NSF Award
2230119
The global COVID-19 pandemic has revealed how critically the success of public health measures depends on understanding human behavioral responses to both infection risks and policy recommendations. Core mathematical epidemiological models have provided useful insight about pandemic risks, but typically do not account for the wide variety of people’s responses to the risk from the disease and the ways these responses shape ongoing transmission. Behavior affects disease spread: nature affects people, and people affect nature—connecting the natural and human systems in feedback loops that determine the course of outbreaks. The multi-disciplinary research team will bridge disciplines, toolkits, and data to advance knowledge about these feedbacks between human behaviors and infectious disease outcomes. The PIs will extend mathematical epidemiological models by including heterogeneity in behavioral responses to risks and social norms (e.g., mask/vaccines acceptance) involving feedback from both aggregate public health outcomes and the diverse responses from individuals. The models will be informed by data from three countries with unique characteristics representing health risks, public policies, information sources, and government trust: the United States, Norway, and Sweden. Real-world data will be supplemented by data collected in controlled settings—through surveys and behavioral laboratory experiments—to gain a deeper understanding of the individual factors and social processes that shape people’s responses to epidemic risks. The project will improve the abilities of epidemiological models to predict both disease outcomes and the economic impacts of public health regulations or guidelines, enhancing the capacity of public policy-makers to design and evaluate epidemic control measures during future outbreaks.<br/><br/>This project will develop and estimate behavioral reaction functions that can be included in systems of ordinary differential equations (ODEs) that comprise most epi-models, with the goal of better informing policy design during novel epidemics. The PIs will focus on two overarching research questions: Q1 How do people’s behavioral reactions influence the evolution of an infectious disease outbreak through feedbacks on pathogen spread? and Q2 How are people’s behaviors during an outbreak moderated by the pronounced uncertainties and frequent policy changes that are characteristic of novel epidemics? To address these questions, the PIs will: (i) develop a new epidemiological-behavioral system of coupled ODEs, (ii) use observational, survey, and experimental data and methods to estimate people’s reactions to epidemic risks and top-down control policies, (iii) integrate our empirical findings into our new epi-model, and (iv) use their parameterized epi-model to conduct retrospective and prospective policy simulations and comparisons. In addition, the PIs will use observational data from three developed countries that undertook distinct policy approaches to the on-going COVID-19 pandemic: the United States, Norway, and Sweden. Moreover, the PIS will design surveys and behavioral laboratory experiments to gain a deeper understanding of responses to risk in contexts that are similar to novel epidemics. This multi-method approach will provide opportunities to test hypotheses about the mechanisms that underlie associations in the observational data and examine the external validity of the survey and laboratory studies.<br/><br/>This project is jointly funded by the Division of Mathematical Sciences (DMS) in the Directorate of Mathematical and Physical Sciences (MPS) and the Division of Social and Economic Sciences (SES) in the Directorate of Social, Behavioral and Economic Sciences (SBE).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
