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Spatiotemporal Evolution of Oncomelania Snails and Their Responses to Environmental Factors in Wuhan City from 2014 to 2023
XIN Ji, WANG Li-hua, LIU Cong, XU Jian, ZHANG Jia-jing
Journal of Changjiang River Scientific Research Institute ›› 2026, Vol. 43 ›› Issue (9) : 1-10.
PDF(3061 KB)
PDF(3061 KB)
Spatiotemporal Evolution of Oncomelania Snails and Their Responses to Environmental Factors in Wuhan City from 2014 to 2023
[Objective] Schistosomiasis japonica is a zoonotic parasitic disease caused by Schistosoma japonicum. As its sole intermediate host, the distribution pattern of Oncomelania hupensis snails is critical for disease control. This study aims to investigate the spatiotemporal trends of snail habitats, their responses to environmental factors, and the spatial distribution of future high-risk areas, thereby providing scientific support and decision-making references for identifying snail risk zones and preventing schistosomiasis in Wuhan City. [Methods] Based on spring snail survey data from Wuhan City between 2014 and 2023, remote sensing techniques were utilized to construct and extract a Vegetation Suitability Index (VSI), integrating the median membership of NDVI, textural homogeneity, patch scale, and edge density. Concurrently, environmental factors were acquired, including the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Water Incidence Frequency (WIF), Temperature (TEMP), Precipitation (PREC), Soil Moisture (SM), and Distance to Water (DIS). The spatiotemporal evolution of snail distribution was systematically analyzed, alongside the relationship between snail density and primary environmental factors. Spatial clustering and variations in cold/hotspot areas were evaluated. Finally, an XGBoost model was employed to predict snail habitat risk zones. [Results] (1) From 2014 to 2023, both the snail-infested area and the density of live snails in Wuhan exhibited a fluctuating downward trend. The snail-infested area decreased from 43.675 7 million m2 in 2014 to 26.564 3 million m2 in 2023, with an average annual reduction of approximately 4.2%. The density of live snails declined from 0.061 snails per 0.11 m2 in 2014 to 0.036 snails per 0.11 m2 in 2023. (2) Over the past decade, snail density was spatially clustered mainly along the Fuhe River, the Yangtze River, and the Tongshun River, demonstrating significant spatial aggregation. The dynamic evolution of snail habitats varied distinctly across different river basins. The snail-infested area in the Fuhe River basin shrank substantially; the Yangtze River basin showed an overall fluctuating downward trend; whereas the Tongshun River basin experienced a rebounding growth, becoming the core area for subsequent snail expansion. (3) Correlation analysis indicated that moisture-related factors had the most prominent impact on snail density (SM, WIF, and PREC showed moderate positive correlations). The improved VSI provided more effective supplementary explanations than NDVI alone, while the correlations with LST, TEMP, and DIS were generally weak. Based on these findings, a simplified factor model (SM, WIF, PREC, VSI) achieved a higher R2 under identical evaluation conditions without increasing errors compared to the full-factor model, indicating that a few key factors are sufficient to support snail density prediction and risk zoning. [Conclusions] (1) The snail density risk zoning map, constructed based on model-predicted values, reveals that future high-risk areas are primarily distributed along the Fuhe River, Tongshun River, and Zhuru River. These areas are highly consistent with historical hotspots and may serve as key regions for snail density rebound or expansion. (2) It is recommended to prioritize snail eradication and ecological remediation in high-risk areas, strengthen monitoring, early warning, and risk assessments to promptly identify and mitigate hazards, and enhance patrol management in seasonal waterlogged areas, agricultural irrigation canals, and abandoned wetlands to prevent covert snail diffusion and habitat revival. These findings provide a basis for targeted schistosomiasis control in key river basins and offer technical support for snail monitoring and ecological regulation around water conservancy projects.
oncomelania snails / remote sensing / environmental factors / long-term series / Wuhan City
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Schistosomiasis is a water-bourne parasitic disease endemic to Yangtze River basin of China. And the disease epidemic would be seriously influence on the public health and socio-economic developing. After the big flood of 1998, a lot of flood control measures such as “ discharge of flood by removing some of dikes, giving up the cultivated land around for restoreing of lake ' s capacity ” were brought into effect. However, the flood control measures would be extensive in influence on the river ecosystem, and also the Oncomelania snail and Schistosomiasis transmission dynamics was affected by the flood control measures. In this article, the factor that affected transmission dynamics of Oncomelania snail and schistosomiasis was summarized, and the change of Schistosomiasis epidemic after flood control measures implemented was investigated. The results show that: transmission dynamics of Oncomelania snail and schistosomiasis is relation to the nature habitats and human activity, and also relation to the results of interaction between nature habitats and human activity. In the areas where the flood control measures implemented, the transmission dynamics of schistosomiasis present different results because of the different way of the measures implemented. And in this paper the measures controlling epidemic of schistosomiasis were brought forward against the different flood storage and detention areas.
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Schistosomiasis japonica is a parasitic disease that debilitates human bodies and greatly impedes socioeconomic progress in endemic areas. It was widespread in southern China several decades ago and the disease prevention effort of the Chinese government and researchers achieved remarkable results in reducing infections. However, in recent year, the epidemic situation has worsened due to a series of changes in the natural environment and socioeconomic conditions. As the only intermediate host of Schistosome, Oncomelania hupensis plays an important role in the spread of this disease and its control is critical for the prevention and control of Schistosome. Therefore, identifying the environmental factors that determine the distribution of the snail could help predict the distribution and extent of snail breeding sites, obtain a macroscopic view on snail spreading trend, and take effective measures to eliminate the snails. In this paper, we aim to determine key indictors that could be used in remote sensing monitoring of Oncomelania hupensis breeding extent and density. Hubei Province is one of the serious epidemic areas in China. Oncomelania hupensis here can be classified into three subtypes: the subtype inside embankments, subtype outside embankments, and subtype in hilly areas, according to the geographical environment of snail habitats. We take into account several environmental factors including elevation, nearest distance to river (water), land use, soil and vegetation to analyze their influence on snail distribution. Geographical Detector Model used in this research is based on spatial variation analysis of the geographical strata to assess the health risks in different environment. It contains four geographical detectors: factor detector identifies which factors are responsible for the risk; ecological detector compares the relative importance of risk factors; risk detector discloses where the high risk areas are; and interaction detector reveals whether the risk factors interact or lead to disease independently. The main procedures of our analysis are as follows: first, both snail statistics and environmental data are collected and preprocessed with ArcGIS Desktop software; then the environmental indicators that are strongly related to snail distribution are identified by the factor detector and ecological detector; finally, favorable (suitable) type or range of each indicator as well as the reference factors that indirectly influence the snails can be computed from the risk detector and interaction detector. It is found that for the subtype inside embankments, vegetation coverage of epidemic season (March to October), especially July to September, determines the extent of distribution, while high density areas are characterized by moderate silt content in soil texture, yellowish red soil and submerged paddy soil, high vegetation coverage in the first quarter of the year. The subtype outsider embankments distributed mainly at lake beaches with high vegetation coverage, while high vegetation coverage in the first quarter, reed and amur silver grass vegetation contributes to its abundance. In hilly areas, there is no clear indicator for the extent of distribution of the subtype due to the relatively complex environment, yet woodland and farmland close to river, waterlogged paddy soil as well as submerged paddy soil are strongly related to high dense of the snails. This result is consistent with previous studies. The result and method of this research could provide scientific reference for policy makers and researchers to take efficient measures to control snail prevalence.
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Schistosomiasis is one of the key diseases of surveillance and prevention in China. The elimination of schistosomiasis is of great significance to people's health and social economy. With the development of spatial epidemiology, progress has been made in the spatial distribution of schistosomiasis, the prediction of spatial and temporal trends, and analysis of the environmental factors. This paper reviews the application of spatial epidemiology in the control and prevention of schistosomiasis and introduces the spatio-temporal distribution methods, spatial model, and application of remote sensing technology.
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Schistosomiasis is closely related to environmental factors, the changes of environmental factors, such as vegetation, temperature, hydrology and soil, could impact the transmission of the disease. The environmental factors associated with schistosomiasis could be extracted by remote sensing technology quickly and precisely, and be applied to monitor the schistosomiasis transmission. The studies on high resolution remote sensing technology applied in the research of schistosomiasis are reviewed in this paper.
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水体时空分布特征对于水资源监测与应用具有重要意义，而包括水体分布在内的地物覆盖类型分类和变化分析是遥感技术最常见的应用。对大区域的水体参数提取，尤其是高山无人区的水体的定量分析，利用卫星遥感数据进行水体位置、面积、形状和河宽等水体参数提取，不仅节省人力、保障安全，还提高了工作效率，已经成为一种快速获取水体参数的有效方法和手段。该文从4个方面对卫星遥感在水体信息提取上的应用现状进行综述：水体在电磁波波谱各波谱段的反射特性；1980年以来国内外基于雷达和光学遥感数据提取水体信息的研究状况和具体应用方向；各种水体信息提取方法的工作原理和优缺点；应用卫星遥感技术提取水体信息面临的挑战和尚待解决的关键问题，利用遥感技术提取水体遥感信息的发展趋势展望。
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唐启强, 张智, 黄潮清, 等. 基于GIS的南昌县血吸虫病疫情聚集区域综合探测研究[J]. 中国血吸虫病防治杂志, 2012(5): 518-521.
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To explore the cluster of schistosomiasis in Nanchang County, Jiangxi Province.Based on the data of schistosome infection cases and population, the spatial analysis technology, global autocorrelation and hotspot detection methods in ArcGIS 9.2 software were used to render the spatial autocorrelation coefficient graph. The autocorrelation index change trend of schistosome infection rates in different spatial scales was described. In addition, the hotspot area of schistosome infection rates in study area was detected by using the representative distance for pace parameters combined with actual situation.The spatial distribution of schistosome infection in study area was characteristic of clusters in 2009. The spatial autocorrelation coefficient graph indicated that the peak of wave happened in the distances of 1 900 m, 2 600 m, 3 800 m and 5 000 m, respectively. Comparing with the geographical conditions, the hotspots in 5 000 m spatial scale were more realistic than other distances. In this scale, 2 hotspots and 2 second hotspots were explored.The spatial clustering analysis combined with the spatial autocorrelation analysis can explore the schistosomiasis gathering area more precisely.
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刘璐, 施学文, 毛桂林, 等. 2005—2012年云南省洱源县钉螺时空分布特征分析[J]. 中国血吸虫病防治杂志, 2016(2): 120-124.
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To study the spatial and temporal characteristics of in Eryuan County, Yunnan Province from 2005 to 2012, so as to provide the scientific evidence for snail surveillance and control.Based on the geographic database of snail distribution from 2005 to 2012, the spatial and local autocorrelation analysis and "hot spots" analysis were applied to analyze the spatial and temporal characteristics of the snails.Percent of frames with snails in Eryuan County decreased as a whole from 2005 to 2012. The spatial clustering of global autocorrelation (Moran's ) was increasing from 2007 to 2012 and all Moran's values showed statistically significance. The local spatial autocorrelation analysis indicated that the number of villages of High-High type of correlation model increased from 2 in 2005 to 7 in 2012, which mainly clustered in plateau canyon areas. The infected snails with High-High type mainly distributed in plateau basin region in 2007. Further "hot spot" analysis found that the living snails gathered in Xinzhuang, Liantie, Xipo and Taiping nearby areas.The snail distribution in Eryuan has global and local spatial autocorrelations. The number of villages of High-High type of correlation increased. These findings provide the basis for target control of in the future.
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