Wastewater Based Epidemiology(WBE) surveillance tool for the COVID-19 pandemic for counties identified at a greater vulnerability utilizing the US CDC’s Social Vulnerability Index(SVI) Jessica Mosher, MBA*, Krystin Kadonsky+ , Colleen C. Naughton, PhD, MS + and Ryan G. Sinclair PhD, MPH School of Public Health, Loma Linda University, Loma Linda, CA 92354 * indicates current LLU SPH DrPH student +Civil and Environmental Engineering, University of California Merced, 95343
Introduction: The vast majority of SARS-CoV-2 testing has been performed within populations consisting of voluntary subjects (e.g. those purposefully seeking test results in a clinical or hospital setting) or those required to submit to testing for various reasons such as work or educational requirements (Havers et al., 2020). To date, the available standardized methods of SARS-CoV-2 testing and data collection rely on these sources of information and thus do not reflect multiple vulnerable populations in disadvantaged areas, individuals who for myriad reasons are either unable or unwilling to receive testing and are unrepresented in the current SARS-CoV-2 testing data (Havers et al., 2020). This project addresses the problem of a lack of consistent testing for SARS-CoV-2 for vulnerable populations in disadvantaged areas. The proposed solution was to use a Wastewater-Based Epidemiology (WBE) approach to detect SARS-CoV2 in small communities, rural areas, and compartmentalized populations. This allowed a study of community infection dynamics and focused on low-income areas that had inefficient disease monitoring systems. This study collected Geographic Information System (GIS) site information of all known wastewater treatment plants and other wastewater monitoring programs across the United States. The monitoring programs of these sites were compared against the United States CDC Social Vulnerability Index (SVI) on a map to visualize the coverage of wastewater-based surveillance distribution both nationwide and at the county level to determine whether or not SVI impacted the prevalence of WBE programs. Our hypothesis is that this type of surveillance is uniquely positioned in affluent communities and may not yet provide important surveillance data for disadvantaged areas.
Methods:
Results:
The methods utilized to collect data on the proliferation of WBE across the nation was conducted by the Environmental Systems Graduate Group at the University of California Merced. That group “combined standard literature review, direct submissions, and daily, social media keyword searches” (Naughton, C. C., et al, 2021) to maintain a dashboard of locations using WBE. The resulting data was combined with the US CDC’s Social Vulnerability Index(SVI) percentile and RPL Theme 1 variable on a county level and visualized nationwide.
The US CDC SVI Socioeconomic theme/dataset entitled "RPL_THEME1" utilizes a percentile rank based on fifteen different variables, (e.g. unemployment, income, high school graduation rates) which range from 0 to 1 with larger values indicating a higher level of vulnerability (CDC, 2018). The Socioeconomic theme was visualized nationwide to determine the utilization of WBE based on SVI. This data is displayed in Table 1. Those counties identified as having the greatest vulnerability only account for 8% of the total national usage of WBE.
Conclusion: There is much room for improvement of WBE utilization in highly vulnerable communities. Environmental justice demands that there should be a more evenly distributed use of WBE across all levels of SVI and on a state level as displayed in Figure 1. This proven surveillance system can be utilized to predict SARS-CoV-2 outbreaks 4 to 10 days in advance, among other communicable diseases (Sinclair, R. G., et al, 2008). References: Centers for Disease Control and Prevention (CDC). (2018). CDC social vulnerability index 2018. Agency for Toxic Substances and Disease Registry (ATSDR). Retrieved January 15, 2022, from https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI _documentation_2018.html Havers, F. P., Reed, C., Lim, T., et al (2020). Seroprevalence of antibodies to SARS-COV-2 in 10 sites in the United States, March 23-May 12, 2020. JAMA Internal Medicine, 180(12), 1576. https://doi.org/10.1001/jamainternmed.2020.4130 Naughton, C. C., Roman, F. A., Alvarado, A. G., Tariqi, A. Q., Deeming, M. A., Bibby, K., Bivins, A., Rose, J. B., Medema, G., Ahmed, W., Katsivelis, P., Allan, V., Sinclair, R., Zhang, Y., & Kinyua, M. N. (2021). Show us the data: global covid-19 wastewater monitoring efforts, equity, and gaps. https://doi.org/10.1101/2021.03.14.21253564 Sinclair, R. G., Choi, C. Y., Riley, M. R., & Gerba, C. P. (2008). Pathogen surveillance through monitoring of sewer systems. Advances in Applied Microbiology, 249–269. https://doi.org/10.1016/s0065-2164(08)00609-6
Figure 1.
Acknowledgments Colleen C. Naughton*1, Fernando A. Roman, Jr.1, Ana Grace F. Alvarado1, Arianna Q. Tariqi1, Matthew A. Deeming1, Kyle Bibby2, Aaron Bivins2, Joan B. Rose3, Gertjan Medema456, Warish Ahmed7, Panagis Katsivelis8, Vajra Allan9, Ryan Sinclair10, Yihan Zhang11, Maureen N. Kinyua11 *Corresponding Author cnaughton2@ucmerced.edu 1Department of Civil and Environmental Engineering, University of California at Merced, Merced, CA 95343, USA 2Department of Civil & Environmental Engineering & Earth Science, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN, 46556, USA 3Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan 48824, USA 4KWR Water Research Institute, Groningenhaven 7, Nieuwegein, 3433 PE, the Netherlands 4Delft University of Technology, Stevinweg 1, Delft, 2628 CN, the Netherlands 6Michigan State University, 1405 S Harrison Rd, East-Lansing, Michigan, 48823, USA 7CSIRO Land and Water, Ecosciences Precinct, 41 Boggo Road, QLD 4102, Australia 8Venthic Technologies, Kipoupoleos 129, Peristeri, Athens, Greece 9PATH 2201Westlake Avenue, Suite 200 Seattle, WA 98121, USA 10Schools of Public Health and Earth and Biological Sciences, Loma Linda University Loma Linda, CA 92350, USA 11Department of Civil and Environmental Engineering, University of California at Davis, Davis, CA 95616, USA