The spatio-temporal distribution of Oncomelania hupensis along Yangtze river in Jiangsu Province, China after implementation of a new, integrated schistosomiasis control strategy

Jiang, He; Li, Wei; Bergquist, Robert; Zhang, Jianfeng; Shi, Liang; Song, Zhao; Wu, Feng; Yang, Kun

doi:10.4081/gh.2016.480

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…A large number of public health problems have been analysed with the geographic information system (GIS) and spatial statistics (Wang et al ., 2016; Gomes et al, 2018 ). Depending entirely on the distribution of the intermediate snail host O. hupensis , schistosomiasis is reported to demonstrate temporal and spatial variations in geographic distribution (Sun et al ., 2015; He et al ., 2016; Li et al ., 2018; Niu et al ., 2018). Considering the spatial variation of schistosomiasis, its prevalence and spatial distribution can be accurately analysed by GIS.…”

Section: Introductionmentioning

confidence: 99%

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

Chen¹,

Li²,

Xiao³

et al. 2019

Parasitology

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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.

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Section: Introductionmentioning

confidence: 99%

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

Chen¹,

Li²,

Xiao³

et al. 2019

Parasitology

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“…The migration and diffusion behaviors of Oncomelania snails are complex because they are related not only to the physical properties of the snails, including the geometry and density of their bodies, but also to water flow and meteorological conditions and are further affected by the survival activities of the snails (Belizario et al, 2017). Yang et al (2005), He et al, 2016 andZhang et al (2004) studied the settlement and incipient motion of Oncomelania snails in laboratory flumes and proposed formulas for the settling velocity and incipient velocity. Field surveys and sampling have commonly been used to explore the spatiotemporal distribution patterns of Oncomelania snails in the Changjiang River basin (Liu et al, 2011;Liu, 2013) and to assess the effect of various water projects, such as water system connection projects and water diversion projects, on snail migration and diffusion (Perez Saez et al, 2016;Hu et al, 2017;Hu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of the Oncomelania snails transport attached to floating objects under different wind conditions

Zhang,

Zhou,

Jin

et al. 2024

Front. Ecol. Evol.

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The long-distance migration of Oncomelania snails mainly occurs by attaching to floating objects during floods. However, the processes, characteristics and effects of migration are not fully understood. Here, a motion equation for floating objects with attached Oncomelania snails was constructed using the Lagrangian method. The equation can be numerically solved to simulate the movement of floating objects after parameter calibration. Then, the calibrated parameters were used to simulate the migration of Oncomelania snails in the lower Jingjiang River, where they had spread over a large area. The effects of flood conditions on the migration and spread of Oncomelania snails have been studied to a certain extent, but the impact of wind conditions on snail migration has rarely been reported. Therefore, based on the distribution of Oncomelania snails in China, the difficulties and key areas for the control of schistosomiasis and Oncomelania snails, and the morphological characteristics of the river reach, the Lower Jingjiang River section was selected as a practical application case. A theoretical model of the migration and spread of Oncomelania snails was established, and the characteristics of the Oncomelania snail migration were simulated and analyzed based on flood and distribution patterns under different wind conditions. The results indicate that wind conditions have little influence on the longitudinal spreading of Oncomelania snails but have a relatively large influence on the lateral spreading of snails. Compared with calm wind conditions, both northeasterly and southerly wind conditions can lead to longer longitudinal migration distances of snails, thereby increasing the risk of snail spreading and schistosomiasis transmission.

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“…Fortunately, spatial information technology, e.g., geographic information systems (GIS) and global positioning systems (GPS), have powerful spatial data management and analysis capacities that offer spatial information on snail distribution and related environmental factors, which can then be visualized [ 26 ]. In addition, aside from mapping the spatial distribution of O. hupensis and its related environmental factors to master geographical distribution characteristics, various studies with respect to spatial correlations, clusters, predictions of snail breeding areas, and snail monitoring in part of an area have been carried out [ 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

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

Deng

et al. 2023

TropicalMed

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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.

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The spatio-temporal distribution of Oncomelania hupensis along Yangtze river in Jiangsu Province, China after implementation of a new, integrated schistosomiasis control strategy

Cited by 4 publications

References 14 publications

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

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

Numerical simulation of the Oncomelania snails transport attached to floating objects under different wind conditions

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

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