A scenario modeling pipeline for COVID-19 emergency planning

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  • Lemaitre, J.C
    • Other Affiliation: Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • Grantz, K.H
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Kaminsky, J
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Meredith, H.R
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Truelove, S.A
    • Other Affiliation: Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Lauer, S.A
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Keegan, L.T
    • Other Affiliation: Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States
  • Shah, S
  • Wills, J
  • Kaminsky, K
  • Perez-Saez, J
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Lessler, J
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
  • Lee, E.C
    • Other Affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
Abstract
  • Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.
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  • Article
Rights statement
  • In Copyright
License
  • Attribution 4.0 International
Journal title
  • Scientific Reports
Journal volume
  • 11
Journal issue
  • 1
Language
  • English
Version
  • Publisher
Funder
  • 130492
  • Centers for Disease Control and Prevention, CDC: 126280, 5U01CK000538-03
  • Office of Statewide Health Planning and Development, State of California, OSHPD
  • U.S. Department of Health and Human Services, HHS
  • U.S. Department of Homeland Security, DHS
  • 26798
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF: 200021-172578
ISSN
  • 2045-2322
Publisher
  • Nature Research

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