This article examines the main factors affecting COVID-19 lethality across 16 European Countries with a focus on the role of health system characteristics during the first phase of the diffusion of the virus. Specifically, we investigate the leading causes of lethality at 10, 20, 30, 40 days in the first hit of the pandemic. Using a random forest regression (ML), with lethality as outcome variable, we show that the percentage of people older than 65 years (with two or more chronic diseases) is the main predictor variable of lethality by COVID-19, followed by the number of hospital intensive care unit beds, investments in healthcare spending compared to GDP, number of nurses and doctors. Moreover, the variable of general practitioners has little but significant predicting quality. These findings contribute to provide evidence for the prediction of lethality caused by COVID-19 in Europe and open the discussion on health policy and management of health care and ICU beds during a severe epidemic.
【저자키워드】 Health policy, Health care economics, 【초록키워드】 COVID-19, Europe, pandemic, intensive care, hospital, outcome, virus, ICU, Epidemic, Health, Characteristics, management, healthcare, health system, Care, Evidence, Nurse, Chronic diseases, Older, Factor, random, diffusion, Practitioner, GDP, European, caused, contribute, cause, affecting, 【제목키워드】 pandemic, Characteristics, health system, European, affecting,