(1) Background: to describe the dynamic of the pandemic across 35 European countries over a period of 9 months. (2) Methods: a three-phase time series model was fitted for 35 European countries, predicting deaths based on SARS-CoV-2 incidences. Hierarchical clustering resulted in three clusters of countries. A multiple regression model was developed predicting thresholds for COVID-19 incidences, coupled to death numbers. (3) Results: The model showed strongly connected deaths and incidences during the waves in spring and fall. The corrected case-fatality rates ranged from 2% to 20.7% in the first wave, and from 0.5% to 4.2% in the second wave. If the incidences stay below a threshold, predicted by the regression model ( R 2 = 85.0 % ), COVID-19 related deaths and incidences were not necessarily coupled. The clusters represented different regions in Europe, and the corrected case-fatality rates in each cluster flipped from high to low or vice versa. Severely and less severely affected countries flipped between the first and second wave. (4) Conclusions: COVID-19 incidences and related deaths were uncoupled during the summer but coupled during two waves. Once a country-specific threshold of infections is reached, death numbers will start to rise, allowing health care systems and countries to prepare.
【저자키워드】 COVID-19, SARS-CoV-2, Time series analysis, Multiple regression, corrected case fatality rate, flip effect, death threshold, 【초록키워드】 Europe, pandemic, Infection, Region, Regression model, death, Cluster, second wave, incidence, threshold, First wave, Health care system, hierarchical clustering, COVID-19 incidence, multiple regression model, European, country, European country, predicted, affected, less, reached, ranged, R 2, 【제목키워드】 Comparative, time, Month, Sery,