Collaborative Research: Conference on Bridging Disciplinary Divides for Behaviorally Modulated Mathematical Models in Human Epidemiology

Project: Research project

Project Details

Description

This award will support a virtual conference on May 6-7 2021 that will bring together some of the world's leading mathematics, epidemiological, and social science scholars in order to chart a research agenda that enable policy makers to understand how infectious disease, economics, and society shape each other. Infectious diseases alter the United State's economy, society, and culture in complex ways, and these economic and social changes influence the way a pandemic develops. For example, the on-going COVID-19 pandemic is having substantial economic, educational, social, and societal consequences, including changes in work and housing habits, labor markets, and social justice dialogues. Similarly, the HIV epidemic had a major impact on our society in the 1980's, far beyond those immediately impacted by the virus. Mathematical models help make sense of these complex interactions. Constructing models of such complex socio-economic-epidemiological systems requires experts from the constituent fields to work together. The PIs anticipate the research agenda developed in the workshop will facilitate the research communities to discover new mathematical methods and modeling approaches to jointly forecast epidemiological, economic and social patterns so that future pandemics are mitigated with lower social and economic cost.

The conventional approach to the modelling of infectious diseases is to collect basic life-cycle data on the disease, and to overlay that onto structured population data to predict prevalence patterns, health outcomes, using differential equations, networks, agent-based simulations, or another related modelling approaches. These approaches are quite successful at day-ahead prediction, but aside from largely ad hoc parametric adjustments, these standard approaches have almost no ability to connect to behavioral based interventions. These means that the models are not helpful for measuring the benefits and costs (broadly defined) of non-pharmaceutical interventions, which are critical when novel pathogens emerge. There is expert knowledge and modeling work, related to epidemics, in economics and social sciences that can be used to better describe transmission, while providing internally consistent connections to society and the economy. But the disciplinary divides are difficult to bridge. There are limits in data collection, including scale, precision, and representativeness. This difficulty has been amplified by the fast growth of the scholarly literature over the last few years. Bringing together a diverse group of scholars, scientists, and modelers will help everybody interested in the field better understand what has been accomplished so far and produce a research agenda for improving mathematical models in human epidemiology in the future. More information can be found at the conference web site http://the-mathepi-behavior-bridge.site/

This project is jointly funded by the MPS Division of Mathematical Sciences through the Mathematical Biology Program, and the SBE Division of Social and Economic Sciences Sociology Program.

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.

StatusActive
Effective start/end date5/1/214/30/22

Funding

  • National Science Foundation: $28,585.00

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