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Title: Networked epidemiology for COVID-19
Computational epidemiology aims to develop computer models and decision support systems that understand, predict, and control a disease’s spatiotemporal diffusion throughout a population. Researchers can use these models to forecast an epidemic’s future course, allocate scarce resources and assess depletion of current resources, infer disease parameters, and evaluate various interventions. Individual behavior and public policy are critical in understanding and controlling infectious diseases, and computational techniques provide a potentially powerful study tool. The COVID-19 pandemic has had significant social, health, economic, and political ramifications worldwide, and its impact will undoubtedly continue to grow in the coming months. Here we outline an approach to support the COVID-19 response with examples that are rooted in network science and data-driven modeling.
Authors:
; ; ; ; ; ;
Award ID(s):
1917819
Publication Date:
NSF-PAR ID:
10218327
Journal Name:
Siam news
Volume:
53
Issue:
5
Page Range or eLocation-ID:
1-6
ISSN:
1833-069X
Sponsoring Org:
National Science Foundation
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