Real-Time Infectious Disease Modeling to Inform Emergency Public Health Decision Making
Anna Bershteyn1, Hae-Young Kim1, R Scott Braithwaite1
1New York University Grossman School of Medicine, New York, NY, USA;
Abstract:
Infectious disease transmission is a nonlinear process with complex, sometimes unintuitive dynamics. Modeling can transform information about a disease process and its parameters into quantitative projections that help decision makers compare public health response options. However, modelers face methodologic challenges, data challenges, and communication challenges, which are exacerbated under the time constraints of a public health emergency. We review methods, applications, challenges and opportunities for real-time infectious disease modeling during public health emergencies, with examples drawn from the two deadliest pandemics in recent history: HIV/AIDS and coronavirus disease 2019 (COVID-19).
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