Weather elements and the risk of tuberculosis incidence in China from 2005 to 2019: a county-level large observational study

Background Tuberculosis (TB) remains a major public health challenge in China. Although meteorological factors are known to influence its transmission, their nonlinear and lagged impacts across regions and seasons remain unclear. We quantified these effects using the most detailed national data set available and explored how climate information can enhance TB prediction and control. Methods We conducted a nationwide ecological time-series study by integrating weekly TB surveillance data (2005-19) with high-resolution meteorological and air pollution models. We assessed associations between TB incidence and meteorological factors using negative binomial regression and distributed lag nonlinear models to account for nonlinear and delayed effects. Results From 2005 to 2019, TB cases in China decreased from 1.23 million to 0.75 million (estimated annual percent change Conclusions By integrating fine-scale epidemiological and meteorological data, our study adds to our knowledge on TB epidemiology by more accurately characterising climate-disease interactions and enhancing the predictive capability of risk models. The findings provide empirical evidence to support the development of risk stratification tools and guide the implementation of proactive, phased intervention strategies aimed at mitigating the persistent TB burden in high-risk regions.