Impact of Air Pollutants and Meteorological Factors on the Transmission Rate of Scarlet Fever in China.

Scarlet fever, a resurgent childhood infection, lacks a comprehensive understanding of how environmental factors influence its intrinsic transmission. Most existing studies directly link environmental exposures with incidence rates, the results of which may be confounded by intervention measures. In this work, we aim to investigate the lagged and nonlinear effects of air pollutants and meteorological factors on the transmission rate (β(t)) of scarlet fever across 31 provinces in China from 2013 to 2020. We first reconstruct the time-varying transmission rate from surveillance data based on an SEIRA model using a discrete inverse method. Subsequently, Distributed Lag Non-linear Models (DLNM) are applied to analyze associations between β(t) and four pollutants and four meteorological variables.Our results reveal substantial spatiotemporal heterogeneity in the inferred transmission rate. DLNM analysis identifies complex exposure-lag-response relationships. Key findings include: O3 showed positive exposure-lag at longer lag periods; CO showed a weak and nonlinear association with the transmission rate; higher relative humidity showed positive associations over medium to longer lag periods; and sunlight showed a nonlinear and exposure-dependent association with the transmission rate. Our study confirms that environmental pollutants and climatic factors are associated with the transmissibility of scarlet fever through lagged effects spanning several months. Shifting the analytical focus from incidence rates to model-inferred transmission rates can more clearly reveal the association patterns between environmental factors and transmission rates, and provide a potential scientific reference for building climate-sensitive early warning systems.