Bacterial dysentery (BD) brings a major disease burden to developing countries. Exploring the influence of temperature and its interaction with other meteorological factors on BD is significant for the prevention and early warning of BD in the context of climate change. Daily BD cases and meteorological data from 2008 to 2018 were collected in all nine prefecture-level cities in Jilin Province. A one-stage province-level model and a two-stage city-specific multivariate meta-pooled level distributed lag non-linear model were established to explore the correlation between temperature and BD, then the weather-stratified generalised additive model was used to test the interaction. During the study period, a total of 26 971 cases of BD were developed. The one-stage and two-stage cumulative dose-response ‘J’ curves overlapped, and results showed a positive correlation between temperature and BD with a 1–6 days lag effect. Age group ⩾5 years was found to be more sensitive to the effects. Moreover, there was a significant interaction between temperature, humidity and precipitation (P = 0.004, 0.002, respectively) on BD under high temperature (>0 °C), reminding residents and policymakers to pay attention to the prevention of BD in situations with both high temperature and humidity, high temperature and precipitation during the temperate monsoon climate.

Bacillary dysentery continues to be a major health issue in developing countries and ambient temperature is a possible environmental determinant. However, evidence about the risk of bacillary dysentery attributable to ambient temperature under climate change scenarios is scarce. We examined the attributable fraction (AF) of temperature-related bacillary dysentery in urban and rural Hefei, China during 2006–2012 and projected its shifting pattern under climate change scenarios using a distributed lag non-linear model. The risk of bacillary dysentery increased with the temperature rise above a threshold (18·4 °C), and the temperature effects appeared to be acute. The proportion of bacillary dysentery attributable to hot temperatures was 18·74% (95 empirical confidence interval (eCI): 8·36–27·44%). Apparent difference of AF was observed between urban and rural areas, with AF varying from 26·87% (95% eCI 16·21–36·68%) in urban area to −1·90% (95 eCI −25·03 to 16·05%) in rural area. Under the climate change scenarios alone (1–4 °C rise), the AF from extreme hot temperatures (>31·2 °C) would rise greatly accompanied by the relatively stable AF from moderate hot temperatures (18·4–31·2 °C). If climate change proceeds, urban area may be more likely to suffer from rapidly increasing burden of disease from extreme hot temperatures in the absence of effective mitigation and adaptation strategies.

The current study aimed to examine the relationship between floods and the three enteric infectious diseases, namely bacillary dysentery (BD), hand-foot-mouth disease (HFMD) and other infectious diarrhoea (OID) in Qingdao, China. Relative risks (RRs) and 95% confidence intervals (CIs) of floods on BD, HFMD and OID were calculated using a quasi-Poisson generalized linear model, adjusting for daily average temperature, daily average relative humidity, and seasonal and long-term temporal trends. Two separate models within two different periods were designed. Model 1 for the summer period showed that floods were positively associated with BD for 4- to 12-day lags, with the greatest effects for 7-day (RR 1·41, 95% CI 1·22–1·62) and 11-day (RR 1·42, 95% CI 1·22–1·64) lags. Similar findings were found in model 2 for the whole study period for 5- to 12-day lags. However, HFMD and OID were not significantly associated with floods in both models. Results from this study will provide insight into the health risks associated with floods and may help inform public health precautionary measures for such disasters.

Previous studies examining the weather–bacillary dysentery association were of a large time scale (monthly or weekly) and examined the linear relationship without checking the linearity assumption. We examined this association in Beijing at a daily scale based on the exposure-response curves using generalized additive models. Our analyses suggested that there were thresholds for effects of temperature and relative humidity, with an approximately linear effect for temperature >12·5 °C [excess risk (ER) for 1 °C increase: 1·06%, 95% confidence interval (CI) 0·63–1·49 on lag day 3] and for relative humidity >40% (ER for 1% increase: 0·18%, 95% CI 0·12–0·24 at lag day 4); and there were linear effects of rainfall (ER for 1-mm increase: 0·22%, 95% CI 0·12–0·32), negative effects for wind speed (ER: −2·91%, 95% CI −4·28 to −1·52 at lag day 3) and sunshine duration (ER: −0·25% 95% CI −0·43 to −0·07 at lag day 4). This study suggests that there are thresholds for the effects of temperature and relative humidity on bacillary dysentery, and these findings should be considered in its prevention and control programmes.