Identification of COVID-19 Waves: Considerations for Research and Policy

Abstract

The identification of COVID-19 waves is a matter of the utmost importance, both for research and decision making. This study uses COVID-19 information from the 52 municipalities of the Metropolitan Region, Chile, and presents a quantitative method—based on weekly accumulated incidence rates—to define COVID-19 waves. We explore three different criteria to define the duration of a wave, and performed a sensitivity analysis using multivariate linear models to show their commonalities and differences. The results show that, compared to a benchmark definition (a 100-day wave), the estimations using longer periods of study are worse in terms of the model’s overall fit (adjusted R2). The article shows that defining a COVID-19 wave is not necessarily simple, and has consequences when performing data analysis. The results highlight the need to adopt well-defined and well-justified definitions for COVID-19 waves, since these methodological choices can have an impact in research and policy making.