Modeling Dynamic Disease-Behavior Feedbacks
The long-term goal of this project is to enhance our ability to understand and predict the complex dynamic interactions between humans and pathogens during disease emergence, dissemination, and control. Our specific aims are to 1) More accurately predict disease spread and health outcomes during an outbreak/ epidemic/pandemic, 2) Enable multi-objective policy design by simultaneously quantifying both the disease burden and economic costs of proposed policies, allowing for the evaluation of both economic and health policies, and 3) Evaluate heterogeneity and equity by quantifying the distributional impacts of disease burden and economic cost across socio-demographic and risk groups. To accomplish these aims we are developing a novel integrated mathematical framework that combines mechanistic models of infectious disease dynamics with economic models of human behavior. This framework is designed to capture behavioral responses to both the epidemic state and policies in place, and the effect of individual-level behavioral responses on the trajectory of the disease within a population. We will deploy the model using COVID-19 as a case study, to illustrate both feasibility and added value. The project team brings together investigators from the Infectious Disease Dynamic group with other JHU faculty specializing in economics and decision science. This project is part of the Incorporating Human Behavior in Epidemiological Models (IHBEM) Program at the National Science Foundation (NSF).