Prediction of severe COVID-19 cases requiring intensive care in Osaka, Japan

Abstract

Background: To avoid exhaustion of medical resources by COVID-19 care, policy-makers must predict care needs, specifically estimating the proportion of severe cases likely to require intensive care. In Osaka prefecture, Japan, the number of these severe cases exceeded the capacity of ICU units prepared for COVID-19 from mid-April, 2021. Objective: This study used a statistical model to elucidate dynamics of severe cases in Osaka and validated the model through prospective testing. Methods: The study extended from April 3, 2020 through April 26, 2021 in Osaka prefecture, Japan prefecture. We regressed the number of severe cases on the number of severe cases the day prior and the newly onset patients of more than 21 days prior. Results: We selected the number of severe cases the day prior and the number of newly onset patients on 21 and 28 days prior as explanatory variables for explaining the number of severe cases based on the adjusted determinant coefficient. The adjusted coefficient of determination was greater than 0.995 and indicated good fit. Prospective out of sample three-week prediction forecast the peak date precisely, but the level was not t. Discussion and Conclusion: A reason for the gap in the prospective prediction might be the emergence of variant strains.