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

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 to forecast hospital demand may be inaccurately influencing policy decision-maker action. Objective: Based SARS-CoV-2 prevalence data derived from statewide random sample (as opposed relying reported counts), we determine infection-hospitalization ratio (IHR), defined as percentage of individuals who are hospitalized, various demographic groups Indiana. Furthermore, comparison, show extent case-based ratios, compared with IHR, overestimate probability by group. Design: Secondary analysis Indiana, extracted health information exchange, all cases state department. Setting: State Indiana April 30, 2020. Main Outcome Measure(s): Demographic-stratified IHRs case-hospitalization ratios. Results: The overall IHR was 2.1% varied more age than race or sex. Infection-hospitalization estimates ranged 0.4% those younger 40 years 9.2% older 60 years. Hospitalization rates based overestimated factor 10, but this overestimation differed groups, especially age. Conclusions: In first study population prevalence, our results can improve forecasting demand—especially preparation upcoming winter period when an increase SARS CoV-2 is expected.