[Endemic status of schistosomiasis in People's Republic of China in 2020]

Occurrence of pentachlorophenol in surface water from the upper to lower reaches of the Yangtze River and treated water in Wuhan, China

Pentachlorophenol (PCP), a persistent organic pollutant, has been banned in many countries, but it is still used in China as a wood preservative, molluscicide, or reagent for fish-pond cleaning, which may pose risks to the ecosystem and humans. However, data on the occurrence of PCP in the environment are scarce in the recent decade. The Yangtze River was regarded as a priority area of PCP pollution according to previous documents. This study aimed to examine the spatial distribution of PCP in the Yangtze River water, the differences in dry and wet seasons, the ecological risk for aquatic organisms, and its removal efficiency in tap water treatment plants. The river water samples (n = 144) were collected from the upper, middle, and lower reaches across ten provinces (or municipalities) in December 2020 and June 2021, respectively. PCP was detected in 88.9% of all the samples, ranging from  Collapse

Key Words

• Pentachlorophenol
• Removal
• Seasonal difference
• Spatial variations
• Surface water
• Yangtze River

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MESH Headings

• Humans
• Animals
• Pentachlorophenol/analysis
• Ecosystem
• Water Pollutants, Chemical/analysis
• Environmental Monitoring
• Rivers
• Cities
• China
• Risk Assessment
• Aquatic Organisms

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Grants

• WJ2019H307 Health Commission of Hubei Province
• WJ2019H303 Health Commission of Hubei Province
• 42277428 National Natural Science Foundation of China
• 21407117 National Natural Science Foundation of China

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Affiliation(s)

Fengting Yang Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, 430030, Hubei, China
Yanjian Wan Center for Public Health Laboratory Service, Institute of Environmental Health, Wuhan Centers for Disease Prevention & Control, Wuhan, Hubei, 430024, People's Republic of China
Yan Wang Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, 430030, Hubei, China
Shulan Li Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, 430030, Hubei, China
Shunqing Xu Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, 430030, Hubei, China
Wei Xia Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan, 430030, Hubei, China.

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Unraveling trends in schistosomiasis: deep learning insights into national control programs in China

OBJECTIVES

To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China.

METHODS

We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS).

RESULTS

The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1,000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1,000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease.

CONCLUSIONS

The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Alterations in gut microbiome and metabolite profile of patients with Schistosoma japonicum infection

BACKGROUND

Schistosoma infection is a significant public health issue, affecting over 200 million individuals and threatening 700 million people worldwide. The species prevalent in China is Schistosoma japonicum. Recent studies showed that both gut microbiota and metabolome are closely related to schistosomiasis caused by S. japonicum, but clinical study is limited and the underlying mechanism is largely unclear. This study aimed to explore alterations as well as function of gut microbiota and metabolite profile in the patients with S. japonicum infection.

METHODS

This study included 20 patients diagnosed with chronic schistosomiasis caused by S. japonicum, eight patients with advanced schistosomiasis caused by S. japonicum and 13 healthy volunteers. The fresh feces of these participators, clinical examination results and basic information were collected. 16S ribosomal RNA gene sequencing was used to investigate gut microbiota, while ultraperformance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to explore the metabolome of patients in different stages of schistosomiasis.

RESULTS

The study found that gut microbiota and metabolites were altered in patients with different stages of S. japonicum infection. Compared with healthy control group, the gut microbial diversity in patients with chronic S. japonicum infection was decreased significantly. However, the diversity of gut microbiota in patients with chronic schistosomiasis was similar to that in patients with advanced schistosomiasis. Compared with uninfected people, patients with schistosomiasis showed decreased Firmicutes and increased Proteobacteria. As disease progressed, Firmicutes was further reduced in patients with advanced S. japonicum infection, while Proteobacteria was further increased. In addition, the most altered metabolites in patients with S. japonicum infection were lipids and lipid-like molecules as well as organo-heterocyclic compounds, correlated with the clinical manifestations and disease progress of schistosomiasis caused by S. japonicum.

CONCLUSIONS

This study suggested that the gut microbiota and metabolome altered in patients in different stages of schistosomiasis, which was correlated with progression of schistosomiasis caused by S. japonicum. This inter-omics analysis may shed light on a better understanding of the mechanisms of the progression of S. japonicum infection and contribute to identifying new potential targets for the diagnosis and prognosis of S. japonicum infection. However, a large sample size of validation in clinic is needed, and further study is required to investigate the underlying mechanism.

Prevalence trend and burden of neglected parasitic diseases in China from 1990 to 2019: findings from global burden of disease study

Objective

This study sought to investigate the parasitic diseases of neglected tropical diseases defined by the World Health Organization based on the Global Burden of Disease Study (GBD) database. Importantly, we analyzed the prevalence and burden of these diseases in China from 1990 to 2019 to provide valuable information to formulate more effective measures for their management and prevention.

Methods

Data on the prevalence and burden of neglected parasitic diseases in China from 1990 to 2019 were extracted from the global health data exchange (GHDx) database, including the absolute number of prevalence, age-standardized prevalence rate, disability-adjusted life year (DALY) and age-standardized DALY rate. Descriptive analysis was used to analyze the prevalence and burden changes, sex and age distribution of various parasitic diseases from 1990 to 2019. A time series model [Auto-Regressive Integrated Moving Average (ARIMA)] was used to predict the DALYs of neglected parasitic diseases in China from 2020 to 2030.

Results

In 2019, the number of neglected parasitic diseases in China was 152518062, the age-standardized prevalence was 11614.1 (95% uncertainty interval (UI) 8758.5-15244.5), the DALYs were 955722, and the age-standardized DALY rate was 54.9 (95% UI 26.0-101.8). Among these, the age-standardized prevalence of soil-derived helminthiasis was the highest (9370.2/100,000), followed by food-borne trematodiases (1502.3/100,000) and schistosomiasis (707.1/100,000). The highest age-standardized DALY rate was for food-borne trematodiases (36.0/100,000), followed by cysticercosis (7.9/100,000) and soil-derived helminthiasis (5.6/100,000). Higher prevalence and disease burden were observed in men and the upper age group. From 1990 to 2019, the number of neglected parasitic diseases in China decreased by 30.4%, resulting in a decline in DALYs of 27.3%. The age-standardized DALY rates of most diseases were decreased, especially for soil-derived helminthiasis, schistosomiasis and food-borne trematodiases. The ARIMA prediction model showed that the disease burden of echinococcosis and cysticercosis exhibited an increasing trend, highlighting the need for further prevention and control.

Conclusion

Although the prevalence and disease burden of neglected parasitic diseases in China have decreased, many issues remain to be addressed. More efforts should be undertaken to improve the prevention and control strategies for different parasitic diseases. The government should prioritize multisectoral integrated control and surveillance measures to prioritize the prevention and control of diseases with a high burden of disease. In addition, the older adult population and men need to pay more attention.

Sentinel Surveillance of Schistosomiasis - China, 2021

Introduction

This report analyzes the national surveillance data for schistosomiasis in 2021 to understand the current status and provide evidence for further policy actions to promote elimination. This analysis is in line with the National Surveillance Plan of Schistosomiasis, which was revised in 2020 to adapt to the new stage of moving towards elimination.

Methods

Data from the 2021 national surveillance of schistosomiasis in humans, livestock, and snails were collected from 13 provincial-level administrative divisions (PLADs) and analyzed using descriptive epidemiological methodology. The antibody-positive rate and area of newly discovered and re-emergent snail habitats were calculated.

Results

In 2021, a total of 31,661 local residents and 101,558 transient population were screened for antibodies using indirect hemagglutination assay (IHA). Of those who tested positive, 745 local residents and 438 transient population underwent further parasitological examination, with only one stool-positive result in the transient population. Additionally, 12,966 livestock were examined using the miracidia hatching test, with no positives detected. The total area of newly discovered and re-emergent snail habitats was 957,702 m² and 4,381,617 m², respectively. No infected snails were found using the microscopic dissection method, but six pooled snail samples were reported as positive using the loop-mediated isothermal amplification method for detecting specific sequences of Schistosoma. japonicum, in Anhui and Jiangxi Provinces.

Conclusions

The prevalence of schistosomiasis among humans and livestock was found to be low, however, a potential transmission risk was identified in certain areas. To reduce the risk of transmission, a comprehensive control strategy should be continued and new techniques should be implemented in the surveillance and early warning system.

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.

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.

Identifying the Determinants of Distribution of Oncomelania hupensis Based on Geographically and Temporally Weighted Regression Model along the Yangtze River in China

Background: As the unique intermediate host of Schistosoma japonicum, the geographical distribution of Oncomelania hupensis (O. hupensis) is an important index in the schistosomiasis surveillance system. This study comprehensively analyzed the pattern of snail distribution along the Yangtze River in Jiangsu Province and identified the dynamic determinants of the distribution of O. hupensis. Methods: Snail data from 2017 to 2021 in three cities (Nanjing, Zhenjiang, and Yangzhou) along the Yangtze River were obtained from the annual cross-sectional survey produced by the Jiangsu Institute of Parasitic Diseases. Spatial autocorrelation and hot-spot analysis were implemented to detect the spatio–temporal dynamics of O. hupensis distribution. Furthermore, 12 factors were used as independent variables to construct an ordinary least squares (OLS) model, a geographically weighted regression (GWR) model, and a geographically and temporally weighted regression (GTWR) model to identify the determinants of the distribution of O. hupensis. The adjusted coefficients of determination (adjusted R², AICc, RSS) were used to evaluate the performance of the models. Results: In general, the distribution of O. hupensis had significant spatial aggregation in the past five years, and the density of O. hupensis increased eastwards in the Jiangsu section of the lower reaches of the Yangtze River. Relatively speaking, the distribution of O. hupensis wase spatially clustered from 2017 to 2021, that is, it was found that the border between Yangzhou and Zhenjiang was the high density agglomeration area of O. hupensis snails. According to the GTWR model, the density of O. hupensis was related to the normalized difference vegetation index, wetness, dryness, land surface temperature, elevation, slope, and distance to nearest river, which had a good explanatory power for the snail data in Yangzhou City (adjusted R² = 0.7039, AICc = 29.10, RSS = 6.81). Conclusions: The distribution of O. hupensis and the environmental factors in the Jiangsu section of the lower reaches of the Yangtze River had significant spatial aggregation. In different areas, the determinants affecting the distribution of O. hupensis were different, which could provide a scientific basis for precise prevention and control of O. hupensis. A GTWR model was prepared and used to identify the dynamic determinants for the distribution of O. hupensis and contribute to the national programs of control of schistosomiasis and other snail-borne diseases.

Potential Gut Microbiota Features for Non-Invasive Detection of Schistosomiasis

The gut microbiota has been identified as a predictive biomarker for various diseases. However, few studies focused on the diagnostic accuracy of gut microbiota derived-signature for predicting hepatic injuries in schistosomiasis. Here, we characterized the gut microbiomes from 94 human and mouse stool samples using 16S rRNA gene sequencing. The diversity and composition of gut microbiomes in Schistosoma japonicum infection-induced disease changed significantly. Gut microbes, such as Bacteroides, Blautia, Enterococcus, Alloprevotella, Parabacteroides and Mucispirillum, showed a significant correlation with the level of hepatic granuloma, fibrosis, hydroxyproline, ALT or AST in S. japonicum infection-induced disease. We identified a range of gut bacterial features to distinguish schistosomiasis from hepatic injuries using the random forest classifier model, LEfSe and STAMP analysis. Significant features Bacteroides, Blautia, and Enterococcus and their combinations have a robust predictive accuracy (AUC: from 0.8182 to 0.9639) for detecting liver injuries induced by S. japonicum infection in humans and mice. Our study revealed associations between gut microbiota features and physiopathology and serological shifts of schistosomiasis and provided preliminary evidence for novel gut microbiota-derived features for the non-invasive detection of schistosomiasis.

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.

Genome-Wide Association Study Identifies New Risk Loci for Progression of Schistosomiasis Among the Chinese Population

Schistosoma japonicum infections, which lead to local inflammatory responses to schistosome eggs trapped in host tissues, can result in long-term, severe complications. The development of schistosomiasis may result from a complex interaction between the pathogenic, environmental, and host genetic components. Notably, the genetic factors that influence the development of schistosomiasis complications are poorly understood. Here we performed a genome-wide association study on multiple schistosomiasis-related phenotypes of 637 unrelated schistosomiasis patients in the Chinese population. Among three indicators of liver damage, we identified two novel, genome-wide significant single-nucleotide polymorphisms (SNPs) rs34486793 (P = 1.415 × 10^-8) and rs2008259 (P = 6.78 × 10^-8) at locus 14q32.2 as well as a gene, PMEPA1, at 20q13.31 (index rs62205791, P = 6.52 × 10^-7). These were significantly associated with serum levels of hyaluronic acid (HA). In addition, RASIP1 and MAMSTR at 19q13.33 (index rs62132778, P = 1.72 × 10^-7) were significantly associated with serum levels of aspartate aminotransferase (AST), and TPM1 at 15q22.2 (index rs12442303, P = 4.39 × 10^-7) was significantly associated with serum levels of albumin. In schistosomiasis clinical signs, ITIH4 at 3p21.1 (index rs2239548) was associated with portal vein diameter (PVD) class, an indicator of portal hypertension, and OGDHL at 10q11.23 (index rs1258172) was related to ascites grade. We also detected an increased expression of these six genes in livers of mice with severe schistosomiasis. Summary data-based Mendelian randomization analyses indicated that ITIH4, PMEPA1 and MAMSTR were pleiotropically associated with PVD class, HA and AST, respectively.

Rapid Assessment on Potential Risks of Schistosomiasis Transmission - 7 PLADs, China, 2019 and 2021

What is already known about this topic?

Oncomelania hupensis(O. hupensis) and livestock are main infection sources of schistosomiasis. The schistosome infected O. hupensis and livestock’s feces are important risk factors in the transmission of schistosomiasis.

What is added by this report?

The potential risks of schistosomiasis transmission remain prevalent, giving an early warning to local government with information on existing transmission risks. It is expected that the effectiveness and efficiency of schistosomiasis surveillance could be improved by conducting rapid risk assessment at the beginning of transmission season.

What are the implications for public health practice?

Rapid risk assessment is essential in early detection and the active monitoring of indicators of the transmission risks of schistosomiasis in endemic areas. This could work synergistically with surveillance system to minimize infections and prevent rebounds of endemic schistosomiasis outbreaks.

Genetic diversity and structure of Oncomelania hupensis hupensis in two eco-epidemiological settings as revealed by the mitochondrial COX1 gene sequences

BACKGROUND

Oncomelania hupensis hupensis is the only intermediate host of Schistosoma japonicum, the causative agent of schistosomiasis in China and is therefore of significant medical and veterinary health importance. Although tremendous progress has been achieved, there remains an understudied area of approximately 2.06 billion m² of potential snail habitats. This area could be further increased by annual flooding. Therefore, an understanding of population genetics of snails in these areas may be useful for future monitoring and control activities.

METHODS AND RESULTS

We sampled snails from Hexian (HX), Zongyang (ZY) and Shitai (ST) in Anhui (schistosomiasis transmission control), and from Hengtang (HT), Taicang (TC), Dongsan (DS) and Xisan (XS) in Jiangsu (schistosomiasis transmission interrupted), downstream of Anhui. ST, DS and XS are classified as hilly and mountainous areas, and HX, ZY, TC and HT as lake and marshland areas. The mitochondrial cytochrome c oxidase subunit I gene were sequenced. Out of 115 snails analyzed, 29 haplotypes were identified. We observed 56 (8.72%) polymorphic sites consisting of 51 transitions, four transversions and one multiple mutational change. The overall haplotype and nucleotide diversity were 0.899 and 0.01569, respectively. Snail populations in Anhui had higher genetic diversity than in Jiangsu. 73.32% of total variation was distributed among sites and 26.68% within sites. Snails were significantly separated according to eco-epidemiological settings in both network and phylogenetic analyses.

CONCLUSION

Our results could provide important guidance towards assessing coevolutionary interactions of snails with S. japonicum, as well as for future molluscan host monitoring and control activities.