March 2023 - The Epidemiology Monitor

Editor’s Note:

A monthly update covering people, events, research, and key developments

This month’s issue takes a deep look at Artificial Intelligence and what it means for epidemiologists. We hear from a global expert in this space Dr. Cox who writes a piece on the implications of causal inferences. (At the EpiMonitor, we would love to hear perspectives, opinions, field experience, and research from epidemiologists like you. Consider submitting a piece for a future newsletter at: info@epimonitor.net) Finally, we’ve even brought Chat GPT on to write an article based on a question posed by us.

We also introduce a new column called “Research to Practice” where we highlight imperative, on-the-ground work from epidemiologists at health departments. For this issue, Marin County reports how they handled realworld, messy data to make policy decisions during the pandemic.

We continue to provide you with our crossword series, Notes on People, an overview of what we are reading from the public media, and upcoming events for epidemiologists. Don’t miss our summer program update!

Finally, don’t miss the Job Bank offerings this month. We have some fantastic job openings advertised both here and on our website. We continue to field inquiries from employers throughout the US and beyond.

In This Issue

-2-

-4-

-6-

-9-

-12-

-13-

-15- Crossword Puzzle

-17- What We’re Reading

-19- Notes on People

-22-

-24- Marketplace – Jobs & Events

Epidemiological Tools Powered By Artificial Intelligence

Author: Katelyn Jetelina, MPH, PhD

AI is here and it’s like the wind. Like it or not, it’s coming and there is very little we can do to stop it.

It’s unclear what this means for our field of epidemiology, biostatistics, and public health. I may be one of the few that are optimistic. I don’t think AI will replace epidemiologists the human element in public health is absolutely essential. (If you need more convincing, read the NY Magazine article: “Is AI Turning Me Into an Obsolete Machine?) But a person using AI may be a threat due to increased productivity.

More than 200+ tools have been released in just the last week. The frenetic pace is overwhelming, to say the least. I scraped a few worth your time exploring that may be relevant for our field:

 Consensus AI—Scientific summaries. For any research question, hit the “synthesize” button, and the models will deliver a concise summary of the top 5-10 papers. There are a number of limitations: Research quality is not part of analysis. The summary is only as good as search logic. They do not have access to all research.

 Docktopus AI- Create compelling slides.

 Quotify- AI-powered tool to extract meaningful quotes from books and articles.

 SciSpace AI- A research assistant to save hours per day.

 Neuroflash- Brainstorm content, like titles for papers, briefs, or blog posts.

 Lirio-May be useful for a department of public health that combines behavioral science and artificial intelligence into “precision nudging” to improve health choices and outcomes.

There are also tools within apps that are noteworthy:

 Canva- Magic presentations (generate a slide deck from a prompt) Or magic write.

 Adobe Firefly- modify images and create multimedia content by providing simple text inputs

 PDF Extract API- automatically understands content structure to extract text, tables and images

I’ve started playing around with AI. There are a few themes, and specifically limitations to the current AI systems, that are worth recognizing for our field specifically.

1. No real-time information. AI is only as good as the data that goes into it. Because of this, AI is not good at real time information. For example, I asked how we fared with the flu season this year. This is what is spit out:

2, Search terms are crucial. There is a whole new employment field born with the rise of AI called “prompt engineer”. And, rightfully so. AI is only as good as what you ask it. At a Statistica webinar last week, a speaker provided a fantastic example. They wanted to create an image of a hot dog, so in the prompt wrote “a hot dog”. Well, what came out was a flaming dog in a hotdog bun. Better prompts mean better results.

3. Biases can be programmed in. This is a major concern given mis- and disinformation already have significant influence in our field. For example, a reporter asked ChatGPT to write a negative piece on climate change and then a positive one. After, they asked for a positive article on Joe Biden and then a positive article on Donald Trump. The system was more than willing to write a negative piece on climate change and a positive piece on Biden but refused to write a positive piece on climate change or Trump. The program said it refused requests that didn't align with its programming or ethics.

What’s clear is that AI is good at repetitive tasks and spewing back data. It is not good at thinking or being creative. For the time being we will need humans for that. If you’ve started exploring with AI tools, we would love to hear from you! Are there any lessons that you’ve learned so far with AI? And apps that we are missing in the list above for our field? Please comment on the Epi Monitor Facebook page or Twitter @theEpimonitor! ■

Editor’s Note:

As this column was being written a group of over 1,000 technical experts, including Elon Musk, Apple Creator Steve Wozniak and others released a letter asking that the government order a pause on all work related to AI for a period of six months. The timeout that was proposed was intended to provide a breathing period during which guidelines could be established that would govern the future of AI. You can see a copy of their letter here: http://bit.ly/3Zoxytv

All the discussion around the topic of AI has led to a flurry of articles that attempt to describe in layman’s terms exactly what AI is and what it does. In addition there are a similar number of pieces that try to define the perceived dangers or improvements that AI may offer to humanity. One of the best articles that we have seen surfaced while we were researching this issue and we thought you might find it of interest. http://bit.ly/3ZsXi7Y

Check out our article on page 4 to see what AI is capable of doing – it might surprise you!

We Asked Chat GPT About Gun Control

Authors: Katelyn Jetelina MPH, PhD

Madeline M. Roberts MPH, PhD

In light of this special AI issue and the national tragedy in Nashville, we asked Chat GPT what it thought of gun control. Specifically, we queried “write a paper in favor of gun control”. This was its response. Our comments/reactions follow.

Chat GPT:

As a language model AI, I do not have personal beliefs or opinions, but I can provide an example of a paper in favor of gun control.

Gun control has been a hotly debated topic in America for years, with both sides of the argument presenting strong points. However, as the number of mass shootings, homicides and suicides by firearm continues to rise, it is becoming increasingly clear that stricter regulations on gun ownership and access are necessary to prevent further harm to communities across the nation.

The Second Amendment of the United States

Constitution grants American citizens the right to bear arms, and many gun enthusiasts argue that this right should not be restricted in any way. However, it is important to note that the framers of the Constitution could not have foreseen the devastating effects of modern automatic weapons and high-capacity ammunition magazines. These tools of destruction have no civilian application and are only useful for killing large numbers of people quickly.

While mental health must be addressed as a factor in some mass shootings, the solution lies not in allowing greater access to guns, but in providing better mental health care that could

prevent such individuals from ever getting their hands on lethal weapons in the first place. There is no need for civilians to be allowed to own military-grade weapons or to stockpile large numbers of guns and ammunition. Such

- Chat GPT cont'd on page 5

weapons are designed for military use and are not necessary for hunting, self-defense or any other legitimate civilian use.

It is important to note that gun control measures do not necessarily mean confiscation or a ban on all firearms. It may include universal background checks, regulations on the sale and transfer of firearms and high-capacity magazines, and a ban on assault weapons. By implementing such measures, the government can ensure that guns remain out of the hands of those who are likely to misuse them and reduce gun violence.

In the aftermath of tragedies such as the shootings at Sandy Hook, Pulse nightclub or Las Vegas, it is clear that something needs to be done to address the issue of gun violence in America. Individuals, families and communities have the right to feel safe and secure in their homes and towns, and implementing gun

control measures can help to achieve this goal. It is time for lawmakers to put politics aside, listen to the voices of the American people, and take the necessary steps to make our nation safer for all.

Our Reactions:

There are clearly not some not evidence-based claims here, including emphasizing better mental health care provision as “the solution.” This emphasis is presumably because many articles on the web also underscore the mental health component—Chat GPT is only as good as the information from which it can pull. Additionally, we noticed that it pulled relatively “old” examples of mass shootings. This is probably because Chat GPT only pulls data from 2021 and earlier. It’s not up to date. We were surprised, however, at how relatively wellwritten this was. It will be interesting to see how the implications of this play out for educational settings where writing papers is required.■

Local Data for Local Action: A community team approach for mobile vaccination units

The first of our new “Research to Practice” articles to highlight the work of health dept epidemiologists

Authors: Jasmine Soriano, LeeAnn Prebil, Matthew Willis Marin County Dept of Health & Human Services

It was a Wednesday morning in January of 2021 and I logged in nervously to the Marin County COVID-19 Vaccination Strategy Meeting and waited for others to virtually arrive. We did this every week; however, this was different because we were in the midst of a COVID-19 tsunami in Marin County due the holidays and colder weather. A perfect storm for respiratory viruses. We were seeing an average of 2 deaths and 100 cases per day.

Help was finally here in our fight against COVID19 vaccines. But, we had a big problem. Demand far outpaced supply.

This particular morning, tough decisions had to be made on where our mobile vaccination teams were deployed. Which groups do we focus on in outreach and messaging? Who gets priority? Answers to these questions were shaped by the

local epidemiological data our team prepared in lock hand with a coalition of healthcare providers, community-based organizations, school leadership, faith-based leaders, and elected officials. Knowing that our analyses determined who would be offered the vaccine the next day made our impact as epidemiologists clear. At the time, the state of California depended on local health jurisdictions to coordinate distribution of vaccines to a network of local vaccine providers. On a weekly basis, each California county was allocated a certain number of doses. Receiving the full allocation relied on effective use of prior allocations. This model required a locally defined vaccination strategy which made two elements crucial: 1) timely, local data and 2) countywide collaboration.

Local data led us to modify national or state guidance for tailored county policies. In January 2021, Marin County limited vaccine availability

- Marin cont'd on page 7

The Marin County Public Health Team

to residents 75 years or older, despite CDC’s and California’s threshold at 65 years of age. This decision was based on two factors

1. Marin County’s older age distribution, and

2. Local COVID-19 mortality rates.

Our analysis of the association between vaccine status and mortality within our community made this decision clear. For the public, we explained it this way: “Three out of four COVID19 deaths in Marin are among our residents 75 years or older” and, “In Marin today, a vaccine offered a resident above age 75 is more than 300 times more likely to save a life than a vaccine offered to someone under age 50.”

Aligning messaging across the community, with compelling local data and with the buy-in of the countywide vaccine coalition, helped justify a narrower focus when residents of other age groups advocated to their providers and elected leaders.

One month into vaccine distribution, Marin had the highest vaccination coverage of residents 75 years and older of any county in the nation, likely contributing to the county’s relatively low cumulative mortality despite our demographic risk profile.

Timely data and cross-domain collaboration shaped the COVID-19 vaccination strategy during these Wednesday morning meetings. Each week, we organized vaccination coverage data by census tract, race/ethnicity, age, and income level. We showed community-level COVID-19 burden through case rates, percent positivity, hospitalization, and death rates. We developed a vaccine prioritization system using census tract level COVID-19 case rates, vaccination coverage, and community resource level (using the California Healthy Places Index) to direct vaccine operations in real time. We also showed wait times at vaccination sites, and explored vaccine hesitancy through a public survey.

An example of a weekly slide used to report real-time data by Marin County - Marin cont'd

These data were shared with the public through the Marin County COVID-19 Surveillance webpage. Marin residents were provided with information updated daily they could use to track progress toward our equity goals, understand the rationale for local policies, and make individual health decisions. Communication with the public was bidirectional. We crafted responses to public inquiries about the data and honed our dashboard to ensure clarity of communication. This transparency likely contributed to the community’s trust in government and healthcare providers, and ultimately, high vaccination rates.

Our epidemiological work was not routine or fixed. COVID-19 vaccine data was like a river, in ever-changing motion. Gaining access to the state immunization registry was one of many steps in scouring the landscape of useful data sources. As new groups became eligible and new vaccine formulations were added, we developed methods to show vaccine coverage by relevant strata. Population denominators derived from Census Bureau data became puzzles we were tasked to solve. We worked closely with our Information Technology department to develop local data collection systems, and shared tools and ideas with epidemiologists from other jurisdictions.

The coalition continued pivoting local vaccination operations based on the nearly real-

time data we presented each week. Over time, we saw silos in our health and social safety net systems dissipate through the shared goal of vaccinating our population. We learned that all stakeholders, including community members, share an appetite for data, provided it is translated into culturally relevant and meaningful terms. This understanding has contributed to our standing as one of the most highly vaccinated counties in the nation, for all age and race/ethnicity groups.

One frequently cited challenge to a single national vaccination strategy is the diversity of communities across the nation. Most political, demographic, economic and cultural realities are hyper-local, and exert strong influence over vaccine access and uptake. In our experience, using local data to define a coherent strategy ensures more efficient and equitable vaccine uptake.

On those Wednesday mornings, at the center of a local campaign to save lives through vaccines, our team felt a unique responsibility to perform excellent epidemiology. Helping drive public health practice where it matters most, at the level of community, is a unique reward of a local epidemiologist. We will carry the lessons from our pandemic response as we face new public health threats, and our approach to rally around local data as a driving force for action will be natural. We will make good use of that Wednesday morning meeting. ■

ChatGPT and Causal Reasoning in Epidemiology

Author: Louis Anthony Cox, Jr., PhD tcoxdenver@aol.com

A new generation of artificial intelligence (AI) systems has arrived. It’s already beginning to transform the highly skilled cognitive work of knowledge workers including researchers, data analysts, and programmers if not yet the deliberations of policymakers and the choices of decision-makers and risk managers. What are the implications for epidemiologists and casual reasoning?

The underlying technology consists of “large language models” (LLMs) that can engage in fluent and well-informed conversations with human users by continually calculating highly probable argumentation patterns and generating next words and phrases. This process is based on conditional probabilities estimated

How can large language models help epidemiologists?

from massive training sets, such as the corpus of web-accessible documents – a technology sometimes caricatured as “autocomplete on steroids”. One of the currently best-known LLMs, ChatGPT, was launched in November of 2022. (“GPT” stands for “generative pre-trained transformer” reflecting the ability of such models to generate answers to questions, text summaries, stories, poems, and so forth using pre-trained neural nets that transform input sequences of words to output sequences, i.e., responses from the AI.)

How can epidemiologists take advantage of this emerging AI technology? Asking ChatGPT itself produced the following chat (italicized text is the author’s query; plain text is ChatGPT’s response; bold font highlights the parts of ChatGPT’s response that the author considers best summarize the main points):

Large language models like GPT-3 can help epidemiologists in several ways:

1. Data Analysis: Epidemiologists often have to analyze large amounts of data to identify patterns and trends. Large language models can help process and analyze this data more efficiently, which can help epidemiologists identify new insights and correlations.

2. Information Retrieval: Epidemiologists need access to vast amounts of scientific literature and research papers to stay updated on the latest findings. Large language models can help search and retrieve this information more efficiently, which can save time and improve the accuracy of their research.

3. Predictive Modeling: Epidemiologists often use predictive modeling to forecast the spread of diseases and plan for public health interventions. Large language models can help improve the accuracy of these models by incorporating more data and variables, which can lead to more accurate predictions.

4. Natural Language Processing: Epidemiologists often need to communicate their findings to the public and policymakers in clear and accessible language. Large language models can help generate summaries and explanations of complex scientific concepts, which can make their research more accessible to a wider audience.

Overall, large language models have the potential to revolutionize the field of epidemiology by enabling faster, more accurate data analysis and more effective communication of research findings to policymakers and the public.

At the moment, these and other use cases and potential benefits are perhaps more aspirational than real, as ChatGPT struggles to provide accurate references for its outputs (sometimes making up plausible-sounding ones, reflecting its underlying conditional probability models) and often answering technical questions with plausible-sounding answers that may not be correct, and hence that require human checking. However, larger and more powerful LLMs are on

their way, and current ones are already useful if they are used with an understanding that their responses are not necessarily trustworthy. For example, the following question and response illustrate the current state of information retrieval and synthesis using ChatGPT to answer a question about fine particulate matter (PM2.5). Parts of the text in bold and italics deserve further scrutiny in the author’s opinion, as explained below.

Query: What are the few most important confounders of PM2.5-mortality associations?

PM2.5-mortality associations have been extensively studied in epidemiology, and several confounders have been identified that can affect the strength and interpretation of these associations. The following are a few of the most important confounders:

1. Temperature: Temperature is a strong confounder of the PM2.5-mortality association because both high temperatures and high levels of PM2.5 can increase mortality rates. Therefore, studies that do not adjust for temperature may overestimate the effect of PM2.5 on mortality.

2. Socioeconomic status: Individuals from lower socioeconomic backgrounds are more likely to be exposed to high levels of PM2.5, and they may also be more vulnerable to the health effects of air pollution. Therefore, studies that do not adjust for socioeconomic status may overestimate the effect of PM2.5 on mortality.

3. Smoking: Smoking is a major contributor to mortality, and smokers are more likely to be exposed to high levels of PM2.5. Therefore, studies that do not adjust for smoking may overestimate the effect of PM2.5 on mortality.

4. Health status: Individuals with pre-existing health conditions are more vulnerable to the health effects of air pollution. Therefore, studies that do not adjust for health status may overestimate the effect of PM2.5 on mortality.

5. Other air pollutants: Other air pollutants, such as ozone and nitrogen dioxide, can also affect mortality rates. Therefore, studies that do not adjust for other air pollutants may overestimate the effect of PM2.5 on mortality.

It is important for epidemiologists to consider and adjust for these confounders when studying PM2.5-mortality associations to accurately estimate the effect of PM2.5 on mortality.

The responses are certainly helpful in stimulating thought about possible confounders of fine particulate matter (PM2.5)-mortality associations, but their details require checking and thought. (For example, is it true or merely plausible that “smokers are more likely to be exposed to high levels of PM2.5”? Can’t individuals from lower socioeconomic backgrounds have higher mortality rates for many reasons other than possibly being “more vulnerable to the health effects of air pollution”? And is “Health status” an example of confounding or of effect modification?) Nonetheless, the potential for this technology to help epidemiologists is clear. It can remind them of relevant considerations, list the assumptions of technical methods and models, summarize what regulators and others have said, and in general act as a usually helpful, but not completely trustworthy, junior research assistant.

Of greater concern is that ChatGPT is not trained in ideal reasoning patterns but on the body of human reasoning found on the web. An extended (multipage) dialogue with ChatGPT recently published in Global Epidemiology (Cox, 2023) shows ChatGPT making and defending very strongly worded initial causal claims (“It is well-established that exposure to ambient levels of PM2.5 does increase mortality risk”) that it gradually modifies under sustained questioning to a much weaker conclusion that “It is not known with certainty that current ambient levels of PM2.5 increase mortality risk. While there is strong evidence of an association between PM2.5 and mortality risk, the causal nature of this association remains uncertain due to the possibility of omitted confounders, such as lagged daily temperature extremes, that could plausibly explain the observed associations.” Along the way, it displays classic fallacies of

human reasoning and argumentation such as treating evidence of association as evidence of causation until challenged. Further, ChatGPT also introduced red herring and strawman arguments its response to a question about controlling for lagged daily temperatures was, “it is not always possible to control for every single potential confounder” even though it did not deny that the specific confounder in question could in fact be controlled for. However, the current version of ChatGPT is already open to sustained Socratic truth-seeking dialogue and will modify its initial position within a chat (although not yet its starting position for new chats) in light of a reasoned discussion.

The advent of LLMs and the emergence of genuinely useful conversational AI is seen by many as a likely turning point in the co-evolution of humanity and technology (Kissinger et al., 2021). For epidemiologists, it seems likely that as this technology improves – and major improvements are imminent – it will be applied to criticize and improve its own reasoning about causation and prevention of diseases and will become a valuable research assistant and then partner in discovering more effective ways to use data analysis and sound epidemiological reasoning to improve human health and longevity. This revolution has already begun. ■

References

Cox LA (2023). Causal reasoning about epidemiological associations in conversational AI. Global Epidemiology 5.

https://doi.org/10.1016/j.gloepi.2023.100102

Kissinger HA, Schmidt E, Huttenlocher D (2012). The Age of AI and our Human Future. Little Brown and Company. New York, NY.

Erasmus Summer Programme

Name Erasmus Summer Programme

Sponsors Erasmus MC Graduate School

Location Erasmus University Medical Center, Rotterdam, The Netherlands

Program year 33

Types and dates of Courses

One-week morning and/or afternoon courses

Two week courses

Three week courses Workshop

Number of Courses 22

Language English

Number of faculty 30

Target audience Master students, researchers, executives, health professionals

Cost Varies – see website

Deadline for registration Online registration – deadline TBC

Limit on participants Max per course – see the listing on the website for each course

Course directors Prof. Arfan Ikram, MD, PhD

Contact information Nihes@erasmusmc.nl

https://erasmussummerprogramme.nl

Comments Erasmus Summer Programme

Fast Forward: Accelerate your scientific career

Taught by leading international experts in the health sciences, the Erasmus Summer Programme provides essential updates in a range of applied medical and healthcare disciplines.

Whether you are a student, researcher, health professional or executive in the health sciences, this state-of-the-art programme provides the flexibility to mix and match the courses to your own individual needs.

The Erasmus Summer Programme provides a wide range of fundamental to advanced courses in disciplines such as public health, epidemiology, genetic epidemiology, statistics, biostatistics, clinical research, prevention and more

Descriptive Epidemiology Data Proves Extremely Valuable In Setting Vaccine Policy And Preventing Disease

Author: Roger Bernier, MPH, PhD

“A simple yet novel idea”. That’s how Matthew Moore and Cynthia Whitney, epidemiologists at the Centers for Disease Control and Prevention in Atlanta, describe an active surveillance program that was population- and laboratorybased for invasive bacterial infections, including those caused by Streptococcus pneumonia. The modest goal of the program was to identify and characterize these infections, however, the descriptive surveillance data have contributed in substantive ways “to every pneumococcal vaccine policy decision in the past 20 years,” according to Moore and Whitney writing in the journal Emerging Infectious Disease published ahead of print (see below).

Scope of Surveillance

The program begun two decades ago initially tracked invasive pneumococcal disease in 7 states with a population greater than 19 million and grew to include other sites covering 31 million persons by 2014. The methods used to count cases were audits of clinical laboratories where specimens were tested coupled with reviews of medical records in each site to ascertain underlying conditions and discharge status. Estimates of disease burden in this population have been provided annually since 1998.

Risk Assessments

Moore and Whitney provide multiple examples in their article of how descriptive data proved useful for vaccine policy. Data showing an

increased risk in infants not eligible at the time for vaccination and in older persons who were eligible but not vaccinated influenced vaccine advisory bodies to recommend pneumococcal vaccine for children and to intensify efforts to raise coverage for adults over 65. Descriptive data on cases and antimicrobial resistance was used to shape treatment policy for pneumonia and meningitis. Sometimes data from special studies were used not to recommend more vaccination but to recommend limiting the age at which adults should be targeted for vaccination. This was shown to be desirable because the existing target age recommendation already included most of the high risk persons. This fact was not known when the question about broadening the target age for vaccination first arose.

Natural Experiments

The existence of the ongoing surveillance program allowed investigators to take advantage of “natural experiments” when vaccine shortages occurred to evaluate different vaccine dose schedules. This work produced evidence that using three instead of four doses of vaccine for children could produce very high efficacy.

Modes of Transmission

An interesting payoff of the surveillance data on asymptomatic infections was to elucidate the dynamics of pneumococcal transmission. While the primary driver for immunizing children was initially the prevention of otitis media,

- Vaccine cont'd on page 11

subsequent surveillance data showed that because vaccinated children were not being colonized with pneumococci to the same extent, population-based surveillance data showed that disease in adults decreased as well. According to the authors, “… a key driver after [vaccine] introduction was the reduction in adult disease…The cost per IPD (invasive pneumococcal disease) episode averted without consideration of herd protection was $33,000, and the cost per episode averted with herd protection decreased to $5,500. This observation fundamentally changed the method for cost-effectiveness analyses of pneumococcal conjugate vaccines, not only in the United States but also in other countries.”

Broadening the Recommendation

Despite the success of pneumococcal vaccines

in reducing disease in children and adults, surveillance data showed that the remaining disease burden in adults was sufficiently high for CDC’s vaccine advisory group to recommend pneumococcal vaccine in 2014 not only for high risk persons but for all adults 65 years or older. According to the authors, this was perhaps “the widest-ranging” change in vaccine policy made possible by the descriptive surveillance data.

In concluding their review, the authors reemphasize that the surveillance programs “have contributed in fundamental ways to every pneumococcal vaccine recommendation in the United States since 2000.”

To read the article, visit: https://tinyurl.com/osf2p5e ■

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What’s Up Doc?

Our crossword puzzle was created by by Dr. Richard Dicker A former CDC employee and not-quite-retired epidemiologist. For an online version go to: http://bit.ly/3JRWfZs For the solution to February’s crossword please go to page 18.

- Crossword Questions cont'd on page 16

Across

1. TV doc with great diagnostic skills and horrible bedside manner

6. David Muir's employer

9. Hoover and Three Gorges, for example

13. Like some old buckets

14. Milne bear

16. Bypass

17. What Wall Street's Gordon Gekko said is good

18. Blanched

19. British sailors' scurvy preventive

20. Pittsburgh product

22. Fan

24. Tortoise racer

25. Doc of bluegrass and Arthur Conan Doyle

26. Doc of the NBA

29. Have a syncopal episode

31. "___ on a Grecian Urn"

32. Dr. of 1964 nuclear bomb satire film

37. Third male child of Adam and Eve

39. DC's time zone during winter

40. Pennsylvania port

41. Risk ratio is a measure of this

46. Building wing

47. Gooseneck and swing-arm

48. Birds of extinction

50. Housekeeper Bedelia's first name

53. "Your majesty"

54. Irrational outbursts

56. Single

58. Footnote abbr.

59. Coffee or tea order

61. Like Donkey Kong

64. "___ thousand flowers bloom"

65. House votes

66. Primate of Madagascar

67. Cut down

68. TV doc in her 19th (and last) season

69. "Head, shoulders, ___, and..."

Down

1. Harley Davidson, Inc.'s stock symbol

2. "Shattered (Turn the Car Around)" band

3. Hawaiian strings

4. Boil

5. Ingratiates

6. Doc-repelling fruit

7. Feathery wrap

8. Inflation-driven increase in benefits (abbr.)

9. Doc who can speak with animals

10. Arabian princes

11. Copy, in an old-fashioned way

12. NYU Business School's name

15. Harry Potter's owl

21. In the past, in the past

23. 55-Down has one

26. Civil rights activist Parks

27. Bad day for Caesar

28. Docs for dachshunds

29. What the rabbi does during Yom Kippur

30. The "A" of ABM

33. Harvest

34. Hydrox rival

35. Loathsome

36. Unagi fish

38. Doc of Wild West (actually a dentist)

42. Older brother of 37-Across

43. One of the words of MRI

44. Thor's dad

45. What norovirus was originally called

49. Dredge

50. Pomegranate seeds

51. "______, Black Label,..." (vintage beer commercial)

52. "Don't Cry for Me, Argentina" musical

53. Like dishwater

55. "Lion King" villain

57. Roosevelt coin

60. Hurricane's center

62. What Morgan and Morgan does

63. Time units for Staph food poisoning incubation period (abbr.)

Editor's Note: All of us are confronted with more material than we can possibly hope to digest each month. However, that doesn't mean that we should miss some of the articles that appear in the public media on topics of interest to the epi community. The EpiMonitor curates a monthly list of some of the best articles we've encountered in the past month. See something you think others would like to read? Please send us a link at info@epimonitor.net and we'll include it in the next month

Avian Flu

♦ According to scientists in Cambodia, bird flu has mutated to infect people

http://bit.ly/3lXBrb5

Public Health Topics

♦ CDC warns about the rise of untreatable shigella bacterial infections

http://bit.ly/40wZMU8

♦ Our food may be giving us Alzheimer’s disease

http://bit.ly/3G54S1K

♦ What will the next pandemic be – a panel of experts respond

http://bit.ly/3nCtOYc

♦ Authorities seek to arrest woman with tuberculosis for refusing care

http://bit.ly/3K0oWmT

♦ EPA proposes national limits on PFAS in drinking water

https://cnb.cx/3zD9fO5

♦ Native American epidemiologist interviewed on approaching epidemiology with empathy

http://bit.ly/3lXHRHi

♦ 6 former Phillies players died of brain cancer – the Astroturf contained dangerous chemicals

http://bit.ly/3Zx1IL3

♦ Thousands hired in public health during the pandemic are losing their jobs.

http://bit.ly/3KkYMg1

♦ Newly revealed records show the EPA sided with polluters in Butte

http://bit.ly/3ZCjXyU

- Reading cont'd on page 18

[Type a quote from the document or the summary of an interesting point. You can position the text box anywhere in the document. Use the Text Box Tools tab to change the formatting of the pull quote text box.]

COVID-19

What We're Reading This Month - con't

from page 14

♦ No one really knows how much COVID is silently spreading…again

http://bit.ly/3nAfxLz

♦ The lab-leak debate is getting personal among experts investigating the origins of COVID-19

http://bit.ly/3zmhCxk

♦ America shut down in response to COVID. Would we ever do it again?

http://bit.ly/3TTUfVe

♦ If we knew then what we know now about COVID, what would we have done differently?

https://on.wsj.com/3ZnRAnO

♦ WHO calls on China to share data on raccoon dog link to pandemic.

http://bit.ly/3G2LwKF

♦ The truth about long COVID is finally emerging. It’s not what we thought

http://bit.ly/3lO84bf

Answers to February 2023

Crossword Puzzle

o you have news about yourself, a colleague, or a student?

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Honored: Wayne D. Rosamond, PhD, professor of epidemiology at the UNC Gillings School of Global Public Health, has been named the 2023 recipient of the American Heart Association’s (AHA) EPI Mentoring Award. The award highlights the importance of superior mentoring in cardiovascular epidemiologic research by honoring a person who has provided exceptional individual and institutional mentoring and advocacy for cardiovascular epidemiology researchers.

Appointed: Karina L. Walters, Ph.D., M.S.W., enrolled member of the Choctaw Nation of Oklahoma, has been appointed director of the NIH Tribal Health Research Office (THRO). Dr. Walters’ wealth of experience and deep commitment to engaging tribal leadership in health research efforts makes her ideally suited for the position. Her commitment to community-based participatory research is evident in her demonstrated ability to sustain collaborations with diverse Native communities and conduct successful randomized clinical trials in tribal communities. She succeeds David R. Wilson, Ph.D., who is on assignment to the White House Council on Native American Affairs.

Honored: Kristen Bibbins-Domingo, M.D. has been named to the STATUS List for the second year in a row. As the editor in chief of JAMA, she became the first person of color to lead the prestigious medical journal and its network of publications. She is also the former chair of the U.S. Preventive Services Task Force. Her contributions to advancing cardiac science through population studies earned Bibbins-Domingo, who is trained in epidemiology and is a member of the National Academy of Medicine, the American Heart Association’s 2022 Population Research Prize.

Honored: Albert Ascherio, M.D., has been named to the STATUS List for 2023. He began his career as a young doctor treating tropical diseases in South American rainforests and parts of Africa. Over the next quarter-century, he made his way to what is now his wheelhouse: studying the links between viruses and neurodegenerative diseases. Perhaps none of his projects have generated as much attention as his 2022 paper, which offered strong evidence, through a 20-year study of more than 10 million people, that infection with the Epstein-Barr virus, most commonly known for causing mononucleosis, increased the likelihood of developing MS by more than 32-fold.

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Honored: Ashish Jha, MD, MPH the White House coronavirus coordinator and Brown School of Public Health dean (on leave), has been honored with a place on the 2023 STATUS List. In March 2022, He signed on to help the White House manage its pandemic response at a time when fast-spreading variants continued to pose a major public health threat even as many Americans moved away from restrictions. In Washington, Jha has focused on promoting Covid-19 countermeasures such as bivalent booster shots, free at-home tests, and free masks for use in crowded public settings.

Honored: Harvard epidemiology professor, John Marc Lipsitch DPhil, was named to the STATUS List for 2023. When Lipsitch observed the government’s lackluster pandemic response back in spring 2020, the Harvard epidemiologist helped fill the void by providing timely, accurate information to the public via social media and news outlets. Since then, Lipsitch has become one of the most trusted voices in the U.S. on Covid-19. Last year, he took the helm as inaugural director of science at the CDC’s new Center for Forecasting and Outbreak Analytics, which has been likened to the National Weather Service, but for infectious diseases.

Honored: UCLA epidemiologist Anne Rimoin PhD, MPH, was named to the STATUS List for 2023. Rimoin has spent two decades studying emerging infections in Central Africa, and has long advocated for surveillance systems that allow for their rapid identification and control. Last year, when mpox began to sweep the globe, Rimoin was an early, authoritative voice calling on public health officials to take the threat seriously. Although the threat of mpox has since waned, she urges continued vigilance against infections with the potential for global spread, including mpox.

Elected: Epidemiologist and biostatistician Maria Cervania, MPH was elected to serve in the North Carolina legislature. She is one of the first two AsianAmerican women to serve in that body and the first Filipino elected to serve in any elected government office in North Carolina. Her new position follows 20 years of work in public health.

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Named: Jennie H. Kwon, DO, an assistant professor of medicine in the Division of Infectious Diseases at Washington University School of Medicine in St. Louis, has been named head of the Society of Healthcare Epidemiologists of America Research Committee. Kwon’s clinical and translational research is dedicated to infection prevention and combating antimicrobial resistance.

Passed: Dr. Mark A. Belsey died peacefully at home in Brooklyn Heights on March 2, surrounded by his family. In 1965 he was the Director of Emergency, Immunization and Epidemiologic Surveillance following Hurricane Betsy in New Orleans. He taught epidemiology and pediatrics at Tulane and saw patients at Charity Hospital while pursuing research at the International Center for Medical Research and Training in Cali, Colombia. He joined the World Health Organization in 1972, and moved his young family to Geneva, Switzerland. In 1982 he was named Chief Medical Officer and Head of Maternal and Child Health and Family Planning at the WHO. His 2005 book for the United Nations, "AIDS and the Family" focused on the repercussions of HIV/AIDS on families in Sub-Saharan Africa. http://bit.ly/3G1j7Vp

Passed: Corleen Jane Thompson PhD, 78, of Wilmington, NC died on February 26, 2023. She received her PhD in Epidemiology from UNC Chapel Hill after working in medical research for many years. Corleen pursued the field of Epidemiology in Georgia and resided in Albany, GA.

Near Term Epidemiology Event Calendar

Every December The Epidemiology Monitor dedicates that issue to a calendar of events for the upcoming year. However that often means we don't have full information for events later in the upcoming year. Thus an online copy exists on our website that is updated regularly. To view the full year please go to: http://www.epimonitor.net/Events The events that we are aware of for the next month follow below.

April 2023

April 3-5

https://bit.ly/3G1mAn4

Short Course: Mendelian Randomisation / Erasmus MC / Rotterdam, The Netherlands

April 3-6

https://bit.ly/3HFdFJd

Conference: 2023 World Vaccine Congress / Multiple / Washington, DC

April 12-14

https://bit.ly/3BHaIUI

Conference: SHEA (Society for Healthcare Epidemiology of America) Spring 2022 / SHEA / Seattle, WA

April 12-15

https://bit.ly/3FyWK8A

Conference: 2022 Annual Conference - Population Association of America / PAA / New Orleans, LA

April 14-16

https://bit.ly/3jcYIUJ

Conference: CUGH 14th Annual Global Health Conference / Consortium of Universities for Global Health / Washington, DC

April 14-19

https://bit.ly/3YwS7o2

Conference: 2023 Annual Meeting American Assn for Cancer Research / AACR / Orlando, FL

April 19-21

https://bit.ly/3PBPOfq

Short Course: Advanced Analysis of Prognosis Studies / Erasmus MC / Rotterdam, The Netherlands

April 24-26

https://bit.ly/2C4g1PE

Short Course: Quality of Life Measurement / Erasmus MC / Rotterdam, The Netherlands

April 24-27

https://bit.ly/3oLZ2Kz

Conference: NACCHO Preparedness Summit 2023 / Multiple / Atlanta, GA

April 24-27

http://bit.ly/38nmB26

Conference: 71st Annual Epidemic Intelligence Service Conference / CDC / Atlanta, GA

April 30

May 2

https://bit.ly/3rX33gV

Conference: Health Effects International 2023 Conference / HEI / Boston, MA

May 2023

May 2-6

https://bit.ly/3V8D7dd

Conference: 17th World Congress on Public Health / World Federation of Public Health Associations / Rome, Italy

May 4-5

https://mpemeeting.org

Conference: 6th International Molecular Pathological Epidemiology (MPE) Meeting / Multiple / Buffalo, NY

May 8-11

https://bit.ly/3i12eBq

Conference: 2023 USPHS Scientific & Training Symposium / PHS Commissioned Officers Foundation / Tulsa, OK

May 8-26

http://bit.ly/41tEDLt

Short Course: Modeling Food Safety and Animal Health Risks Using R / Epix Analytics / Online

May 9-12

http://bit.ly/2DXzS3d

Conference: INTEREST 2023 / IeDE (Intl Epi Databases to Evaluate AIDS / Maputo, Mozambique

May 10-12

https://bit.ly/3s6nOXC

Short Course: Epigenetic Epidemiology / University of Bristol / Virtual

May 15-17

http://bit.ly/33YKQQx

Short Course: Cardiovascular Epidemiology / Erasmus MC / Rotterdam, The Netherlands

May 15 – June 1

http://bit.ly/2P1VUrR

Summer Program: Summer Public Health Institute / University of Minnesota / Minneapolis, MN

May 16-18

https://bit.ly/3Fz1F9t

Conference: 2023 ACHI National Conference / Association for Community Health Improvement / Minneapolis, MN

May 16-18

https://bit.ly/3YKIyCr

Conference: National Violent Death Reporting System Conference / CDC & American Public Health Association / Milwaukee, WI

May 18-19

https://bit.ly/3s2pyBi

Short Course: Advanced Epigenetic Epidemiology / University of Bristol / Virtual

May 18-19

https://bit.ly/3jfwGrL

Conference: World Conference on Public Health and Epidemiology / Eurasia Conferences / Barcelona, Spain

May 21-24

https://bit.ly/3FBbwf3

Conference: 44th Annual Meeting / Society for Clinical Trials / Baltimore, MD

May 21-30

https://bit.ly/321Yo2B

Conference: 76th World Health Assembly / WHO / Geneva, Switzerland

May 22-26

https://bit.ly/3YwW6kG

Short Course: Missing Values in Clinical Research / Erasmus MC / Rotterdam, The Netherlands

May 30- June 1

https://bit.ly/3IO7yAC

Short Course: Child Psychiatric Epidemiology / Erasmus MC / Rotterdam, The Netherlands

May 30 – June 10

https://bit.ly/3J09R3I

Short Course: Principles in Causal Inference / Erasmus MC / Rotterdam, The Netherlands

May 31 – June 1

https://bit.ly/3Gs79Vv

Conference: 2022 Annual Conference / Society for Prevention Research / Seattle, WA

May TBA

https://bit.ly/3hx0Rdx

Conference: Brain Tumor Epidemiology Consortium Conference / BTEC / Lexington, KY

K12 Career Development Opportunity

The UCSF-Kaiser Permanente Urological Epidemiology Research Career Development Program (UCSFKPNC UroEpi) is seeking a highly qualified, motivated MD, PhD, or comparable doctoral degree in early faculty or final year post-doctoral positions. The UroEpi Program seeks to :

► Recruit individuals committed to becoming an independent clinical researcher in the epidemiology of benign urological conditions at Kaiser.

► Develop Scholars’ proficiency in epidemiology, research field methods, research ethics, leadership, manuscript preparation, and grantsmanship

► Individualize each scholar’s career development plan according to his or her background and future career goals.

The awardee will devote at least 50-75% effort to conducting research on non-cancerous urologic conditions and research career development. Other research and clinical activities will be identified to support a 100% position.

For more information, please contact:

Stephen K. Van Den Eeden, PhD at Stephen.Vandeneeden@kp.org

Assistant Professor Population Health & Big Data

The Department of Otolaryngology - Head and Neck Surgery at the University of Mississippi Medical Center is recruiting a position at the Assistant Professor level with a focus in population health and big data. We invite applications from candidates with strengths in epidemiology, big data (e.g. EMR data), health econometrics, machine learning, data science, and biostatistics. The successful candidate will be expected to develop an independent program of research as well as actively collaborate and provide statistical expertise to faculty and residents within the Department. The successful candidate will have the opportunity to participate in teaching activities.

The applicant should have experience analyzing population health data using statistical software such as SAS, Stata, TreeAge or R.

Minimum Qualifications:

 PhD in data science area, epidemiology, population health, or related discipline

 Recognition or promise of outstanding contributions as a scholar

Preferred Qualifications:

 Must have advanced skills in computer programming and data management with software such as SAS, Stata, R, Hadoop, and TreeAge

 Experience working with complex datasets (e.g. NHANES)

 Plan and conduct independent research; write and publish peer-reviewed manuscripts

UMMC is located in the heart of Jackson, the capital of Mississippi. This modern city, containing many historic buildings and sites, is home to a diverse dining, shopping and entertainment scene. The community includes recreational lakes, trails and other outdoor activities. Home to 500,000 residents, metropolitan Jackson boasts affordable living with a warm, welcoming southern culture.

Interested applicants should email their CV with a note of interest to ent@umc.edu

Environmental Health Perspectives (EHP), a monthly journal of environmental health research and news published with support from the National Institute of Environmental Health Sciences (NIEHS), will be accepting applications for a new Science Editor with experience in environmental epidemiology or related fields. This candidate will evaluate manuscripts focused on human observational studies, actively participate in developing and implementing journal policies. As a key ambassador to the environmental epidemiology community, this individual will encourage both established and early-career researchers to submit high-quality scholarly contributions that are within EHP’s scope

About the Role:

The Science Editor will serve as a science advisor to the Editor-in-Chief (EIC), and will work closely with a team of Science Editors, Deputy Editors, and Associate Editors, who are recognized experts in the core environmental health disciplines, including human physiology and disease, exposure science, epidemiology, toxicology, and environmental health.

Operating at a high level of responsibility and independence, EHP Science Editors interface with journal contributors and stakeholders, including scientists, physicians, policy makers, representatives from all levels of government, nongovernmental organization members, environmental health advocates, industry representatives, and the general public.

For detailed information about the position & application: https://bit.ly/3Knhnbi

Research Assistant Professor

Epidemiology

Tulane University School of Public Health and Tropical Medicine is seeking applications for a non-tenure track, fulltime position at the rank of Research Assistant Professor in the Department of Epidemiology. Candidates with a doctoral degree in epidemiology, community health, clinical research or implementation research or a MD with a master’s degree in epidemiology or clinical research will be considered. The faculty member will actively participate in research grant applications, management of on-going and new research studies, and preparation of manuscripts and presentations. The candidate should have excellent communication and interpersonal skills to work with community partners.

Review of applications will begin as soon as possible and applications will be accepted and reviewed until the position is filled. Applicants should send a cover letter with name of at least three references and complete resume to:

Jiang He, MD, PhD

Tulane University School of Public Health and Tropical Medicine

1440 Canal Street, Suite 2000

Mail Box 8318

New Orleans, LA 70112

E-mail Address: jhe@tulane.edu

All applicants should also apply electronically via the following link: https://apply.interfolio.com/73392

Asst / Assoc / Full Professor

Infectious Disease Epidemiology

The Department of Epidemiology at the Tulane University School of Public Health and Tropical Medicine is seeking applications for tenure-track faculty positions in the field of Infectious Disease Epidemiology. The Department has a long -standing collaboration with local clinics and the School of Medicine as well as the State Office of Public Health and can provide research opportunities both domestically and internationally. The qualifications for Assistant Professor include a doctoral degree in epidemiology or MD with epidemiology training, post-doctoral experience in studies related to the epidemiology of infectious diseases, demonstrated potential to establish independent research programs, evidence of excellence in teaching, and interest in collaborative research. Qualifications for Associate/Full Professor candidates include significant contributions to published research, continued external research funding, and professional distinction in teaching, mentoring, and service

Review of applications will begin as soon as possible, and applications will be accepted and reviewed until the positions are filled. Applicants should send a cover letter, complete resume, and at least three letters of recommendation to:

Jiang He, MD, PhD

Tulane University School of Public Health and Tropical Medicine

1440 Canal Street, Suite 2000

Mail Box 8318

New Orleans, LA 70112

E-mail Address: jhe@tulane.edu

All applicants should also apply electronically via the following link: https://apply.interfolio.com/87766

PostDoctoral Fellow - Digital Health & Health Disparities

We are seeking one full-time postdoctoral fellow to join the Digital Health & Health Disparities Research Lab. The lab is housed in the Population and Community Health Sciences Branch of the Intramural Research Program at the National Institute on Minority Health and Health Disparities, National Institutes of Health. The mission of the lab is to leverage digital technologies for health promotion and disease prevention among minorities and health disparity populations. The main focus is on the design and evaluation of just-in-time adaptive interventions via the collection of real-time ecological momentary assessments and physiological smartphone sensor and wearables data.

Candidates must have completed a PhD in social or behavioral science, biostatistics, epidemiology, or a closely related field and have no more than five years of relevant research experience since receipt of their most recent doctoral degree. Candidates must have expertise or an interest in developing expertise in health disparities and digital health.

Expertise in quantitative research methods and advanced statistical analysis is a must. Expertise in natural language processing, machine learning, and Geographic Information Systems (GIS) is highly desirable.

The fellow will assist with study design and implementation, data analysis, and publication of study findings. In addition, the fellow will work on secondary data projects. The postdoctoral fellow will develop his/her own research questions related to digital health and health disparities.

Fellows receive multidisciplinary training and mentorship at NIH. They also receive support in developing a K-series or similar grant proposal during their fellowship. They can also apply for internal funding mechanisms. They are encouraged to participate in grant writing courses and trainings. Postdoctoral fellows can participate in journal clubs, in-person speaker series, and webinar series. Travel funds will be available to travel to 2 conferences a year to present their research and network.

Employer name: National Institute on Minority Health and Health Disparities

Position location: Bethesda, Maryland.

Salary: Commensurate with experience.

Duration: This is a fulltime 2 to 3-year appointment with year-to-year renewal up to five years based on satisfactory performance and availability of funds. Eligible U.S. citizens and permanent residents who have recently received a doctoral degree can come to the NIH as Postdoctoral IRTAs (Intramural Research Training Awardees) to complete up to five years of postdoctoral research. Eligible international scholars who are recent doctoral degree recipients can conduct up to five years of postdoctoral research at the NIH as Visiting Fellows; they generally come to the NIH on J1 visas. Both groups are considered NIH trainees, rather than employees. See https://www.training.nih.gov/programs

Instructions: Applicants should submit: (1) a curriculum vitae, (2) a two-page synopsis of their research interest, including a brief description of their career plans related to digital health and health disparities, (3) three representative publications or working papers, and (4) three letters of recommendation.

Email applications to Sherine Eltoukhy sherine.el-toukhy@nih.gov with subject line: Last name, First name, Postdoc application.

Position available for immediate hire. Applications will be accepted and screened on a rolling basis until the position is filled.

Women and minorities are strongly encouraged to apply. The NIH is dedicated to building a diverse community in its training and employment programs.

The Epidemiology Monitor ISSN (2833-1710) is published monthly Editorial Contributors

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