This study investigates the relationship between social norms and the spread of COVID-19. Using global social data and covariates (climate, economic indicators, healthcare access), the researchers applied model-based clustering and random forest regression to identify societal groups and predict COVID-19 doubling time. Four societal groups emerged: reserved, drifting, assertive, and compliant. Compliant societies in dry climates showed the highest doubling times despite higher population densities. Population density, freedom of assembly and association, and agency were key predictors of doubling time, highlighting the importance of social factors in COVID-19 transmission.

Máté Kapitány-Fövény, Mihály Sulyok