# SUPPLEMENT - Systems Analysis of Social Pathways of Epidemics to Reduce Health Disparities

> **NIH NIH R01** · UNIVERSITY OF VIRGINIA · 2020 · $381,948

## Abstract

Summary
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.

## Key facts

- **NIH application ID:** 10159587
- **Project number:** 3R01GM109718-07S1
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Achla Marathe
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $381,948
- **Award type:** 3
- **Project period:** 2014-08-15 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10159587

## Citation

> US National Institutes of Health, RePORTER application 10159587, SUPPLEMENT - Systems Analysis of Social Pathways of Epidemics to Reduce Health Disparities (3R01GM109718-07S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10159587. Licensed CC0.

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