Although pandemics have threatened human civilization since ancient times, how to predict and prevent them remains a pressing challenge, calling for innovative insights and practices. Pandemics emerge through incidental ‘perfect storms’: molecular changes in pathogens, gradual trends in climate, subtle shifts in ecological interactions among potential hosts, and individual behavioral decisions by people, all colluding to make up the difference between an interesting but rare new variant of a known disease and an existential worldwide crisis. Being able to predict the emergence of pandemic threats, therefore, requires a fully integrated, multidisciplinary approach, able to consider the complexity of these realms across scales of interaction to predict and, ideally, prevent. This workshop is one of four bringing experts from scholarly communities in the social and behavioral sciences, biology, engineering, and computer science together to discuss how to integrate the approaches taken by each community into a more effective, unified science of pandemic prediction. The focus of this workshop is on developing understanding of how human attitudes, social behavior, and the drivers underlying both shape patterns of infectious-disease transmission and efforts at control and eradication. This fundamental understanding in turn will facilitate pandemic prevention and control decisions that leave us better prepared when confronted with future pandemic threats.

The workshop is structured to focus on four topical areas of crucial importance, dealing with cultural transmission, information and communication, equity, and sustainability. The white paper that comes from this workshop will provide important guidance for incorporating insights into the social and behavioral sciences into predictive intelligence and pandemic prevention. It will inform future research investments, institutional capacity-building, and other policy priorities aimed at keeping the US and the world safe from inevitable future pandemics.

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.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
2118926
Program Officer
Joseph Whitmeyer
Project Start
Project End
Budget Start
2021-02-15
Budget End
2022-01-31
Support Year
Fiscal Year
2021
Total Cost
$53,873
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94305