Drinking water monitoring is essential for identifying health-related risks, as well as for building foundations for management of safe drinking water supplies. However, statistical analyses of drinking water quality monitoring data are challenging because of non-normal (skewed distributions) and missing values. Therefore, a new method combining a water quality index (WQI) with spatial analysis is introduced in this paper to fill the gap between data collection and data analysis. Water constituent concentrations in different seasons and from different water sources were compared based on WQIs. To generate a WQI map covering all of the study areas, predicted WQI values were created for locations in the study area based on spatial interpolation from nearby observed values. The accuracy value of predicted and measured values of our method was 0.99, indicating good predication performance. Overall, the results of this study indicate that this method will help fill the gap between the collection of large amounts of drinking water data and data analysis for drinking water monitoring and process control.

Intermittent water supply (IWS) is a relatively common phenomenon across the world as well as in rural and peri-urban areas across China, though there has been little IWS-focused research from China published to date. IWS consumers typically adopt a range of strategies to cope with insufficient water supply, poor drinking water quality, and associated inconveniences. In this study, we collected a range of data from small-scale utilities and households in two IWS systems and two continuous water supply (CWS) systems, as well as from comparison groups, in Shandong and Hubei provinces. Data collection included water quality testing, interviews, and surveys on behavioral adaptations, coping strategies, water-related health perceptions, and other metrics of consumer satisfaction. Overall, we found that the IWS coping strategies employed in northern China (Shandong) were associated with generally safe, but inconvenient, water access, whereas adaptation strategies observed in southern China (Hubei) appeared to improve convenience, but not water quality. Compared to the CWS comparison groups, we did not observe significant differences in water- and sanitation-related behaviors in the IWS groups, suggesting interventions to increase adaptive and protective behaviors at the household level might further improve safe water access for households living with IWS. Overall, although the water supply infrastructure in these study areas appeared to be in relatively good condition, in contrast to reported data on IWS systems in other countries, we observed multiple risk factors associated with the water treatment and distribution processes in these IWS systems. Among policy recommendations, our results suggest that the implementation of Water Safety Plans in China would likely improve the management of drinking water treatment and, by extension, safe drinking water supply under conditions of IWS.

The epidemiological features of Cryptosporidium infection among school-age children in China still remain unclear. Hereby, a cross-sectional study of 1637 children aged 3–9 years was designed to investigate the risk factors and spatial clusters of Cryptosporidium infection in a rural region of Eastern China. Stool specimens collected from participants were examined using the auramine-phenol and modified acid-fast staining. Univariable and multivariable analyses were performed to identify the risk factors of Cryptospordium infection. The spatial clusters were analyzed by a discrete Poisson model using SaTScan software. Our results showed that the overall prevalence of Cryptosporidium infection was 11‰ in the research region. At the age of 3–6 years (odds ratios (OR) = 3.072, 95% confidence intervals (CI): 1.001–9.427), not washing hands before eating and after defecation (OR = 3.003, 95% CI: 1.060–8.511) were recognized as risk factors. Furthermore, a high-risk spatial cluster (relative risk = 4.220, p = 0.025) was identified. These findings call for effective sustainable interventions including family and school-based hygienic education to reduce the prevalence of Cryptosporidium infection. Therefore, an early warning system based spatiotemporal models with risk factors is required to further improve the effectiveness and efficiency of cryptosporidiosis control in the future.