About
Biography
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:
- Surveillance of antibiotic resistant and other emerging infectious diseases, including COVID-19
- Development and understanding of collaborative learning health systems
- Innovative uses of electronic health record (EHR) data for diverse health stakeholders
- Actionable, large-scale collection and analysis of unstructured data, so called “big data,” for early warnings of epidemics and infectious disease situational awareness
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.
Interests
Infectious disease epidemiology; public health surveillance; mathematical and computer modeling
Research Areas
Quality Improvement, Infectious Diseases
Publications
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.
Identifying and Validating Pediatric Hospitalizations for MIS-C Through Administrative Data. Pediatrics. 2023; 151:e2022059872.
Impact of the COVID-19 pandemic on hospitalizations of children with neurologic impairment. Journal of hospital medicine (Online). 2023; 18:33-42.
Secondary Impact of the Coronavirus Disease 19 Pandemic on Patients and the Cellular Therapy Healthcare Ecosystem. Transplantation and Cellular Therapy. 2022; 28:737-746.
Testing an Automated Approach to Identify Variation in Outcomes among Children with Type 1 Diabetes across Multiple Sites. Pediatric Quality and Safety. 2022; 7:e602.
From the Blog
Not Just Individuals: Health System Hesitancies Also Increased COVID Risks
David M. Hartley, PhD, MPH, Andrew F. Beck, MD, MPH12/8/2023
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