BIOGRAPHICAL SKETCH

A.        Personal Statement

Dr. Ayers is a computational epidemiologist committed to getting the public back in public health. He passively assesses and responds to the public’s health needs by harnessing artificial intelligence, internet search queries, news media, social media, and online networks. Beginning in 2011 he showed electronic cigarettes were the most popular smoking alternative on the market, being the first to predict their rise. This study has been followed by several unique discoveries making public health science more responsive to the public and more effective in the process. For instance, his recent JAMA Internal Medicine report on harnessing AI for answering the public’s healthcare questions was covered in more than 10,000 news outlets, trended on both Facebook and X, ranks among the top 5 most discussed studies ever appearing in JAMA Internal Medicine according to Altmetric, and was the most read article in JAMA Network for 2023. His work has also been trans-disciplinary (e.g., he has published with more than 75 different collaborators from applied mathematics, climatology, communications, computer science, economics, engineering, political science, sociology, and more). Dr. Ayers’ is among the 20 most-cited “computational epidemiologists” and 10 most-cited “digital epidemiologists” (according to Google Scholar). His peer-reviewed articles consistently rank in the top 1% of Altmetric’s research rankings, with coverage in traditional news (e.g., ABC, CBS, NBC, etc.), tech and business news (e.g., Bloomberg, Popular Science, Wired, etc.), and entertainment news (e.g., Dr. Drew, Dr. Oz, Saturday Night Live, etc.). Dr. Ayers never forgot from where he came: a trailer in the backwoods of North Carolina. As a result, he is focused on science that helps people, millions at a time.

B.        Positions and Honors

Positions and Employment

2023-                Deputy Director of Informatics, Altman Clinical and Translational Research Institute

2020-                Senior Scientist, Qualcomm Institute (School of Engineering)

2018-                Vice Chief of Innovation, Division of Infectious Disease & Global Public Health

2018-                Faculty (Infectious Disease & Global Public Health), Department of Medicine, UC San Diego

2016-                Co-Founder, Good Analytics, San Diego, CA

2013-                Faculty (Epidemiology), Graduate School of Public Health SDSU, San Diego, CA

2011-                Founder, Health Watcher, Boston, MA

Honors (selected)

2007         1st Runner Up California State University Research Competition in Behavioral and Social Science (among 23 universities and 417,000 students)

2008        Most Outstanding Graduate, Political Science, SDSU, San Diego, CA

2016        Citation Award for Research Excellence, SDSU Office of the President

2016        Citation Award, Society of Behavioral Medicine

2017        Citation Award for Research Excellence, SDSU Office of the President

2017        Innovator in Regulatory Science, Burroughs Wellcome Fund

C.        Contributions to Science

Informatics 

Dr. Ayers has led a systematic and continuously funded research agenda on novel public health informatics, including some of the earliest studies to use big data in tobacco control, psychiatric epidemiology, obesity prevention, etc.. This agenda has resulted in the discovery of seasonal patterns across nine types of mental illness, the discovery of circaseptan (day of the week) patterns in smoking cessation contemplations and weight loss contemplations, and the first prediction of the rise of electronic cigarettes in 2011. It has concurrently resulted in new approaches to data analytics, including an open-access alternative to Google Flu Trends that yielded more accurate forecasts every week than any other domestic influenza forecasting system with forecasts running live today. He also developed a data mining strategy to quantify the precise health concerns of the public.        

1. Leas EC, Dredze M, Ayers JW. Ignoring data delays our reaction to emerging public health tragedies. JAMA Psychiatry 2020;77:102-03.
2. Ayers JW, Althouse BM, Dredze M. Could behavioral medicine lead the web data revolution? JAMA. 2014;311(14):1399-1400.
3. Nobles AL, Leas EC, Althouse BM,...Ayers JW. Crowddiagnosed: Requests for diagnoses of sexually transmitted disease on a social media platform. JAMA. 2019;322:1712-13.
4. Santillana M, Zhang D, Althouse BM, Ayers JW. What can digital disease detection learn from (an external revision to) Google flu Trends? Am J Prev Med. 2014;47(3):341-347.

Communication

Novel big data has the potential to revolutionize health communication. For instance, awareness campaigns are ubiquitous, but little is known about their potential effectiveness because traditional evaluations are often unfeasible. Dr. Ayers led the development of a novel evaluation framework for assessing awareness campaigns that directly observes how awareness campaigns unfold: a) a message is propagated in news media, b) some of the public then amplifies the message by sharing it on social media, c) this motivates some to seek out additional information related to the message online, such as on Google or Wikipedia, and d) finally some are motivated to act on the message by initiating the targeted behavior change. The result is more work in health communication is based on evaluations and data-driven strategies where the outcomes are efficiently and directly observed using big media data. This work has coincided with several discoveries that identify how the public engages with media and responds to those messages by modifying their health practices.  

1. Ayers JW, Goodman A, Smith D. #MedEd: Medical Education and Knowledge Translation on Social Media. JAMA. 2023;330(10):909-910.
2. Ayers JW, Chu B, Zhu Z, et al. Spread of misinformation about face masks and COVID-19 by automated software on Facebook. JAMA Internal Med. 2021;10.1001/jamainternmed.2021.2498.
3. Broniatowski D, Dredze M, Ayers JW. “First do no harm”: Effective communication about COVID-19 vaccines. Am J Public Health. 2021;10.2105/AJPH.2021.306288.
4. Ayers JW, Caputi TL, Leas EC. The need for federal regulation of marijuana marketing. JAMA. 2019;321:2163-64.

Rapid Response Research

To demonstrate the value of data analytics for a responsive public health Dr. Ayers often responds to emerging events to provide actionable insights, often when no other scientific data are available. Within this theme he has focused on an array of outcomes, including, climate change, gun control, HIV screening and testing, distracted driving, sexual violence, etc. For instance, he described how Pokémon Go was increasing cases of distracted driving and even accidents calling for supply-side regulation for one of the first times in driving safety. The publication of this work in JAMA Internal Medicine, and its surrounding publicity pressured the game’s maker to ultimately restrict play at some driving speeds. These studies often involve collaborations with boots on the ground public health advocates, such as the American Automobile Association, American Cancer Society, OraSure Technologies, Everytown for Gun Safety,  LELO Hex, to name a few.

1. Liu M, Caputi TL, Dredze M, Kesselheim AS, Ayers JW. Internet searches for unproven COVID-19 therapies in the United States. JAMA Intern Med. 2020;180:1116-18.
2. Ayers JW, Althouse BM, Leas EC, Allem JP, Dredze M. Web searches for suicide increase following the release of Netflix’s ‘13 Reasons Why.’ JAMA Intern Med. 2017;177(10)1527-29.
3. Ayers JW, Leas EC, Dredze M, Allem JP, Grabowski JG, Hill L. Pokémon Go: A new distraction for drivers and pedestrians. JAMA Intern Med. 2016;176(12)1865-66.
4. Ayers JW, Althouse BM, Dredze M, Leas EC, Noar SM. The Charlie Sheen effect: News and Internet searches for HIV. JAMA Intern Med. 2016;176(4):552-554.

Artificial Intelligence

Dr. Ayers has published some of the most visible work on AI in healthcare and public health. His work has advocated for rigorous evaluation of AI tools in real world settings. He has also been active in the development of AI-powered tools, including Tobacco Watcher (https://tobaccowatcher.globaltobaccocontrol.org/) that relies on machine learning to automatically evaluate the content of news articles as part of a media analysis engine employed by the alphabet of tobacco control advocacy groups with more than 5,000 monthly-users. He has also been fine tuning large language models for healthcare question and answer services.

1. Ayers JW. Poliak A, Dredze M, et al. Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum. JAMA Intern Med. 2023;183(6):589-596.
2. Ayers JW, Zhu Z, Poliak A, et al. Evaluating Artificial Intelligence Responses to Public Health Questions. JAMA Netw Open. 2023;6(6):e2317517.
3. Ayers JW, Desia N, Smith D. Regulate Artificial Intelligence in Health Care by Prioritizing Patient Outcomes. JAMA. 2024;331(8):639-640.
4. Ayers JW, Dredze M, Smith D. Machine-Made Empathy? Why Medicine Still Needs Humans. JAMA Int Med. 2023;183(11):1279-1280.

Classical Epidemiology

Dr. Ayers is a classically trained epidemiologist. He has published more than 25 reports using traditional data in public health, sociology and political science journals. His expertise in this arena is focused on study design (including observational and experimental data), measurement validity, and statistical methods with emphasis on time series analyses, random effects, and causal inference. His classical work is usually focused on minority or disadvantaged populations, including the first study of American Muslims’ behavior, understanding the role of racism toward Latinos for determining support for public resource allocation, understanding how acculturation affects health, understanding the role of social networks and health (e.g., how the effect of networks is modified by the gender of the ego or the cultural setting of the ego), and assessing the needs of sexual minorities; to name a few. These studies are highly cited in their respective fields and subfields.

5. Chu B, Liu M, Leas EC, Althouse BM, Ayers JW. Effect size reporting among prominent health journals: a case study of odds ratios. BMJ Evidence-Based Medicine. 2020;10.1136/bmjebm-2020-111569. 
6. Caputi TC, Smith D, Ayers JW. Suicide Risk Behaviors Among Gay, Lesbian, Bisexual and Unsure Adolescents in the United States, JAMA. 2017;318(23):2249-51.
7. Caputi TC, Smith LR, Strathdee S, Ayers JW. Substance Use Among Lesbian, Gay, Bisexual, and Questioning Adolescents in the United States, 2015. Am J Public Health. 2018;108:1031-34.  

Complete List Of Published Work:

www.johnwayers.com | https://www.ncbi.nlm.nih.gov/pubmed/?term=ayers+jw%5BAuthor%5D