Assessing the utility of COVID-19 case reports as a leading indicator for hospitalization forecasting in the United States.

ABSTRACT: Identifying data streams that can consistently improve the accuracy of epidemiological forecasting models is challenging. Using models designed to predict daily state-level hospital admissions due to COVID-19 in California and Massachusetts, we investigated whether incorporating COVID-19 case data systematically improved forecast accuracy. Additionally, we considered whether using case data aggregated by date of test or by date of report from a surveillance system made a difference to the forecast accuracy. Evaluating forecast accuracy in a test period, after first having selected the best-performing methods in a validation period, we found that overall the difference in accuracy between approaches was small, especially at forecast horizons of less than two weeks. However, forecasts from m

SUBMITTER: Reich NG 

PROVIDER: S-EPMC10029058 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature