Cross-watershed distribution pattern challenging the elimination of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, in Sichuan province, China

Abstract

Background Snail control is critical to schistosomiasis control efforts in China. However, re-emergence of Oncomelania hupensis is challenging the achievements of schistosomiasis control. The present study aimed to test whether the amphibious snails can spread across watersheds using a combination of population genetics and geographic statistics. Methods The digital maps and attributes of snail habitats were obtained from the national survey on O. hupensis. Snail sampling was performed in 45 counties of Sichuan Province. The cox1 gene of specimens was characterized by sequencing. Unique haplotypes were found for phylogenetic inference and mapped in a geographical information system (GIS). Barriers of gene flow were identified by Monmonier’s maximum difference algorithm. The watercourses and watersheds in the study area were determined based on a digital elevation model (DEM). Plain areas were defined by a threshold of slope. The slope of snail habitats was characterized and the nearest distance to watercourses was calculated using a GIS platform. Spatial dynamics of high-density distributions were observed by density analysis of snail habitats. Results A total of 422 cox1 sequences of O. hupensis specimens from 45 sampling sites were obtained and collapsed into 128 unique haplotypes or 10 clades. Higher haplotype diversity in the north of the study area was observed. Four barriers to gene flow, leading to five sub-regions, were found across the study area. Four sub-regions ran across major watersheds, while high-density distributions were confined within watersheds. The result indicated that snails were able to disperse across low-density areas. A total of 63.48% habitats or 43.29% accumulated infested areas were distributed in the plain areas where the overall slope was < 0.94°. Approximately 90% of snail habitats were closer to smaller watercourses. Historically, high-density areas were mainly located in the plains, but now more were distributed in hilly region. Conclusions Our study showed the cross-watershed distribution of Oncomelania snails at a large scale. Natural cross-watershed spread in plains and long-distance dispersal by humans and animals might be the main driver of the observed patterns. We recommend cross-watershed joint control strategies for snail and schistosomiasis control. Graphical Abstract

Population Genetics of Oncomelania hupensis Snails from New-Emerging Snail Habitats in a Currently Schistosoma japonicum Non-Endemic Area

“…This is consistent with the above results. We therefore raised the hypothesis that due to an annual flooding occurring along the Yangtze River, coupled with the movement ecology of O. hupensis , the 2014 snail population in the new emerging habitat might come from its upper reaches nearby, as Taicang of Jiangsu is connected via several canals to the river and snail dispersal may occur along the waterways [ 41 , 42 , 43 ]. The 2015 population, which might be descended from the 2014, may have spread and then form the 2016 and the 2017, the latter of which might have been missed in the local snail survey performed in 2016.…”

The Current Distribution of Oncomelania hupensis Snails in the People’s Republic of China Based on a Nationwide Survey

“…However, the AIS was only 66.10 million m 2 (or 1.85%). The snail habitats are often the small ditches around farmland either in plains or on terraces [ 41 ]. The transformation from rice paddies to dryland in some mountainous areas showed good effectiveness in snail control and schistosomiasis transmission interruption [ 42 ].…”

“…The habitats with a high risk of schistosomiasis transmission should be identified, and these populations should be disposed of in a most reasonable method. Watershed ecological approaches can be used in planning [ 41 , 46 ]. Secondly, technological breakthroughs in snail control are needed.…”

Prediction of Oncomelania hupensis distribution in association with climate change using machine learning models

“…Human population dynamics are often considered to be a major contributor to altering the natural environment. In addition, humans can also directly bring snails to other areas for dispersal, such as the construction of flood control embankments, transportation of seeds, and ditch irrigation [ 50 , 51 ]. The NLI has been applied to assess ecological status, as it reflects the level of urbanization and acts as an indicator of human activity [ 52 – 54 ].…”

“…Consistently, a snail survey conducted in 2021 found that Changtou village of Heqing County ranked first in terms of recurrence of O. hupensis among the 32 villages investigated in 18 endemic counties [ 56 ]. Meanwhile, it is worth noting that our prediction model also found additional suitable regions where O. hupensis has so far been unrecorded but may require further investigation, including Yongping County and Longyang District, due to the possibility of human activities introducing snails into areas suitable for their survival, thus facilitating their dispersal [ 50 , 51 ].…”