Distribution pattern of the snail intermediate host of schistosomiasis japonica in the Poyang Lake region of China

From Perpetual Wetness to Soil Chemistry: Enumerating Environmental and Physicochemical Factors Favoring Oncomelania hupensis quadrasi Snail Presence in the Municipality of Gonzaga, Cagayan, Philippines

Snail control to complement mass drug administration is being promoted by the World Health Organization for schistosomiasis control. Oncomelania hupensis quadrasi, the snail intermediate host of Schistosoma japonicum in the Philippines, has a very focal distribution; thus, scrutinizing baseline data and parameters affecting this distribution is very crucial. In this study in Gonzaga, Cagayan, Philippines, snail habitats were surveyed, and the various factors affecting the existence of the snails were determined. Malacological surveys and the mapping of sites of perpetual wetness in five endemic and five neighboring non-endemic barangays were conducted. Environmental and physicochemical factors were also examined. Maps of both snail and non-snail sites were generated. Of the fifty sites surveyed, O. h. quadrasi were found in twelve sites, and two sites yielded snails that were infected with S. japonicum cercariae. Factors such as silty loam soil, proximity to a snail site, water ammonia, and soil attributes (organic matter, iron, and pH) are all significantly associated with the presence of snails. In contrast, types of habitats, temperatures, and soil aggregation have no established association with the existence of snails. Mapping snail sites and determining factors favoring snail presence are vital to eliminating snails. These approaches will significantly maximize control impact and minimize wasted efforts and resources, especially in resource-limited schistosomiasis endemic areas.

Impact of the National Wetland Park in the Poyang Lake Area on Oncomelania hupensis, the Intermediate Host of Schistoma japonicum

In this study, we aimed to understand the influence of ecotourism on the distribution of Oncomelania hupensis and to provide a scientific basis for formulating effective snail control methods in tourism development areas. Poyang Lake National Wetland Park was selected as the pilot area, and sampling surveys were conducted based on comprehensive and detailed investigations of all historical and suspected snail environments according to map data to determine the snail distribution and analyze the impact of tourism development. The results showed that from 2011 to 2021, the positive rates of blood tests and fecal tests tended to decrease among residents of the Poyang Lake area. The positive rates of blood tests and fecal tests in livestock also tended to decrease. The average density of O. hupensis snails decreased, and no schistosomes were detected during infection monitoring in Poyang Lake. The local economy rapidly grew after the development of tourism. The development of ecotourism projects in Poyang Lake National Wetland Park increased the transfer frequency of boats, recreational equipment, and people, but it did not increase the risk of schistosomiasis transmission or the spread of O. hupensis snails. Prevention and monitoring only need to be strengthened in low-endemic schistosomiasis areas to effectively promote economic development due to tourism activities without affecting the health of residents.

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

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.

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

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

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05496-0.

Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt

BACKGROUND

Schistosomiasis control is striving forward to transmission interruption and even elimination, evidence-lead control is of vital importance to eliminate the hidden dangers of schistosomiasis. This study attempts to identify high risk areas of schistosomiasis in China by using information value and machine learning.

METHODS

The local case distribution from schistosomiasis surveillance data in China between 2005 and 2019 was assessed based on 19 variables including climate, geography, and social economy. Seven models were built in three categories including information value (IV), three machine learning models [logistic regression (LR), random forest (RF), generalized boosted model (GBM)], and three coupled models (IV + LR, IV + RF, IV + GBM). Accuracy, area under the curve (AUC), and F1-score were used to evaluate the prediction performance of the models. The optimal model was selected to predict the risk distribution for schistosomiasis.

RESULTS

There is a more prone to schistosomiasis epidemic provided that paddy fields, grasslands, less than 2.5 km from the waterway, annual average temperature of 11.5-19.0 °C, annual average rainfall of 1000-1550 mm. IV + GBM had the highest prediction effect (accuracy = 0.878, AUC = 0.902, F1 = 0.920) compared with the other six models. The results of IV + GBM showed that the risk areas are mainly distributed in the coastal regions of the middle and lower reaches of the Yangtze River, the Poyang Lake region, and the Dongting Lake region. High-risk areas are primarily distributed in eastern Changde, western Yueyang, northeastern Yiyang, middle Changsha of Hunan province; southern Jiujiang, northern Nanchang, northeastern Shangrao, eastern Yichun in Jiangxi province; southern Jingzhou, southern Xiantao, middle Wuhan in Hubei province; southern Anqing, northwestern Guichi, eastern Wuhu in Anhui province; middle Meishan, northern Leshan, and the middle of Liangshan in Sichuan province.

CONCLUSIONS

The risk of schistosomiasis transmission in China still exists, with high-risk areas relatively concentrated in the coastal regions of the middle and lower reaches of the Yangtze River. Coupled models of IV and machine learning provide for effective analysis and prediction, forming a scientific basis for evidence-lead surveillance and control.

Impact of micro-environmental factors on survival, reproduction and distribution of Oncomelania hupensis snails

Background

Schistosomiasis japonica is a chronic parasitic disease that seriously harms people's health. Oncomelania hupensis is the only intermediate host of Schistosoma japonicum. The micro-environmental factors surrounding the snail have a great impact on the survival, growth and reproduction of O. hupensis, but there are few relevant systematic analyses until the present. This scoping review aims to identify and summarize the micro-environmental factors that greatly affect O. hupensis, and to find gaps in research thus to provide directions for future in-depth studies.

Main body

This scoping review searched databases with search terms of the combinations of “Micro(-)environment”, “Oncomelania” and their expanded aspects. A total of 133 original articles were recruited. Predefined data fields were extracted including research methods, influencing factors, and their effects on O. hupensis. Most studies focused on vegetation factors (54.1%), and other factors noted were soil composition (27.8%), water environmental factors (24.1%), and predator (3.0%), respectively. The factors with positive impacts included water level, pH value, soil temperature, soil humidity, the coverage and height of vegetation at suitable levels. This could provide more detailed information for O. hupensis habitat identification and prediction. The factors with negative impacts included plant extracts, snail control and disease prevention forests, and microorganisms with molluscicidal activities. It revealed a potential application as ecological molluscicides in the future. Factors such as physico-chemical properties of water, soil chemistry showed a gap in scientific studies, thus required further extensive research.

Conclusions

Micro-environmental factors including water quality, soil composition as well as the technology and application of biomolluscicides (plant extracts and microorganisms) deserve more attention. Relative study findings on micro-environment have good potentials in snail control applications. Further studies should be implemented to investigate the impact of micro-environmental factors on snails and close the research gaps.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00826-3.

Assessment of the Transmission Risk of Schistosomiasis after Flooding - North Poyang Lake, Jiangxi Province, China, 2020

What is already known about this topic?

Over 90% of Oncomelania snails, the only intermediate host of Schistosoma japonicum, are distributed in the middle and low reaches of Yangtze River. Flooding can extend the distribution of Oncomelania snails and hence accelerate the transmission of schistosomiasis.

What is added by this report?

Although the dispersal of Oncomelania snails was negligible in north Poyang Lake after flooding in 2020, 2 samples of cattle feces with Schistosoma egg and 2 infected snails samples were indeed found. All four risk sites were distributed in Lushan County. Cattle feces were observed in the six out of seven field sites in Lushan County.

What are the implications for public health practice?

The present national control strategy focusing on control of infection source should be reinforced in Lushan and other schistosomiasis endemic areas. Overlaps of infected snails and cattle feces with Schistosoma egg were not observed, which called for intensive surveillance in Lushan County.

Impact of continuous low water stage on the breeding environment of Oncomelania hupensis: a case study of Poyang Lake area in China

BACKGROUND

Oncomelania hupensis is the only intermediate host of Schistosoma japonicum and plays a decisive role in its transmission. The variation of water level greatly affects the reproduction and growth of snails. Therefore, in this paper, we analyze the variations of water level in the Poyang Lake region from 1993 to 2016 combined with satellite imagery to elucidate the evolution of the snail breeding environment.

METHODS

By employing remote sensing data from 1993 to 2016 (April-June and September-November), the vegetation area of Poyang Lake and the vegetation area at different elevations were extracted and calculated. Moreover, the average daily water level data from the four hydrological stations (Hukou station, Xingzi station, Tangyin station and Kangshan station) which represent the typical state of Poyang Lake were collected from 1993 to 2016. The variance of the monthly mean water level, inundation time and the average area were analyzed by variance to find a significance level of α = 0.05.

RESULTS

According to hydrological data before and after 2003, the average water level after 2003 is significantly lower than that before 2003 in Poyang Lake. After 2003, the time of inundateing the snail breeding period was later in April to June than that before 2003, while the time of wate-falling stage in September to November moved forward after 2003 than before 2003. Of them, the lowest water level affecting the breeding and growing period of O. hupensis in the northern part of Poyang Lake decreased from 11 m to 9 m. After 2003, the expansion of meadow area in the north part of Poyang Lake was mainly concentrated in the elevation of 9-11 m, and the newly increased infested-meadow in the lake area was mainly concentrated in the north part of Poyang Lake.

CONCLUSIONS

By comparing the change of water level characteristics in different parts of the Poyang Lake area as well as changes in meadow area before and after 2003, it is found that the water level changes mainly affect the snail breeding area in the northern part of Poyang Lake. The results are helpful for improving scientific measures for snail control in Jiangxi Province. This approach could also be applicible to Dongting Lake area and other lake areas affected by water level changes and can bring significant guidance for snail control in lake areas.

Risk prediction of two types of potential snail habitats in Anhui Province of China: Model-based approaches

Elimination of the intermediate snail host of Schistosoma is the most effective way to control schistosomiasis and the most important first step is to accurately identify the snail habitats. Due to the substantial resources required for traditional, manual snail-searching in the field, and potential risk of miss-classification of potential snail habitats by remote sensing, more convenient and precise methods are urgently needed. Snail data (N = 15,000) from two types of snail habitats (lake/marshland and hilly areas) in Anhui Province, a typical endemic area for schistosomiasis, were collected together with 36 environmental variables covering the whole province. Twelve different models were built and evaluated with indices, such as area under the curve (AUC), Kappa, percent correctly classified (PCC), sensitivity and specificity. We found the presence-absence models performing better than those based on presence-only. However, those derived from machine-learning, especially the random forest (RF) approach were preferable with all indices above 0.90. Distance to nearest river was found to be the most important variable for the lake/marshlands, while the climatic variables were more important for the hilly endemic areas. The predicted high-risk areas for potential snail habitats of the lake/marshland type exist mainly along the Yangtze River, while those of the hilly type are dispersed in the areas south of the Yangtze River. We provide here the first comprehensive risk profile of potential snail habitats based on precise examinations revealing the true distribution and habitat type, thereby improving efficiency and accuracy of snail control including better allocation of limited health resources.

Obtaining elevation of Oncomelania Hupensis habitat based on Google Earth and it's accuracy evaluation: an example from the Poyang lake region, China

Schistosomiasis japonicum is a major zoonosis that seriously harms human health and affects social and economic development in China. The control of Oncomelania Hupensis, the only intermediate host of schistosome japonicum, is one of the integrated measures for schistosomiasis control in China. Acquiring updated elevation data of snail habitat environment, as well as it's spatial analysis, play an important role for the risk evaluation and precise control of schistosomiasis transmission and prevalence. Currently, the elevation database of snail habitat environment in schistosomiasis epidemic areas has not been available in the world, which affects the development of research and application work regarding to snail control. Google Earth(GE) can provide massive information related to topography, geomorphology and ground objects of a region due to its indisputable advantages such as wide use, free charge and rapidly updating. In this paper, taking the Poyang lake region as a example, we extracted elevation data of snail-inhabited environment of the lake from GE and established a elevation correction regression model(CRM) for acquiring accurate geospatial elevations, so as to provide a decision-making reference for snail control and risk evaluation of schistosomiasis in China. We developed a GE Application Programming Interface(API) program to extract elevation data from GE, which was compared with the actual elevation data obtained from topographic map of the Poyang Lake bottom. Then, a correction regression model was established and evaluated by 3 index, Mean Absolute Error(MAE), Root Mean Squared Error(RMSE) and Index of Agreement(IOA) for the accuracy of the model. The elevation values extracted from GE in 15086 sample grid points of the lake ranged from 8.5 m to 24.8 m. After the sample points were divided randomly to three groups, the mean elevations of three groups were 13.49 m, 13.52 m and 13.65 m, respectively, with standard deviation ranged from 2.04-2.06. The mean elevation among three groups has no statistic difference (F = 1.536, P = 0.215). A elevation correction regression model was established as y = 6.228 + 0.485×. the evaluation results for the accuracy of the model showed that the MAE and RMSE before correction was 1.28 m and 3.95 m respectively, higher than that after correction, which were 0.74 and 1.30 m correspondingly. The IOA before correction (-0.40)was lower than that after correction(0.34). Google Earth can directly or indirectly get access to massive information related to topography, geomorphology and ground objects due to its indisputable advantages. However, it still needs to be converted into more reliable and accurate data by combining with pre-processing tools. This study used self-developed API program to extract elevation data from GE through precisely locating and improved the accuracy of elevation by using a correction regression model, which can provide reliable data sources for all kinds of spatial data researches and applications.