Empirical dynamic modeling reveals climatic drivers in dynamics of bacillary dysentery epidemics in China

Abstract

At present, there is still a lack of studies to address the dynamics underlying epidemics of bacillary dysentery (BD), with particular concern on the role of climatic drivers across different regions of a country or the world. The variability of climate domains, non-linear interactions, and covariations of climatic variables pose challenges for explaining the correlation between environment and BD and identifying causal climatic drivers. In this nationwide study involving 31 provincial capital cities in China, we used the empirical dynamic modeling (EDM), which is a framework for nonlinear time series analysis, to explore climate-driven patterns of BD. We first identified possible temperature (i.e. mostly via its seasonality) and relative humidity driving BD dynamics nationally. Then, we used the EDM to estimate the causal intensity of temperature and relative humidity in different latitudes. The results reveal that the combined nonlinear effect of them on BD may be nationwide, but this effect is concealed due to their high correlation in northern regions. We also found an approximately S-shaped relationship between temperature and BD at the population level; while the effects of relative humidity on BD are strongly dependent on environmental details, especially at temperatures above 0 °C. Temperature may potentially mediate and affect the effects of relative humidity on BD. This nationwide study provides a unified explanation for causal climate drivers of BD, regardless of the different climatic domains and epidemic patterns of BD in diverse cities.

Keywords

• bacillary dysentery
• climatic drivers
• empirical dynamic modeling
• nonlinear dynamics