RAPID: RETrofitting REsiliency AgainsT COVID-19! (RETREAT COVID-19!)

  • Funded by National Science Foundation (NSF)
  • Total publications:0 publications

Grant number: 2029158

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $149,951
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Yury Dvorkin
  • Research Location

    United States of America
  • Lead Research Institution

    New York University
  • Research Priority Alignment

    N/A
  • Research Category

    Secondary impacts of disease, response & control measures

  • Research Subcategory

    Economic impacts

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Engineering - In densely populated urban environments, such physical infrastructure systems as gas, electric power and water networks are critical enablers of shelter-at-home policies that help slow down the spread of the COVID-19 outbreak. However, from the infrastructure viewpoint, these policies cause a major shift of gas, electricity and water consumption to residential rather than commercial neighborhoods, which may face unusual demand profiles for infrastructure services, possibly leading to outages and inability (or limited ability) to serve sheltered population groups. Such outages take societally unacceptable death tolls, even without factoring in the effect of the COVID-19 outbreak. For example, only among medically insured Americans, the estimated number of electricity-dependent persons residing at home was 685,000 (2012), among whom roughly one fifth is vulnerable to even short 3-4 hour power outages. The main goal of this proposal is to analyze infrastructure operations under different scenarios of disease outbreaks, using real-life infrastructure and public health data from New York City, and inform infrastructure operators and urban planners on efficient strategies to mitigate public health risks. In these analyses, the project team will specially focus on needs of vulnerable population groups.

The main technical objective of this proposal is to bridge the current gap between infrastructure and epidemic models to understand how the demand of infrastructure services change under different outbreak scenarios. To this end, we will first internalize the effects of health epidemics in infrastructure models. The epidemics model will include Susceptible-Infectious-Susceptible (SIS) and Susceptible-Infectious-Recovered (SIR) models, which make it possible to reasonably simulate the spread of infectious diseases as flu and influenza (SIS) and measles, mumps, rubella (SIR). Second, using real-life data on the COVID-19 outbreak in NYC and models of gas, electricity, transportation and water systems, our research team will carry out an infrastructure vulnerability analysis under different outbreak scenarios, which will be appropriately designed to represent potential trajectories of the COVID-19 outbreak (e.g. "bell" shape, when the outbreak peaks and then gradually decays or the "W" shape, when the outbreak can have multiple peaks). We will develop outage models of critical infrastructure equipment (water pumps, gas compressors, electric power transformers) in order to adequately capture accelerated wear-and-tear of these resources due to the atypical and shifted usage during the outbreaks.

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.