Infusing human behavior into epidemiological models is focus of new NSF-supported research projects
August 15, 2022
The U.S. National Science Foundation is investing more than $7.5 million in new research focused on empowering more reliable prediction of the spread of infectious diseases, the effects of mitigation measures and other critical aspects of national health crises. The funding will support eight interdisciplinary research projects aimed at incorporating the complexities of human behavior into epidemiological models.
The science of epidemiology studies the health of groups of people — including the causes and patterns of infectious disease spread — in populations ranging in size from individual neighborhoods to the entire world. Advanced mathematical models are invaluable predictive tools in epidemiology and are widely used by healthcare professionals, decision-makers and leaders. However, the COVID-19 pandemic revealed that current epidemiological models do not adequately account for the human behavioral, social and economic factors that are key to understanding and mitigating a rapidly changing public health crisis.
“The resiliency and health of every community in the U.S. can be strengthened by leveraging the fundamental power of mathematics to better understand behavioral and social dynamics,” says NSF Assistant Director for Mathematical and Physical Sciences Sean L. Jones. “These new projects are bringing together researchers in a multitude of fields, from mathematical biology to social psychology, to unlock the insights that can provide policymakers and others with the most complete predictive models possible.”
“This bold work is based on a simple but ambitious premise: The consequences of pandemics and other public health emergencies can and should be anticipated in advance,” says NSF Assistant Director for Social, Behavioral and Economic Sciences Kellina Craig-Henderson. “The potential value of this innovative research for every American is recognized not just by NSF but also by our incredible research community who has risen to this difficult but vital challenge.”
The eight NSF-supported research projects, led by the institutions below, are administered through NSF’s Mathematical Biology program:
Behavioral heterogeneity and uncertainty in epidemiological models (Cornell University)
Equilibrium, network formation and infectious-disease spread: bridging the divide between mathematical biology and economics (Duke University)
Human behavior-driven mathematical modeling and forecasting of respiratory disease transmission in urban settings (Columbia University) — co-funded by the U.S. Centers for Disease Control and Prevention’s Center for Forecasting and Outbreak Analytics
Inclusion of challenges from social isolation governed by human behavior through transformative research in epidemiological modeling (University of Kansas)
Integrating traditional survey and digital socio-behavioral data into infectious disease models for long-term forecasting (UCLA)
Mathematical formulations of human behavior change in epidemic models (Virginia Tech)
Modeling dynamic disease-behavior feedbacks for improved epidemic prediction and response (Johns Hopkins University)
Understanding and predicting behavioral responses to epidemic risks and control policies: implications for epidemiological models and policy design (University of Wyoming)
The U.S. National Science Foundation propels the nation forward by advancing fundamental research in all fields of science and engineering. NSF supports research and people by providing facilities, instruments and funding to support their ingenuity and sustain the U.S. as a global leader in research and innovation. With a fiscal year 2023 budget of $9.5 billion, NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and institutions. Each year, NSF receives more than 40,000 competitive proposals and makes about 11,000 new awards. Those awards include support for cooperative research with industry, Arctic and Antarctic research and operations, and U.S. participation in international scientific efforts.
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