Award Abstract #2032536

RAPID: Modeling COVID-19 in the context of optimizing quarantine policy

See grant description on NSF site

Program Manager:

Katharina Dittmar

Active Dates:

Awarded Amount:



Leila Hedayatifar

Yaneer Bar-Yam

Awardee Organization:

New England Complex Systems Institute


Biological Sciences (BIO)


While large scale quarantine has been the most successful short-term policy, it is not efficient over long periods as it exerts economic costs. That is why countries which have been able to partially control the spread of the coronavirus disease are now thinking about policies to reopen businesses. However, healthcare systems strongly warn against reopening too soon. Thus, it is urgent consider a flexible quarantine policy that balanced these demands. The novelty of this work is in suggesting a multi-level quarantine process based on the mobility patterns of individuals and the severity of COVID-19 contagion in different areas. Broader impacts of this research will be recommendation to long-term policies on coronavirus control, which explicitly takes state cooperation into account, as neighboring states are not necessarily disconnected, according to mobility patterns. Additionally, this research will provide professional development opportunities for early career researchers. This research provides a more adaptive isolation and quarantine process based on actual individuals' mobility patterns. Specifically, it advances the state of knowledge regarding 1) how to define the borders of high-risk patches considering the location and movements of confirmed patients, 2) what is the risk of each patch based on the strength of connectivity between these patches, 3) how this information enables policymakers to make better and faster decisions across the scales, and 4) how models can better simulate the epidemic spread within and among societies. Social fragmentation will be analyzed by applying the Louvain method with modularity optimization to the mobility network. In a multi-scale community detection process, high risk areas will be defined. At the smaller scales, for communities with a higher number of confirmed cases the influence of contact tracing and quarantine policies will be considered. A stochastic transmission model will be built to study how the coronavirus spreads in society and how it affects individuals' health. To develop the model, parameters such as incubation time distribution of asymptotic patients, daily test capacity, and the number of mild, hospitalized, ICU hospitalized, recovered, and death cases will be considered.This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.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.

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