Meteorological, behavioural and social determinants in HFMD transmission: a modelling study in Guangzhou, China

Hand, foot and mouth disease (HFMD) remains a major public health challenge in China, exhibiting distinct seasonal patterns. This study integrates meteorological, behavioural and social determinants to elucidate the transmission dynamics of HFMD in Guangzhou. Utilizing surveillance data from 2012 to 2022, we employed regression analysis and developed a mechanistic transmission model incorporating absolute humidity (AH), the Baidu search index (BDI) as a proxy for health-seeking behaviour and holiday effects. The model, calibrated via Markov chain Monte Carlo methods, explained 91.4% of the case variance and estimated a mean time-varying reproduction number of 2.29. Our findings demonstrate that AH and BDI act as significant nonlinear drivers of transmission, while holidays reduced incidence by an average of 21.3%. The implementation of non-pharmaceutical interventions during the COVID-19 pandemic was associated with a substantial reduction in HFMD incidence, with cases declining by 88.1% in 2020, 36.6% in 2021 and 72.2% in 2022. This integrative modelling framework effectively captures the multifactorial drivers of HFMD seasonality and provides a robust tool for forecasting outbreaks and informing targeted public health interventions.