Face mask wearing rate predicts country's COVID-19 death rates

Miyazawa, D.; Kaneko, G.

Identification of biomedical and socioeconomic predictors for the number of deaths by COVID-19 among countries will lead to the development of effective intervention. While previous multiple regression studies have identified several predictors for the number of COVID-19-related deaths, little is known for the association with mask non-wearing rate possibly because the data is available for limited number of countries, which constricts the application of traditional multiple regression approach to screen a large number of potential predictors. In this study, we used the hypothesis-driven regression approach to test the association with limited number of predictors based on the hypothesis that the mask non-wearing rate can predict the number of deaths to a large extent together with age and BMI, other relatively independent risk factors for hospitalized patients of COVID-19. The mask non-wearing rate, percentage of age [≥] 80 (male), and male BMI showed Spearman's correlations up to about 0.8, 0.7, and 0.6, respectively, with the numbers of deaths per million in 22 countries from mid-March to mid-June, 2020. The observed numbers of deaths per million were significantly correlated with those predicted by the lasso regression model including four predictors, age [≥] 80 (male), male BMI, and mask non-wearing rates from mid-March and late April to early May (Pearson's coefficient = 0.919). The multiple linear regression models including the mask non-wearing rates, age, and obesity-related predictors explained up to 75% variation of the number of deaths per million in the 22 countries with little concerns about multicollinearity. Furthermore, linear regressions using the mask non-wearing rate in mid-March as the sole predictor still explained up to 72% of the variation of the numbers of deaths from March to mid-June, emphasizing the importance of the strongest predictor. Although further verification is needed to identify causes of the national differences in COVID-19 mortality rates, these findings highlight the importance of the mask, age, and BMI in predicting the COVID-19-related deaths, providing a useful strategy for future regression analyses that attempt to contribute to the mechanistic understanding of COVID-19.