Award Abstract #2030509

RAPID: The effect of contact network structure on the spread of COVID-19: balancing disease mitigation and socioeconomic well-being

NSF Directorate:
BIO - Directorate for Biological Sciences
NSF Division:

Division of Environmental Biology

Initial Amendment Date:

Latest Amendment Date:

Award Number:

2030509

Award Instrument:

Grant

Program Manager:

Katharina Dittmar

Start Date:

End Date:

Awarded Amount to Date:

$199,136.00

Investigator(s):

Meggan E Craft [email protected] (Principal Investigator)
Eva Enns (Co-Principal Investigator)
Matthew J Michalska-Smith (Co-Principal Investigator)

Sponsor:

University of Minnesota-Twin Cities
200 OAK ST SE # 224
MINNEAPOLIS MN 554552009

NSF Program:
Ecology of Infectious Diseases
COVID-19 Research
Program Reference Code(s):
096Z
7914
Program Element Code(s):
158Y
Abstract:

What makes COVID-19 spread rapidly in some places, yet slowly in others? How should society lessen social distancing while limiting an increase in infections? To answer these questions, this Rapid Response Research (RAPID) project seeks to understand how patterns of interpersonal interaction (“structure”) in social contact networks affect disease spread in a population. The researchers will simulate a disease spreading through a variety of social contact networks, and use machine learning to relate each network’s structure to the number and timing of new infections. By limiting structures related to increased disease, societies may be able to reopen other parts of their economies while still curbing overall disease spread. The researchers will produce an interactive web application for the public and decision-makers to visualize trade-offs between reducing disease and maintaining social cohesion. This research will support the professional development of an early career scientist.

This research aims to determine the inherent risk of SARS-CoV-2 spread based on contact network structure. The researchers will use machine learning to 1) identify network structures that influence disease spread and 2) predict disease spread on empirical contact networks. Important network structures will serve as targets for simulated disease mitigation interventions (e.g. reducing structures that increase levels of disease or increasing structures that reduce disease levels). Finally, the researchers will investigate whether future outbreaks of COVID-19 or other diseases could be alleviated through optimizing social contact networks ahead of time. The outcomes of this research will inform and facilitate quick, efficient interventions to reduce the social and economic costs of COVID-19. This research will develop a general framework for relating disease to network structure. Thus, results can be generalized beyond the current pandemic, serving to further our understanding of potential future waves of COVID-19, as well as other directly-transmitted diseases in humans, livestock, and wildlife.

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.