Schistosomiasis is a significant public health threat, and Oncomelania hupensis is the only intermediate host for schistosoma japonicum. We conducted 12-year monthly repeated surveys to explore the interactive and lag effects of environmental factors on snail density and to monitor their long-term and seasonal trends in a bottomland around the Dongting Lake region in China. Relevant environmental data were obtained from multiple sources. A Bayesian kernel machine regression model and a Bayesian temporal model combined with a distributed lag model were constructed to analyze interactive and lag effects of environmental factors on snail density. The results indicated the average annual snail density in the study site exhibited an increasing and then decreasing trend, peaking in 2013. Snail densities were the highest in October and the lowest in January in a year. Normalized Difference Vegetation Index (NDVI) and water level were the most effective predictors of snail density, with potential interactions among temperature, precipitation, and NDVI. The mean minimum temperature in January, water level, precipitation and NDVI were positively correlated with snail density at lags ranging from 1 to 4 months. These findings could serve as references for relevant authorities to monitor the changing trend of snail density and implement control measures, thereby reducing the occurrence of schistosomiasis.

Oncomelania hupensis is the exclusive intermediary host of Schistosoma japonicum in China. The alteration of O. hupensis habitat and population distribution directly affects the safety of millions of individuals residing in the Yangtze River Economic Belt (YREB) and the ecological stability of Yangtze River Basin. Therefore, it is crucial to analyze the influence of climate change on the distribution of O. hupensis in order to achieve accurate control over its population. This study utilized the MaxEnt model to forecast possible snail habitats by utilizing snail distribution data obtained from historical literature. The following outcomes were achieved: The primary ecological factors influencing the distribution of O. hupensis are elevation, minimum temperature of the coldest month, and precipitation of wettest month. Furthermore, future climate scenarios indicate a decrease in the distribution area and a northward shift of the distribution center for O. hupensis; specifically, those in the upstream will move northeast, while those in the midstream and downstream will move northwest. These changes in suitable habitat area, the average migration distance of distribution centers across different climate scenarios, time periods, and sub-basins within the YREB, result in uncertainty. This study offers theoretical justification for the prevention and control of O. hupensis along the YREB.

To find a high-efficiency and environment-friendly biogenic molluscicide against Oncomelania hupensis, and prevent aquatic ecosystem from being contaminated by chemical molluscicides and being toxic. We extracted and purified raphides from the tubers of Arisaema erubescent, and determined the active constituents and molluscicidal activity of the raphides, detoxification enzyme activity, and liver damage. The results showed that the raphides had a strong molluscicidal activity. O. hupensis snails were exposed to the lethal concentration (LC50) of 70.95 mg/L and 44.25 mg/L for treatment with raphides for 48 h and 72 h, respectively. The raphides of molluscicidal activity of the main constituents was as follows: intact raphides > calcium oxalate crystals > AEL (Arisaema erubescens Lectin). The activities of peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT) in the snail livers increased significantly at the early stage of treatment (24 h), but decreased sharply in the later stage (120 h), compared with that in the control group. The results indicated that after treatment with 1/2 LC50 raphides for 120 h, the activities of POD, SOD, and CAT in the snail livers decreased by 82.5 %, 62.9 %, and 84.7 %, respectively. In addition, electron micrographs have shown that the raphides were needle-shaped crystals and tended to be sharp at both ends (with a groove down both sides) and some were barbed, which caused damage to the snail livers to different extent. Overall, our results indicate that the mechanism of toxicity of raphides against O. hupensis may be that the calcium oxalate crystals pricked the liver surface of snail and produced mechanical damage; and then the harmful protease AEL in the raphides was injected into the liver, which reduced the activities of detoxification enzymes, produced severe toxic reactions and eventually killed the O. hupensis snails.

Schistosomiasis, the second largest parasitic disease in the world after malaria, poses a significant threat to human health and causes public health issues. The disease primarily affects populations in economically underdeveloped tropical regions, earning it the title of \"neglected tropical disease\". Schistosomiasis is difficult to eradicate globally if medication alone is used. One of the essential elements of thorough schistosomiasis prevention and control is the management and disruption of the life cycle of intermediate host snails. The key approach to controlling the transmission of schistosomiasis is to control the intermediate hosts of the schistosome to disrupt its life cycle. We believe that approaching it from the perspective of the intermediate host\'s immunity could be an environmentally friendly and potentially effective method. Currently, globally significant intermediate host snails for schistosomes include Oncomelania hupensis, Biomphalaria glabrata, and Bulinus truncatus. The immune interaction research between B. glabrata and Schistosoma mansoni has a history of several decades, and the complete genome sequencing of both B. glabrata and B. truncatus has been accomplished. We have summarized the immune-related factors and research progress primarily studied in B. glabrata and B. truncatus and compared them with several humoral immune factors that O. hupensis research focuses on: macrophage migration inhibitory factor (MIF), Toll-like receptors (TLRs), and thioredoxin (Trx). We believe that continued exploration of the immune interactions between O. hupensis and Schistosoma japonicum is valuable. This comparative analysis can provide some direction and clues for further in-depth research. Comparative immunological studies between them not only expand our understanding of the immune defense responses of snails that act as intermediaries for schistosomes but also facilitate the development of more comprehensive and integrated strategies for schistosomiasis prevention and control. Furthermore, it offers an excellent opportunity to study the immune system of gastropods and their co-evolution with pathogenic organisms.

BACKGROUND: Oncomelania hupensis is the sole intermediate host of Schistosoma japonicum. Its emergence and recurrence pose a constant challenge to the elimination of schistosomiasis in China. It is important to accurately predict the snail distribution for schistosomiasis prevention and control.
METHODS: Data describing the distribution of O. hupensis in 2016 was obtained from the Yunnan Institute of Endemic Disease Control and Prevention. Eight machine learning algorithms, including eXtreme Gradient Boosting (XGB), support vector machine (SVM), random forest (RF), generalized boosting model (GBM), neural network (NN), classification and regression trees (CART), k-nearest neighbors (KNN), and generalized additive model (GAM), were employed to explore the impacts of climatic, geographical, and socioeconomic variables on the distribution of suitable areas for O. hupensis. Predictions of the distribution of suitable areas for O. hupensis were made for various periods (2030s, 2050s, and 2070s) under different climate scenarios (SSP126, SSP245, SSP370, and SSP585).
RESULTS: The RF model exhibited the best performance (AUC: 0.991, sensitivity: 0.982, specificity: 0.995, kappa: 0.942) and the CART model performed the worst (AUC: 0.884, sensitivity: 0.922, specificity: 0.943, kappa: 0.829). Based on the RF model, the top six important variables were as follows: Bio15 (precipitation seasonality) (33.6%), average annual precipitation (25.2%), Bio2 (mean diurnal temperature range) (21.7%), Bio19 (precipitation of the coldest quarter) (14.5%), population density (13.5%), and night light index (11.1%). The results demonstrated that the overall suitable habitats for O. hupensis were predominantly distributed in the schistosomiasis-endemic areas located in northwestern Yunnan Province under the current climate situation and were predicted to expand north- and westward due to climate change.
CONCLUSIONS: This study showed that the prediction of the current distribution of O. hupensis corresponded well with the actual records. Furthermore, our study provided compelling evidence that the geographical distribution of snails was projected to expand toward the north and west of Yunnan Province in the coming decades, indicating that the distribution of snails is driven by climate factors. Our findings will be of great significance for formulating effective strategies for snail control.

Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence.
In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data.
The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen\'s kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways.
Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Oncomelania hupensis is the obligate intermediate host of Schistosoma japonicum, highlighting the medical importance of interrupting this unique and long-standing parasite-host interaction in controlling schistosomiasis transmission. It has been reported that a catfish trematode Exorchis sp. could have the potential to function as an effective anti-schistosomal agent in the snail host. However, the feasibility of this eco-friendly biological control strategy should be comprehensively investigated and evaluated in endemic areas for schistosomiasis. In this study, a field survey was conducted from 2012 to 2016 in the marshlands of Poyang Lake, which is one of the highly endemic regions for schistosomiasis in China. Results showed that more than half of Silurus asotus (65.79%) were infected with Exorchis sp., and the average intensity of infection was 14.21 per fish. And the average infection rate of Exorchis sp. in O. hupensis is 1.11%. These findings indicated that there are abundant biological resources for the implementation of this biology control strategy in the marshlands of Poyang Lake. The data presented here provide solid evidences for the practical application of this biological control strategy, thereby contributing to achieving the goals of the elimination of schistosomiasis.

BACKGROUND: The area of Oncomelania hupensis snail remains around 3.6 billion m2, with newly emerging and reemergent habitats continuing to appear in recent years. This study aimed to explore the long-term dynamics of snail density before and after the operation of Three Gorges Dam (TGD).
METHODS: Data of snail survey between 1990 and 2019 were collected from electronic databases and national schistosomiasis surveillance. Meta-analysis was conducted to estimate the snail density. Joinpoint model was used to identify the changing trend and inflection point. Inverse distance weighted interpolation (IDW) was used to determine the spatial distribution of recent snail density.
RESULTS: A total of 3777 snail survey sites with a precise location of village or beach were identified. For the downstream area, snail density peaked in 1998 (1.635/0.11 m2, 95% CI: 1.220, 2.189) and fluctuated at a relatively high level before 2003, then declined steadily from 2003 to 2012. Snail density maintained lower than 0.150/0.11 m2 between 2012 and 2019. Joinpoint model identified the inflection of 2003, and a significant decreasing trend from 2003 to 2012 with an annual percentage change (APC) being - 20.56% (95% CI: - 24.15, - 16.80). For the upstream area, snail density peaked in 2005 (0.760/0.11 m2, 95% CI: 0.479, 1.207) and was generally greater than 0.300/0.11 m2 before 2005. Snail density was generally lower than 0.150/0.11 m2 after 2011. Snail density showed a significant decreasing trend from 1990 to 2019 with an APC being - 6.05% (95% CI: - 7.97, - 7.09), and no inflection was identified. IDW showed the areas with a high snail density existed in Poyang Lake, Dongting Lake, Jianghan Plain, and the Anhui branch of the Yangtze River between 2015 and 2019.
CONCLUSIONS: Snail density exhibited a fluctuating downward trend in the Yangtze River basin. In the downstream area, the operation of TGD accelerated the decline of snail density during the first decade period, then snail density fluctuated at a relatively low level. There still exists local areas with a high snail density. Long-term control and monitoring of snails need to be insisted on and strengthened.

Schistosomiasis is a helminth infection caused by the genus Schistosoma, which is still a threat in tropical and sub-tropical areas. In the China, schistosomiasis caused by Schistosoma japonicum is mainly endemic to the Yangtze River valley. The amphibious snail Oncomelania hupensis (O. hupensis) is the unique intermediate host of S. japonicum; hence, snail control is a crucial approach in the process of schistosomiasis transmission control and elimination. In 2016, a nationwide snail survey was conducted involving all snail habitats recorded since 1950 in all endemic counties of 12 provinces. A total of 53,254 existing snail habitats (ESHs) were identified, presenting three clusters in Sichuan Basin, Dongting Lake, and Poyang Lake. The overall habitat area was 5.24 billion m2, of which 3.58 billion m2 were inhabited by O. hupensis. The area inhabited by snails (AIS) in Dongting and Poyang Lakes accounted for 76.53% of the population in the country. Three typical landscape types (marshland and lakes, mountains and hills, and plain water networks) existed in endemic areas, and marshland and lakes had a predominant share (3.38 billion m2) of the AIS. Among the 12 endemic provinces, Hunan had a share of nearly 50% of AIS, whereas Guangdong had no ESH. Ditches, dryland, paddy fields, marshland, and ponds are common habitat types of the ESH. Although the AIS of the marshland type accounted for 87.22% of the population in the whole country, ditches were the most common type (35,025 or 65.77%) of habitat. Six categories of vegetation for ESHs were identified. A total of 39,139 habitats were covered with weeds, accounting for 55.26% of the coverage of the area. Multiple vegetation types of snail habitats appeared in the 11 provinces, but one or two of these were mainly dominant. Systematic sampling showed that the presence of living snails was 17.88% among the 13.5 million sampling frames. The occurrence varied significantly by landscape, environment, and vegetation type. The median density of living snails in habitats was 0.50 per frame (0.33 m × 0.33 m), and the highest density was 40.01 per frame. Furthermore, two main clusters with high snail densities and spatial correlations indicated by hotspot analysis were identified: one in Hunan and Hubei, the other in Sichuan. This national survey is the first full-scale census on the distribution of O. hupensis, which is significant, as transmission interruption and elimination are truly becoming the immediate goal of schistosomiasis control in China. The study discerns the detailed geographic distribution of O. hupensis with the hotspots of snail density in China. It is beneficial to understand the status of the snail population in order to finally formulate further national control planning.

The construction of the Yangtze River Economic Belt (YEB) is a great national economic development strategy in China. As the YEB covers most endemic provinces of schistosomiasis japonica featured by low endemicity, this study aimed to investigate the spatiotemporal distribution pattern of Oncomelania hupensis (O. hupensis), which serves as the only intermediate host of Schistosoma japonicum in the YEB. Annual data reflecting the distribution of O. hupensis from 2015 to 2021 were collected from the National Institute of Parasitic Disease, Chinese Center for Disease Control and Prevention. Spatial autocorrelation analysis, hotspot analysis and space-time scan analysis were performed to explore the aggregation features and spatiotemporal dynamics of the snail distribution. The distribution of both total snail habitats (during 2015-2021) and emerging snail habitats (in 2016, 2018 and 2020) showed spatial autocorrelation (Z = 15.8~16.1, p < 0.05; Z = 2.3~7.5, p < 0.05). Hotspot (high-value areas in space) counties were mainly clustered in the alluvial plain of the middle and lower reaches of the YEB. Eight spatial and temporal clusters of snail habitats were scanned and were mainly concentrated in the counties of Anhui, Jiangxi, Hubei, Hunan and Jiangsu provinces along the Yangtze River. The YEB carries a tremendous burden of O. hupensis. Surveillance and risk identification based on the snail presence should be strengthened to provide reference for protecting humans and public health security in the YEB.