Unveiling the Underlying Severity of Multiple Pandemic Indicators

Abstract

Background: Multiple interconnected key metrics are frequently available to track the pandemic progression. One of the difficulties health planners face is determining which provides the best description of the status of the health challenge (...) Methods: The aim of this study is to capture the information provided by multiple pandemic magnitudes in a single metric. Drawing on official Spanish data, we apply techniques of dimension reduction of time series to construct a synthetic pandemic indicator that, based on the multivariate information, captures the evolution of disease severity over time. Three metrics of the evolution of the COVID-19 pandemic are used to construct the composite severity indicator: the daily hospitalizations, ICU admissions and deaths attributable to the coronavirus. The time-varying relationship between the severity indicator and the number of positive cases is investigated (...)