Background Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity. Methods We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model. Results Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season. Conclusions The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea.

Population demand, healthcare resourcing, and transportation linkage are considered as major determinants of spatial access to health care. Temporal changes of the 3 determinants would result in gain or loss of spatial access to health care. As a remarkable milestone achieved by Targeted Poverty Reduction Project launched in China, the significant improvements in spatial access to health care served as an ideal context for investigating the relative contributions of these 3 determinants to the changes in spatial access to health care in a rural county. A national level poverty-stricken county, Chishui county from Guizhou province, China, was chosen as our study area. The enhanced two-step floating catchment area model and the chain substitution method were employed for analysis. The relative contributions of the 3 determinants demonstrated variations with villages. The relative contributions of healthcare resourcing were positive in all villages as indicated by sharp increases in healthcare resources. Population changes and transportation infrastructure expansion had both negative and positive effects on spatial access to health care for different villages. Decisionmakers should take into account the duration of travel time spent between where people live, where transport hubs are located, and where healthcare services are delivered in the process of formulating policies toward rural healthcare planning. For villages with poorly-established infrastructure, the optimization of population distribution and healthcare resourcing should be considered as the priority. A stronger marginal effect would be induced by transportation infrastructure expansion with increased spatial accessibility. This study provides empirical evidences to inform healthcare planning in low- and middle-income countries.