How Many SARS-CoV-2-Infected People Require Hospitalization? Using Random Sample Testing to Better Inform Preparedness Efforts

J Public Health Manag Pract. 2021 May-Jun;27(3):246-250. doi: 10.1097/PHH.0000000000001331.


Context: Existing hospitalization ratios for COVID-19 typically use case counts in the denominator, which problematically underestimates total infections because asymptomatic and mildly infected persons rarely get tested. As a result, surge models that rely on case counts to forecast hospital demand may be inaccurately influencing policy and decision-maker action.

Objective: Based on SARS-CoV-2 prevalence data derived from a statewide random sample (as opposed to relying on reported case counts), we determine the infection-hospitalization ratio (IHR), defined as the percentage of infected individuals who are hospitalized, for various demographic groups in Indiana. Furthermore, for comparison, we show the extent to which case-based hospitalization ratios, compared with the IHR, overestimate the probability of hospitalization by demographic group.

Design: Secondary analysis of statewide prevalence data from Indiana, COVID-19 hospitalization data extracted from a statewide health information exchange, and all reported COVID-19 cases to the state health department.

Setting: State of Indiana as of April 30, 2020.

Main outcome measures: Demographic-stratified IHRs and case-hospitalization ratios.

Results: The overall IHR was 2.1% and varied more by age than by race or sex. Infection-hospitalization ratio estimates ranged from 0.4% for those younger than 40 years to 9.2% for those older than 60 years. Hospitalization rates based on case counts overestimated the IHR by a factor of 10, but this overestimation differed by demographic groups, especially age.

Conclusions: In this first study of the IHR based on population prevalence, our results can improve forecasting models of hospital demand-especially in preparation for the upcoming winter period when an increase in SARS CoV-2 infections is expected.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • COVID-19 / epidemiology*
  • COVID-19 / therapy*
  • Civil Defense / organization & administration*
  • Civil Defense / statistics & numerical data*
  • Female
  • Forecasting
  • Hospitalization / statistics & numerical data*
  • Hospitalization / trends*
  • Humans
  • Indiana / epidemiology
  • Male
  • Middle Aged
  • Population Surveillance*
  • Prevalence
  • SARS-CoV-2
  • Young Adult