Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries

Objective To assess whether the basic reproduction number ( R 0 ) of COVID-19 is different across countries and what national-level demographic, social, environmental factors other than interventions characterize initial vulnerability to virus. Methods We fit logistic growth curves reported daily case numbers, up first epidemic peak, for 58 which 16 explanatory covariates are available. This fitting has been shown robustly estimate from specified period. then use a generalized additive model (GAM) discern both linear nonlinear effects, include 5 random effect account potential differences in testing reporting that can bias estimated . Findings found mean R0 1.70 (S.D. 0.57), with range between 1.10 (Ghana) 3.52 (South Korea). identified four factors—population 20–34 years old (youth), population residing urban agglomerates over 1 million (city), social media organize offline action (social media), GINI income inequality—as having strong relationships , countries. An intermediate level youth inequality associated high (n-shape relationships), while city Pollution, temperature, humidity did not have but were positive. Conclusion Countries characteristics predispose them greater intrinsic COVID-19. Studies aim measure effectiveness locations should these baseline demographic characteristics.