Spatiotemporal pattern analysis of schistosomiasis based on village level in the transmission control stage in lake and marshland areas in China

Abstract

Hubei Province is one of the endemic regions with severe schistosomiasis in China. To eliminate schistosomiasis in lake and marshland regions, this study detected hotspots of schistosomiasis cases both spatially and spatiotemporally on the basis of spatial autocorrelation; clustering and outlier, purely spatial and spatiotemporal cluster analyses at the village level from 2013 to 2017 in Hubei Province. The number of cases confirmed positive by an immunodiagnostic test and etiological diagnosis and advanced schistosomiasis cases dramatically declined during the study period. Significant global spatial autocorrelation of schistosomiasis patients was found at the village level in the whole province in 5 years. Clustering and outlier analysis showed that most HH villages were mainly concentrated along the Yangtze River, especially in Jianghan Plain. Spatial and spatiotemporal cluster analyses showed that significant clusters of the schistosomiasis cases were detected at the village level. In general, space and spatiotemporal clustering of schistosomiasis cases at the village level demonstrated a downward trend from 2013 from 2017 in Hubei Province. High-risk regions included Jianghan Plain along the middle reach of Yangtze River and Yangxin County in the lower reaches of the Yangtze River in Hubei Province. To eliminate schistosomiasis, precise control and management of schistosomiasis cases should be strictly implemented. Moreover, comprehensive prevention and control measures should be continuously strengthened in these regions.

Infestation risk of the intermediate snail host of Schistosoma japonicum in the Yangtze River Basin: improved results by spatial reassessment and a random forest approach

“…Since O. hupensis is an amphibious snail that needs water for reproduction and survival, the greatest factor with regard to snail infestation was unsurprisingly found to be the distance to water bodies, a result consistent with previous observations near the Yangtze River [ 37 , 38 ]. Second, human activities have a non-linear level of impact on the probability of snail infestation but the footprint shows the lowest values in unperturbed environments where the probability of O. hupensis survival consequently is high, in contrast to urban and industrial areas where O. hupensis habitats are scarce.…”

Geographic Information System-based association between the sewage network, geographical location of intermediate hosts, and autochthonous cases for the estimation of risk areas of schistosomiasis infection in Ourinhos, São Paulo, Brazil

“…Previous studies have used this tool (Gi or Gi* statistics) to analyze schistosomiasis in Africa 16 , 17 , 18 , 19 and vector-borne diseases, such as dengue , in Brazil 20 . Additionally, other studies have investigated schistosomiasis using GIS worldwide 5 , 21 , 22 , 23 . Thus, GIS and spatial analysis tools may contribute to identifying areas with the highest risk of human schistosomiasis infection and other diseases and consequently help guide public health measures 21 , 24 .…”