Modeling and Simulation to Support Public Health Outbreaks and Decision Making: Lessons Learned and Future Work

Following the 2001 bioterrorism attacks with anthrax, the U.S. government focused on becoming better prepared for chemical, biological, radiological, and nuclear threats. Part of that process was the use of modeling and simulation to support public health planning and decision making. Responding to the 2009 H1N1 influenza pandemic was challenging due to the lack of rapid detection assays, case reporting, and hospitalization data. We dodged a bullet as the clinical severity of the H1N1 pandemic was relatively low. The COVID-19 pandemic was drastically different, but the availability of rapid diagnostic tests and the unprecedented availability of case data down to the county level allowed modelers to explore the characteristics of the virus and to predict the future cases, hospitalizations, and deaths. We review how modeling and simulation has changed with respect to supporting public health since the anthrax attacks to identify lessons learned as we try to improve our methods and approaches for future public health emergencies.

Keywords:Modeling and simulation; medical countermeasures; public health; preparedness planning; public health response; lessons learned

Abbreviations:MS: Modeling and Simulation; USPS: United States Postal Service; PEP: Post-Exposure Prophylaxis; MCMs: Medical Countermeasures; CBRN: Chemical, Biological, Radiological, Nuclear; HHS: Health and Human Services; PHEMCE: Public Health Emergency Medical Countermeasures Enterprise; ICU: Intensive Care Unit; PODs: Points of Dispensing; DOD: Department of Defense; WHO: World Health Organization; COVID-19: Coronavirus disease; AI: Artificial Intelligence; CDC: Centers for Disease Control and Prevention; FDA: Food and Drug Administration; SLTT: State, Local, Tribal, Territorial; ASTHO: Association of State and Territorial Health Officials; NACCHO: National Association of County and City Health Officials; CSTE: Council of State and Territorial Epidemiologists