Multidimensional drivers of urban infectious diseases: a comparative longitudinal study informing planetary health governance

Urban centers are critical nexuses where climate, environmental exposures, and socioeconomic disparities converge to shape infectious disease dynamics. Addressing the underexploration of these compound drivers, we conducted a comparative longitudinal analysis across three major Chinese cities, integrating multi-dimensional epidemiological, climatic, air quality, and socioeconomic data. Our framework incorporated Spearman’s correlation, mutual information networks, principal component analysis, and time-series visualization. Results demonstrated that the efficacy of non-pharmaceutical interventions against Omicron varied inversely with population density: highest in Chongqing, moderate in Shanghai, and lowest in Hong Kong. Furthermore, correlation matrices revealed distinct city-specific patterns; notably, hand, foot, and mouth disease in Shanghai correlated with passenger volume ( ρ = 0.64) and international tourists ( ρ = 0.45), whereas these associations were attenuated in Chongqing. Mutual information networks uncover non-monotonic synergies and hidden city-specific hubs (e.g., NO 2 , SO 2 ) missed by correlation, alongside shared socioeconomic hubs like passenger volume and containment. Composite indices captured systemic co-exposures, with the crowd-gathering index correlating with scarlatina ( ρ = 0.37) and dengue ( ρ = 0.35). Collectively, these findings indicate that urban infection risks originate from complex, context-dependent systems. Consequently, we propose a planetary health-based urban governance framework with six pillars: intelligent foresight, nature-based design, collaborative governance, medical preparedness, data integration, and global solidarity, fostering enhanced urban resilience.