of this virus. There are similar symptoms and laboratory findings with both dengue fever and COVID-19, paving way to dangerous possibilities such as incorrect or delayed initial treatment due to misdiagnosis of serological examination. Dengue and coronavirus disease 2019 (COVID-19) are difficult to distinguish because they have shared clinical and laboratory features.3 Most commercial rapid diagnostic tests (RDT) avail- able in the market are for the detection of SARS-CoV-2 antibodies, with relatively high sensitivity and specific- ity, especially when samples are taken later in the disease progression. However, it is hampered by the apparent cross-reactivity resulting in false-positive results.4 Thus, potential co-infection of COVID-19 and dengue virus, as well as antibody cross-reactivity, might impact clinical manifestation and diagnosis.5 The case of misdiagnosis between COVID-19 and Dengue can be find as well in Singapore4 and become some additional burden in Brazil.6


In this systematic review, we wanted to analyze whether there was any misdiagnosis between dengue fever and COVID-19 disease in Utilizing Serological Examination.

Methods For our systematic review, we collect and use our data from several randomized control trial studies, retrospective studies, and clinical trials published in online sources including NCBI, PubMed, springer link, scopus, research gate, microsoft academic research, and Google Scholar. The randomized control trials and retrospective study that we used were published within 2016 2021. The data were accessed in March - November 2021 using the following keyword or terms : A systematic analysis, such as PICO analysis and MeSH terminology, was also used in this study. For PICO analysis, we used “Patients with positive serological detection results of COVID19 and Dengue” for People or Population (P). For the Intervention (I), we used “Serological Detection”. There is no Comparison (C) in this review. Lastly, the Outcome (O) we used “there is misdiagnosis between COVID-19 and Dengue ”. The inclusion criteria used in this systematic review are countries with dengue endemic, patients with positive result of COVID-19 serological detection, patients with positive result of DENV and COVID-19 infection, retrospective study, randomized clinical study. While the exclusion criteria are Meta-analysis, Literature Review, Case-control Study, Systematic Review, Case Report, Animal Study. The quality of study was assessed using the Newcastle-Ottawa scale, with the results of three high quality studies8,9,10 and one high risk quality study11

Result and Discussion We used the PICO method and MeSH terminology and obtained 4 studies, which consists of 3 randomized controlled trials and 1 retrospective study that will be analyzed and reviewed. The initial search yielded 19 results from Pubmed, 42 results from NCBI, and 58 results from Publisher. The PRISMA flow chart is shown in Figure 1, depicting the process of choosing studies for the systematic review. After pairing with the inclusion and exclusion criteria, we eliminated 13 results from Pubmed, 38 results from NCBI, and 55 results from Publisher, filtering double literature also done and carried out 4 full text articles that were relevant for our quantitative analysis. The literature selections were summarized in Figure 1.


Figure 1. Literature Search and Selection Process


Table 1 Summary of studies of Misdiagnosis between COVID-19 and Dengue in Utilizing Serological Examination

Authors

Place

Study Design

Date of

Sample size

publication

(COVID-

Result

Conclusion

19/Dengue) Khairunisa et

Indonesia

al8

Randomized

June 7, 2021

N = 158 (120/4)

Clinical Trial

4 out of 120 COVID-19 sample

Using the serological RDT to determine

positive presence of DENV viral

COVID-19 or dengue infection might lead to

tested by RT-PCR

misdiagnosis

38 asymptomatic healthy sera sample showed one person positive NS1 and Positive DENV IgG Lokida et al9

Indonesia

Retrospective

August 5, 2020

N = 42 (35/7)

Study

DENV IgM and IgG were detected by

There is a probability of misdiagnosis

ELISA in 7 out of 42 COVID-19

COVID-19 in areas hyperendemic for

patients that were tested by RT-PCR.

tropical infections with overlapping presentations such as dengue. It was also recommended to use the validated NS1 and IgM or IgG RDT to improve the specificity of identifying differentiate acute and repeat dengue infections, in order to prevent the further transmissions of COVID-19 and provide COVID-19 treatments as soon as possible for the patients.

Santoso et al10

Indonesia

Randomized Controlled Trial

March 11, 2021

N= 204 (95/3)

95 RT-PCR from positive COVID-19

Cross-reactions and false-positive results

patients, one patient positive dengue

between dengue and COVID-19 are very


IgM, one positive dengue IgG, and

Regardless of the high specificity of the

one patient positive dengue both IgG

COVID-19 RDT, it is possible for cross-

and IgM as well as NS1.

reaction and false-positive outcomes among

And out of asymptomatic patient 33

COVID-19 and dengue to happen and that

samples that tested positive for

co-infection can likewise happen.

COVID-19 IgG, 2 samples (6.1%) also tested positive for dengue IgG, while out of 19 sam- ples that tested positive for COVID-19 IgM, 4 samples (21.1%) also tested positive for dengue IgG Nath et al11

India

Randomized Clinical Trial

June 10, 2021

N= 33 (13/33)

There are 13 DV Ab rapid test

The results explain that DV Abs, give cross-

positive sera, the samples were tested

reaction with SARS-CoV antigen and give

with rapid SARS-CoV-2 IgG and

false-positive results in COVID-19 rapid

IgM detection lateral flow-based strip

IgG and IgM test.

test. Five of the thirteen DV Ab-positive samples were found to produce falsepositive bands in SARS-CoV-2 IgG and IgM detection rapid tests.


Based on Khairunisa et al8, with total 158 samples, there are 38 sera samples from healthy individuals in Surabaya were collected using the dengue RDT (pre-COVID-19 date), and 120 samples from COVID-19 patients. After all the COVID-19 plasma being tested with DENV IgM/IgG (SD Biosensor, Suwonsi, Korea), 4 out of 120 samples were serologically positive for dengue IgG while the NS1 test and RT-PCR test showed a negative result (Table 2)

Table 2. Samples from COVID-19 patients with positive dengue antibodies Khairunisa et al8 conducted in the study that there are two possibilities that can explain this result. First, four patients had dengue infection before the hospital admission due to COVID-19. Therefore, the antibody remained circulating in the blood although the virus had already gone. Dengue antibody response in the post infection can last for a long time, because IgM circulates in the body up to 2 to 6 months, while IgG persists longer, generally up to 6 months to 2 years after dengue primary infection. The second possible reason is the presence of antibody cross-reactivity between COVID-19 and dengue infection in the samples. This condition could become a significant hurdle, especially in the dengue-endemic areas since it could give false-positive results and misdiagnoses, thereby delaying appropriate patients' treatment. The IgM detection compared with ELISA indicated 97.5% and 96.6% sensitivity and specificity, respectively. This study concluded that the use of serological RDT to determine COVID-19 or dengue might have misdiagnosis as the result. A 2020 study conducted by Lokida et al9 at Tangerang District Hospital, Indonesia, reaffirms challenges associated with diagnosing COVID-19 in areas hyperendemic for tropical infections with overlapping presentations such as dengue. The retrospective study revealed that 7 out of 42 patients who were tested positive for SARS-CoV-2 by RT-PCR, were also tested positive for DENV infection, considering the positive findings of DENV IgM RDT, IgG RDT, and IgG


ELISA (Table 3). These findings were concerning since misdiagnosis of acute COVID-19 due to presumption of dengue can result in inadvertent omission of targeted precautions, which could lead to transmissions to contacts, including family, colocated patients, and healthcare workers. Furthermore, the misdiagnosis can also delay the receipt of standard of care COVID-19 treatment. However, the positive findings didn’t show the signs of acute coinfections with DENV and were probably caused by recent secondary DENV infections, which overlapped the serological testings of COVID-19 patients. The misdiagnosis can also be caused by the nosocomial infections, which the patients may have contracted SARS-CoV-2 during hospitalization. Hence, this study recommended the use of a validated NS1. which will improve the specificity of identifying acute dengue cases, and IgM or IgG RDT, to reaffirm clinicians in conducting the COVID-19 evaluations.

Table 3. Interpretation of dengue diagnostic test results among patients with COVID-19 In a study conducted by Santoso et al.10, specificity of Rapid Diagnostic Test (RDT) samples (n=204) from Indonesia were evaluated for cross-reactivity between the diagnosis of dengue fever against COVID-19 with both diseases having matching laboratory and clinical features. Specificity of COVID-19 RDT against 60 dengue-confirmed samples was assessed. Then, 95 COVID-19-confirmed samples were tested against dengue RDT. Lastly, 49 asymptomatic individuals that are positive for COVID-19 samples were tested on dengue RDT


(Table 4). The limitation of this study is that it did not evaluate the sensitivity of COVID-19 RDT data and that it did not perform repeat testing and along these lines can’t preclude the chance of recent but not simultaneous dengue disease. The study observed that all COVID-19 RDT have a high specificity against dengue samples (%=98.3-100). On the other hand, only 3 samples of COVID-19-confirmed samples were positive on dengue RDT, suggesting the possibility of coinfection. Lastly, out of all 49 samples of asymptomatic COVID-19 individuals, only 6 samples were tested positive on dengue RDT. It is concluded that regardless of the high specificity of the COVID-19 RDT, it is possible for cross-reaction and false-positive outcomes among COVID-19 and dengue to happen and that co-infection can likewise happen.

Table 4. Characteristics of samples used in the study In a study conducted by Nath et al11., they performed a rapid DV IgG and IgM detection tests (SD Bioline, Abbott) on 33 archived serum samples from DV-diagnosed patients from the 2017 dengue cases. The purpose was to find out DV Ab cross-reactivity in a lateral flow-based immunoassay system for SARS-CoV-2 Ab detection. The serum samples were collected from


2017, which was long before the COVID-19 emergence in order to rule out the probability of preexisting SARS-CoV-2 Abs in it, and in that condition, will react in the COVID-19 Ab tests. Thirteen subjects with DV Ab rapid test positive sera were collected to rapid SARS-CoV-2 IgG and IgM detection lateral flow-based strip test. Each of the COVID-19 rapid test strips was coated with SARS-CoV-2 antigen based on the manufacturers’ manuals.

Table 5. Rapid IgG and IgM test results for COVID-19 and Dengue Table 5 confirms that DV Abs can cross react with SARS-CoV-2 antigen and give falsepositive results in COVID-19 rapid IgG and IgM tests. The result represents that in dengueendemic countries, COVID-19 detection-based assays can result in false-positive COVID-19 IgM and also IgG results in case of DV infected patients. The study concludes that sero-surveillance needs to be complemented with NAT and/or virus antigen tests for definitive diagnosis of COVID19 and dengue in regions where both the viral diseases are endemic.

Conclusion From 4 studies that we evaluated and analysed, all of the study ended up with the conclusion that there is misdiagnosis between COVID-19 and Dengue in Utilizing serological detection. Therefore we suggest that it is necessary to have more specific immunoassays for


accurate differential diagnosis of these cross-reacting dengue and coronavirus (SARS-CoV-2), especially in Dengue endemic areas. However, there are some limitations such as limited samples and limited time for collecting samples, also this study need further study whether the misdiagnosis is caused by genetic, or the specificity of the serological, or only because recent infection.

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10. Santoso MS, Masyeni S, Haryanto S, Yohan B, Hibberd ML, Sasmono RT. Assessment of dengue and COVID-19 antibody rapid diagnostic tests cross-reactivity in Indonesia. Virology Journal. 2021;18(1). 11. Nath H, Mallick A, Roy S, Sukla S, Basu K, De A, et al. Archived dengue serum samples produced false-positive results in SARS-COV-2 lateral flow-based rapid antibody tests. Journal of Medical Microbiology. 2021;70(6).



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