This application is in response to the urgent need to understand the epidemiological and economic impact of SARS-CoV-2 in the US. Due to the diverse and complex factors driving this outbreak, understanding the epidemiological and economic impact requires a detailed model of individual and community level activities and mobility, for which it is essential to have a high resolution agent based model (ABM), rather than metapopulation models. This research will build a detailed, age- strati ed, ABM of SARS-CoV-2 which takes into account the heterogeneity in demographics and social interactions among individuals. A large number of novel data sources will be integrated to calibrate the model and to infer the parameters. Due to unobservable parameters such as the asymptomatic rate, and constantly changing behaviors and compliance to social distancing, the calibration, simulation and analysis of such an ABM is very challenging, and require high performance computing resources. The calibrated model will be used to simulate di erent kinds of counterfactual scenarios that would include di erent types of social distancing strategies { school closure, home-isolation, quar- antine of symptomatic and diagnosed cases, liberal leave policy, and low ecacy vaccines and antivirals. Sensitivity analysis on compliance and duration of social distancing, transmissibility, epidemic severity, and ecacies will be performed. Novel interventions such as pulsing of the economy i.e. odd/even day closure or alternative week closure will be simulated. The workforce disruptions due to illness, deaths and prophylactic absenteeism will be used to measure indus- try level inoperability and its cascading e ect on other industries and on the US Gross National Product. Various epidemic and economic outcome metrics will be compared across scenarios and trade-o s between outcomes will be measured and explained. Epidemic outcomes will be measured in terms of morbidity, mortality, time to peak and peak infections whereas economic outcomes will be measured in terms of cost of illness, and cost of prevention due to social distancing directives. Multiple rankings of the scenarios will be provided based on mortality, cost of illness and overall macroeconomic impact.

Public Health Relevance

This research will study the epidemiological and economic impact of COVID-19 in the US under di erent social-distancing scenarios, and evaluate the trade-o s between infections/deaths and the economic costs of the lock down.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM109718-07S1
Application #
10159587
Study Section
Program Officer
Ravichandran, Veerasamy
Project Start
2014-08-15
Project End
2023-03-31
Budget Start
2020-07-01
Budget End
2021-03-31
Support Year
7
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Virginia
Department
Type
University-Wide
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
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