To clarify the high variability in COVID-19-related deaths during the first wave of the pandemic, we conducted a modeling study using publicly available data.
We used 13 population- and country-specific variables to predict the number of population-standardized COVID-19-related deaths in 43 European countries using generalized linear models: the test-standardized number of SARS-CoV-2-cases, population density, life expectancy, severity of governmental responses, influenza-vaccination coverage in the elderly, vitamin D status, smoking and diabetes prevalence, cardiovascular disease death rate, number of hospital beds, gross domestic product, human development index and percentage of people older than 65 years.
We found that test-standardized number of SARS-CoV-2-cases and flu vaccination coverage in the elderly were the most important predictors, together with vitamin D status, gross domestic product, population density and government response severity explaining roughly two-thirds of the variation in COVID-19 related deaths. The latter variable was positively, but only weakly associated with the outcome, i.e., deaths were higher in countries with more severe government response. Higher flu vaccination coverage and low vitamin D status were associated with more COVID-19 related deaths. Most other predictors appeared to be negligible.
Adequate vitamin D levels are important, while flu-vaccination in the elderly and stronger government response were putative aggravating factors of COVID-19 related deaths. These results may inform protection strategies against future infectious disease outbreaks.