Data Envelopment Analysis Models Connected in Time Series: A Case Study Evaluating COVID-19 Pandemic Management in Some European Countries

ABSTRACT

Efforts of individual countries fighting the COVID-19 pandemic may significantly vary. In this work, we compare the overall efficiency of COVID-19 anti-pandemic management of selected European countries using data envelopment analysis (DEA) models connected in weekly time series for summer 2021. To evaluate the COVID-19 transmission mitigation of the countries, we consider a proportion of fully vaccinated people, relative numbers of hospitalized patients, and a reproductive number as an indicator of the rate of current regional COVID-19 pandemic transmission. All DEA models, including those with variable returns to scale and free disposability hulls, require no assumptions, unlike regression models. By connecting the models in time series, we try to identify countries with the highest long-term efficiencies that may serve as examples for other countries. Of course, the situation is always more complex than the data envelopment models, even if connected in time series, may describe;thus, the results are rather illustrative and propose the aspect of models connection in time series.