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-19
  • Start & end year

    2014
    2023
  • Known Financial Commitments (USD)

    $381,948
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    ANIL VULLIKANTI
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF VIRGINIA
  • Research 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.