摘要：The identification of factors associated to COVID-19 mortality is important to design effective containment measures and safeguard at-risk categories. In the last year, several investigations have tried to ascertain key features to predict the COVID-19 mortality tolls in relation to country-specific dynamics and population structure. Most studies focused on the first wave of the COVID-19 pandemic observed in the first half of 2020. Numerous studies have reported significant associations between COVID-19 mortality and relevant variables, for instance obesity, healthcare system indicators such as hospital beds density, and bacillus Calmette-Guerin immunization. In this work, we investigated the role of ABO/Rh blood groups at three different stages of the pandemic while accounting for demographic, economic, and health system related confounding factors. Using a machine learning approach, we found that the “B+” blood group frequency is an important factor at all stages of the pandemic, confirming previous findings that blood groups are linked to COVID-19 severity and fatal outcome.
