MIDAS Catalog

MIDAS

Created by Arnold Milstein, Johannes Opsahl Ferstad, Joshua Salomon, Alejandro Martinez, Angela Gu, Nigam Shah, Kevin Schulman, Isha Thapa, Raymond Ye Lee, David Scheinker, Andy Shin and Peter Glynn
Description:

This is an interactive, quantitative model that forecasts demand for COVID-19 related hospitalization based on county-level population characteristics, data from the literature on COVID-19, and data from online repositories. The model estimates a time series of demand for intensive care beds and acute care beds as well as the availability of those beds due to COVID-19 using the initial numbers, the doubling time, and the population-specific rates and then compares these to the numbers of relevant beds derived from data from the American Hospital Association. The tool is only designed to project hospitalizations when a small proportion of the overall population has been infected (<20%) and does not account for community immunity. The output of the model can be viewed in a graphic or in a table and is downloadable in a CSV format.

Preview:
https://surfcovid19.shinyapps.io/pop_prod/

During the latest test, the link checker returned HTTP error code 404 for this site. (NA)

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IdentifierURL:https://surfcovid19.shinyapps.io/pop_prod/
Typesoftware
Biological Scalepopulation
Collection End Date
LanguageEnglish
Topics
  • Disease
    • Infectious Disease
      • Vaccine-Preventable Disease
        • COVID-19
      • Viruses Infection
        • Viral Respiratory Tract Infection
          • COVID-19
  • Health System Capacity
  • Host
    • Homo sapiens
  • Modeling
    • Modeling Purpose
      • Forecasting
  • Pathogen
    • Viruses
      • SARS-CoV2
  • Population Count
    • Hospitalization
      • Incident Hospitalization
Geographical ScopeUnited States
Geographical ResolutionCounty, State
Start Date
End Date
Versionunspecified
Accessible For FreeTRUE
Licenseunspecified
Rightsunspecified
HTTP Status Code404
HTTP Checked On2025/09/01