SUPPLEMENT - Systems Analysis of Social Pathways of Epidemics to Reduce Health Disparities
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20142023Known Financial Commitments (USD)
$381,948Funder
National Institutes of Health (NIH)Principal Investigator
ANIL VULLIKANTIResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF VIRGINIAResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
Data Management and Data Sharing
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
SummaryThis application is in response to the urgent need to understand the epidemiological and economicimpact 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 andcommunity level activities and mobility, for which it is essential to have a high resolution agentbased 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 andsocial interactions among individuals. A large number of novel data sources will be integratedto calibrate the model and to infer the parameters. Due to unobservable parameters such asthe 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 highperformance computing resources. The calibrated model will be used to simulate di erent kinds of counterfactual scenarios thatwould 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 andantivirals. Sensitivity analysis on compliance and duration of social distancing, transmissibility,epidemic severity, and ecacies will be performed. Novel interventions such as \pulsing' of theeconomy i.e. odd/even day closure or alternative week closure will be simulated. The workforcedisruptions 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 NationalProduct. Various epidemic and economic outcome metrics will be compared across scenarios andtrade-o s between outcomes will be measured and explained. Epidemic outcomes will be measuredin terms of morbidity, mortality, time to peak and peak infections whereas economic outcomes willbe 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 overallmacroeconomic impact.