Risk of hospitalization of diagnosed COVID-19 cases during the pandemic: a time-series analsys to unveil short- and long run dynamics

Abstract

Objectives: With the outbreak of the SARS-CoV-2 pandemic, the unprecedented rise in demand for hospital care brought health Systems worldwide to the brink of collapse. The dynamics of the COVID-19 pandemic have alternated periods of high incidence with others of low incidence, making it difficult to separate short- and long-run relationship between the number of COVID-19 cases diagnosed and the demand for hospital beds. The aim of this study is to model the risk of hospitalization of diagnosed cases during the pandemic.

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Conclusions: Models discriminating between the short- and long-run dynamics provide health planners with a valuable demand forecasting tool which should be useful for developing both structural programs and emergency interventions.