My research work investigates the factors governing the emergence and transmission of infectious diseases by applying mathematical modeling, computer simulation and data analytic approaches. I strive to use team-based, interdisciplinary research to improve child health.
A background in applied physics and mathematics led me to begin using math and computer simulation to better understand the HIV epidemic in the early 1990s. That interest grew into mathematical disease ecology and research on how environmental variables affect the emergence and spread of different infectious diseases. Interest in public health surveillance followed from my study of epidemics.
I also study the spread of ideas and cooperation in learning healthcare systems using mathematical tools like those applied to measuring and modeling epidemics.
My current research projects include:
I have served on numerous review, advisory and expert panels, including a 2003 White House Blue Ribbon Panel charged with addressing the threat of bioterrorism directed against livestock. From 2008 to 2014, I served on a working group for the Department of Homeland Security and National Institutes of Health (DHS-NIH) Research and Policy for Infectious Disease Dynamics (RAPIDD). I have also been elected to senior membership in the Institute of Electrical and Electronics Engineers (IEEE).
PhD: University of Maryland Baltimore County, Baltimore, MD, 1996.
MPH: George Washington University, Washington, DC, 2006.
Infectious disease epidemiology; public health surveillance; mathematical and computer modeling
Engagement as a mechanism of action in collaborative learning health systems. Learning Health Systems. 2025; 9:e10459.
Engraft: A Collaborative Learning Health Network for Enhanced Transplant and Cellular Therapy Outcomes. Transplantation and Cellular Therapy. 2025; 31:123-134.
Ten Simple Rules for Making a Career Transition from Basic Science to Public Health Research. International Journal of Environmental Research and Public Health. 2025; 22:223.
The Test and Protect Program: A Data-Driven, Community-Engaged Approach to COVID-19 Testing Site Localization. Journal of public health management and practice : JPHMP. 2025; 31:61-64.
Integrating a machine learning algorithm to forecast daily asthma hospitalizations. Annals of Epidemiology. 2024; 97:120.
A regional learning health system of congregate care facilities for COVID-19 response. Learning Health Systems. 2024; 8:e10407.
Development of a multimodal geomarker pipeline to assess the impact of social, economic, and environmental factors on pediatric health outcomes. Journal of the American Medical Informatics Association : JAMIA. 2024; 31:1471-1478.
Learning from an equitable, data-informed response to COVID-19: Translating knowledge into future action and preparation. Learning Health Systems. 2024; 8:e10369.
Review and analysis of the overlapping threats of carbapenem and polymyxin resistant E. coli and Klebsiella in Africa. Antimicrobial Resistance and Infection Control. 2023; 12:29.
Epidemiology and Severity of Illness of MIS-C and Kawasaki Disease During the COVID-19 Pandemic. Pediatrics. 2023; 152:e2023062101.
David M. Hartley, PhD, MPH, Andrew F. Beck, MD, MPH12/8/2023