MIDAS Catalog

MIDAS

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

This site was available on the date of the last automated link check. (2025/06/16)

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IdentifierURL:https://surfcovid19.shinyapps.io/pop_prod/
Typesoftware
Biological Scalepopulation
Collection End Date
LanguageEnglish
Topics
  • case counts
    • hospital stay dataset
      • incident hospitalization count
  • disease
    • infectious disease
      • COVID-19
  • health system capacity
  • host organism
    • Homo sapiens
  • modeling
    • modeling purpose
      • forecasting
  • pathogen
    • Severe acute respiratory syndrome coronavirus 2
Geographical ScopeUnited States
Geographical ResolutionCounty, State
Start Date
End Date
Versionunspecified
Accessible For FreeTRUE
Licenseunspecified
Rightsunspecified
HTTP Status Code200
HTTP Checked On2025/06/16