[Progresses of research on patterns and monitoring approaches of Oncomelania hupensis spread]

Single-target detection of Oncomelania hupensis based on improved YOLOv5s

To address the issues of low detection accuracy and poor effect caused by small Oncomelania hupensis data samples and small target sizes. This article proposes the O. hupensis snails detection algorithm, the YOLOv5s-ECA-vfnet based on improved YOLOv5s, by using YOLOv5s as the basic target detection model and optimizing the loss function to improve target learning ability for specific regions. The experimental findings show that the snail detection method of the YOLOv5s-ECA-vfnet, the precision (P), the recall (R) and the mean Average Precision (mAP) of the algorithm are improved by 1.3%, 1.26%, and 0.87%, respectively. It shows that this algorithm has a good effect on snail detection. The algorithm is capable of accurately and rapidly identifying O. hupensis snails on different conditions of lighting, sizes, and densities, and further providing a new technology for precise and intelligent investigation of O. hupensiss snails for schistosomiasis prevention institutions.

Molecular evidence on the presence of Schistosoma japonicum infection in snails along the Yangtze River, 2015-2019

Background

Due to sustained control activities, the prevalence of Schistosoma japonicum infection in humans, livestock and snails has decreased significantly in P. R. China, and the target has shifted from control to elimination according to the Outline of Healthy China 2030 Plan. Applying highly sensitive methods to explore the presence of S. japonicum infection in its intermediate host will benefit to assess the endemicity or verify the transmission interruption of schistosomiasis accurately. The aim of this study was to access the presence of S. japonicum infection by a loop-mediated isothermal amplification (LAMP) method through a 5-year longitudinal study in five lake provinces along the Yangtze River.

Methods

Based on previous epidemiological data, about 260 villages with potential transmission risk of schistosomiasis were selected from endemic counties in five lake provinces along the Yangtze River annually from 2015 to 2019. Snail surveys were conducted in selected villages by systematic sampling method and/or environmental sampling method each year. All live snails collected from field were detected by microscopic dissection method, and then about one third of them were detected by LAMP method to assess the presence of S. japonicum infection with a single blind manner. The infection rate and nucleic acid positive rate of schistosomes in snails, as well as the indicators reflecting the snails’ distribution were calculated and analyzed. Fisher's exact test was used to examine any change of positive rate of schistosomes in snails over time.

Results

The 5-year survey covered 94,241 ha of environment with 33,897 ha of snail habitats detected accumulatively. Totally 145.3 ha new snail habitats and 524.4 ha re-emergent snail habitats were found during 2015–2019. The percentage of frames with snails decreased from 5.93% [45,152/761,492, 95% confidence intervals (CI): 5.88–5.98%] in 2015 to 5.25% (30,947/589,583, 95% CI: 5.19–5.31%) in 2019, while the mean density of living snails fluctuated but presented a downward trend generally from 0.20 snails/frame (155,622/761,492, 95% CI: 0.17–0.37) in 2015 to 0.13 snails/frame (76,144/589,583, 95% CI: 0.11–0.39) in 2019. A total of 555,393 live snails were collected, none of them was positive by dissection method. Totally 17 pooling snail samples were determined as positives by LAMP method among 8716 pooling samples with 174,822 of living snails, distributed in 12 villages of Hubei, Hunan, Jiangxi and Anhui provinces. The annual average positive rate was 0.41% (95% CI: 0.13–0.69%) in 2015, 0% in 2016, 0.36% (95% CI: 0.09–0.63%) in 2017, 0.05% (95% CI: 0–0.16%) in 2018, 0.05% (95% CI: 0–0.15%) in 2019, respectively, presenting a downward trend from 2015 to 2019 with statistical significance (χ² = 11.64, P < 0.05).

Conclusions

The results suggest that S. japonicum infection still persisted in nature along the Yangtze River and traditional techniques might underestimate the prevalence of schistosomiasis in its intermediate hosts. Exploring and integrating molecular techniques into national surveillance programme could improve the sensitivity of surveillance system and provide guidance on taking actions against schistosomiasis.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00995-9.

Infestation risk of the intermediate snail host of Schistosoma japonicum in the Yangtze River Basin: improved results by spatial reassessment and a random forest approach

BACKGROUND

Oncomelania hupensis is only intermediate snail host of Schistosoma japonicum, and distribution of O. hupensis is an important indicator for the surveillance of schistosomiasis. This study explored the feasibility of a random forest algorithm weighted by spatial distance for risk prediction of schistosomiasis distribution in the Yangtze River Basin in China, with the aim to produce an improved precision reference for the national schistosomiasis control programme by reducing the number of snail survey sites without losing predictive accuracy.

METHODS

The snail presence and absence records were collected from Anhui, Hunan, Hubei, Jiangxi and Jiangsu provinces in 2018. A machine learning of random forest algorithm based on a set of environmental and climatic variables was developed to predict the breeding sites of the O. hupensis intermediated snail host of S. japonicum. Different spatial sizes of a hexagonal grid system were compared to estimate the need for required snail sampling sites. The predictive accuracy related to geographic distances between snail sampling sites was estimated by calculating Kappa and the area under the curve (AUC).

RESULTS

The highest accuracy (AUC = 0.889 and Kappa = 0.618) was achieved at the 5 km distance weight. The five factors with the strongest correlation to O. hupensis infestation probability were: (1) distance to lake (48.9%), (2) distance to river (36.6%), (3) isothermality (29.5%), (4) mean daily difference in temperature (28.1%), and (5) altitude (26.0%). The risk map showed that areas characterized by snail infestation were mainly located along the Yangtze River, with the highest probability in the dividing, slow-flowing river arms in the middle and lower reaches of the Yangtze River in Anhui, followed by areas near the shores of China's two main lakes, the Dongting Lake in Hunan and Hubei and the Poyang Lake in Jiangxi.

CONCLUSIONS

Applying the machine learning of random forest algorithm made it feasible to precisely predict snail infestation probability, an approach that could improve the sensitivity of the Chinese schistosome surveillance system. Redesign of the snail surveillance system by spatial bias correction of O. hupensis infestation in the Yangtze River Basin to reduce the number of sites required to investigate from 2369 to 1747.

Distribution Patterns of the Snail Intermediate Host of Schistosoma japonicum- China, 2015-2019

What is already known about this topic?

The endemic status of schistosomiasis appeared to continuously decrease in China from 2015 to 2019. The snail species Oncomelania hupensis is the only intermediate host involved in the transmission of Schistosoma japonicum, and this snail’s geographic distribution is strictly consistent with that of schistosomiasis.

What is added by this report?

The snail’s habitats did not decrease significantly in China from 2015 to 2019, and some habitats have been newly detected or recurrent in some regions. Snail habitats among nine counties in Hunan and Jiangxi covered nearly half of the areas with snails.

What are the implications for public health practice?

Considering the situation of snail distribution, strategies and measures on snail control should focus on key areas. In addition, study of the origin and causes of the newly-detected snail habitats and recurrent areas with snails needs to be strengthened, and comprehensive measures should be taken to prevent the spread of snails.