Re-emergence and influencing factors of mountain-type zoonotic visceral leishmaniasis in the extension region of Loess Plateau, China.

OBJECTIVE: To understand the epidemiological distribution characteristics of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in Yangquan City, Shanxi Province, China, from 2006 to 2021, to explore the influencing factors leading to the re-emergence of the epidemic, and to provide a basis for the formulation of targeted control strategies. METHODS: Case information spanning from 2006 to 2021 in Yangquan City was collected for a retrospective case-control study conducted from June to September 2022. A 1:3 matched ratio was employed. A questionnaire was utilized to gather data on basic information, demographic characteristics, awareness of MT-ZVL knowledge, residence, and dog breeding and living habits. The study employed a multifactorial conditional stepwise logistic regression model to analyze the influencing factors. RESULTS: A total of 508 subjects was analyzed. Risk factors for MT-ZVL included the use of soil/stone/concrete as building materials (OR = 3.932), presence of nearby empty/stone stack houses (OR = 2.515), dog breeding (OR = 4.215), presence of stray dogs (OR = 2.767), and neighbor's dog breeding (OR = 1.953). Protective factors comprised knowledge of MT-ZVL (OR = 0.113) and using mosquito repellents (OR = 0.388). The findings indicate significant associations between environmental and behavioral factors and MT-ZVL incidence in Yangquan City, Shanxi Province, China, from 2006 to 2021. These results underscore the importance of public awareness campaigns and targeted interventions aimed at reducing exposure to risk factors and promoting protective measures to mitigate the re-emergence of MT-ZVL outbreaks. CONCLUSION: House building materials, presence of neighboring empty houses, breeding domestic dogs and distribution of stray dogs surrounding the home are risk factors for MT-ZVL. Awareness of MT-ZVL and implementation of preventive measures during outdoor activities in summer and autumn are protective and may reduce the risk of MT-ZVL.

The genetic diversity of Oncomelania hupensis robertsoni, intermediate hosts of Schistosoma japonicum in hilly regions of China, using microsatellite markers.

BACKGROUND: The elimination of schistosomiasis remains a challenging task, with current measures primarily focused on the monitoring and control of Oncomelania hupensis (O. hupensis) snail, the sole intermediate host of Schistosome japonicum. Given the emerging, re-emerging, and persistent habitats of snails, understanding their genetic diversity might be essential for their successful monitoring and control. The aims of this study were to analyze the genetic diversity of Oncomelania hupensis robertsoni (O. h. robertsoni) using microsatellite DNA markers; and validate the applicability of previously identified microsatellite loci for O. hupensis in hilly regions. METHODS: A total of 17 populations of O. h. robertsoni from Yunnan Province in China were selected for analysis of genetic diversity using six microsatellite DNA polymorphic loci (P82, P84, T4-22, T5-11, T5-13, and T6-27). RESULTS: The number of alleles among populations ranged from 0 to 19, with an average of 5. The average ranges of expected (He) and observed (Ho) heterozygosity within populations were 0.506 to 0.761 and 0.443 to 0.792, respectively. The average fixation index within the population ranged from - 0.801 to 0.211. The average polymorphic information content (PIC) within the population ranged from 0.411 to 0.757, appearing to be polymorphic for all loci (all PIC > 0.5), except for P28 and P48. A total of 68 loci showed significant deviations from Hardy-Weinberg equilibrium (P < 0.05), and pairwise Fst values ranged from 0.051 to 0.379. The analysis of molecular variance indicated that 88% of the variation occurred within snail populations, whereas 12% occurred among snail populations. Phylogenetic trees and principal coordinate analysis revealed two distinct clusters within the snail population, corresponding to "Yunnan North" and "Yunnan South". CONCLUSIONS: O. h. robertsoni exhibited a relatively high level of genetic differentiation, with variation chiefly existing within snail populations. All snail in this region could be separated into two clusters. The microsatellite loci P82 and P84 might not be suitable for classification studies of O. hupensis in hilly regions. These findings provided important information for the monitoring and control of snail, and for further genetic diversity studies on snail populations.

Field validation of different intervention modes for the potential transmission risk of schistosomiasis during post-transmission interruption phase.

OBJECTIVE: Precision interventions have been proposed in transmission-interrupted areas to further reduce the potential transmission risk of schistosomiasis. This study aimed to evaluate the effects of different interventions modes for potential transmission risk control. METHODS: Three groups of schistosomiasis-endemic villages were selected in Jiangling county, Hubei province. After baseline surveys in 2020, three intervention models were employed in 2021 and 2022. In Model 1, Oncomelania hupensis snail control in key settings and an integrated strategy with an emphasis on the infectious sources managing was employed. In Model 2, an integrated health education-led strategy with an emphasis on infectious source management was employed. In Model 3, only the integrated strategy with an emphasis on infectious source management was employed. The effects of the different intervention models were examined with multiple indicators after 2 years of intervention using the entropy-weighted technique for order of preference by similarity to ideal solution (TOPSIS), rank-sum ratio (RSR) and fuzzy combination model of entropy-weighted TOPSIS and RSR. RESULTS: Entropy-weighted TOPSIS modeling showed that the Ci values of Model 2 were 0.4434, 0.2759, and 0.3069 in the three pilot villages, Ci values were larger, with top comprehensive ranking. The results of the RSR method showed that the RSR values of Model 2 were 0.75, 0.708, and 0.736 in the three pilot villages, with top comprehensive ranking. The results from the fuzzy combination model of entropy-weighted TOPSIS and RSR showed that implementation of Model 2 resulted in the highest comprehensive ranking among the three models in the three pilot villages under Ci: RSR = 0.1: 0.9, Ci: RSR = 0.5: 0.5 and Ci: RSR = 0.9: 0.1. CONCLUSION: The integrated health education-led strategy with an emphasis on infectious source management was the optimal model to manage the risk of transmission of schistosomiasis during the post-transmission interruption phase.

Recognizing and monitoring infectious sources of schistosomiasis by developing deep learning models with high-resolution remote sensing images.

BACKGROUND: China is progressing towards the goal of schistosomiasis elimination, but there are still some problems, such as difficult management of infection source and snail control. This study aimed to develop deep learning models with high-resolution remote sensing images for recognizing and monitoring livestock bovine, which is an intermediate source of Schistosoma japonicum infection, and to evaluate the effectiveness of the models for real-world application. METHODS: The dataset of livestock bovine's spatial distribution was collected from the Chinese National Platform for Common Geospatial Information Services. The high-resolution remote sensing images were further divided into training data, test data, and validation data for model development. Two recognition models based on deep learning methods (ENVINet5 and Mask R-CNN) were developed with reference to the training datasets. The performance of the developed models was evaluated by the performance metrics of precision, recall, and F1-score. RESULTS: A total of 50 typical image areas were selected, 1125 bovine objectives were labeled by the ENVINet5 model and 1277 bovine objectives were labeled by the Mask R-CNN model. For the ENVINet5 model, a total of 1598 records of bovine distribution were recognized. The model precision and recall were 81.9% and 80.2%, respectively. The F1 score was 0.81. For the Mask R-CNN mode, 1679 records of bovine objectives were identified. The model precision and recall were 87.3% and 85.2%, respectively. The F1 score was 0.87. When applying the developed models to real-world schistosomiasis-endemic regions, there were 63 bovine objectives in the original image, 53 records were extracted using the ENVINet5 model, and 57 records were extracted using the Mask R-CNN model. The successful recognition ratios were 84.1% and 90.5% for the respectively developed models. CONCLUSION: The ENVINet5 model is very feasible when the bovine distribution is low in structure with few samples. The Mask R-CNN model has a good framework design and runs highly efficiently. The livestock recognition models developed using deep learning methods with high-resolution remote sensing images accurately recognize the spatial distribution of livestock, which could enable precise control of schistosomiasis.

Establishment of an indicator framework for the transmission risk of the mountain-type zoonotic visceral leishmaniasis based on the Delphi-entropy weight method.

BACKGROUND: Visceral leishmaniasis (VL) is one of the most important neglected tropical diseases. Although VL was controlled in several regions of China during the last century, the mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has reemerged in the hilly areas of China in recent decades. The purpose of this study was to construct an indicator framework for assessing the risk of the MT-ZVL in China, and to provide guidance for preventing disease. METHODS: Based on a literature review and expert interview, a 3-level indicator framework was initially established in November 2021, and 28 experts were selected to perform two rounds of consultation using the Delphi method. The comprehensive weight of the tertiary indicators was determined by the Delphi and the entropy weight methods. RESULTS: Two rounds of Delphi consultation were conducted. Four primary indicators, 11 secondary indicators, and 35 tertiary indicators were identified. The Delphi-entropy weight method was performed to calculate the comprehensive weight of the tertiary indicators. The normalized weights of the primary indicators were 0.268, 0.261, 0.242, and 0.229, respectively, for biological factors, interventions, environmental factors, and social factors. The normalized weights of the top four secondary indicators were 0.122, 0.120, 0.098, and 0.096, respectively, for climatic features, geographical features, sandflies, and dogs. Among the tertiary indicators, the top four normalized comprehensive weights were the population density of sandflies (0.076), topography (0.057), the population density of dogs, including tethering (0.056), and use of bed nets or other protective measures (0.056). CONCLUSIONS: An indicator framework of transmission risk assessment for MT-ZVL was established using the Delphi-entropy weight method. The framework provides a practical tool to evaluate transmission risk in endemic areas.

Epidemiological features and spatial-temporal clustering of visceral leishmaniasis in mainland China from 2019 to 2021.

Background: Visceral leishmaniasis (VL) is a serious vector-borne disease in central and western China. In recent years, the number of VL cases increased gradually, particularly the mountain-type zoonotic visceral leishmaniasis (MT-ZVL). This study clarified the epidemiological features and spatial-temporal clustering of VL in China between 2019 and 2021, identified the risk areas for VL transmission, and provided scientific evidence for the prevention and control of VL. Materials and methods: The information on VL cases in 2019-2021 was collected from the Infectious Disease Reporting Information Management System of the Chinese Center for Disease Control and Prevention. The epidemiological characteristics of VL cases were analyzed. The global Moran's I and Getis-ORD Gi* statistical data were processed for spatial autocorrelation and hotspot analysis in ESRI ArcGIS software. Also, spatial-temporal clustering analysis was conducted with the retrospective space-time permutation scan statistics. Results: A total of 608 VL cases were reported from 2019 to 2021, with 158, 213, and 237 cases reported each year, respectively. Of the 608 cases, there were 10 cases of anthroponotic visceral leishmaniasis (AVL), 20 cases of desert-type zoonotic visceral leishmaniasis (DT-ZVL), and 578 cases of MT-ZVL. The age of VL cases was mainly distributed in the group of subjects aged ≥ 15 years. Peasants and infants were the dominant high-risk population. The incidence peak season of VL occurred between March and May. The cases were mainly distributed in Shanxi (299 cases), Shaanxi (118 cases), and Gansu (106 cases) Provinces, accounting for 86.02% (523/608) of the total reported cases in China. Spatial analysis revealed that clustering of infection is mainly located in eastern Shanxi Province and Shaanxi-Shanxi border areas, as well as southern Gansu and northern Sichuan Province. In addition, new reemergence hotspots in Shanxi, Henan, and Hebei Provinces have been detected since 2020. Spatio-temporal clustering analysis revealed an increase in the degree of infection aggregation in eastern Shanxi Province and Shaanxi-Shanxi border areas. Conclusion: The AVL and DT-ZVL were endemic at a lower level in western China, whereas MT-ZVL rebounded rapidly and showed a resurgence in historically endemic counties. The spatial-temporal clustering analysis displayed that the high-incidence areas of VL have shifted to central China, particularly in Shanxi and Shaanxi Provinces. Integrated mitigation strategies targeting high-risk populations are needed to control VL transmission in high-risk areas.

Transmission Risk Predicting for Schistosomiasis in Mainland China by Exploring Ensemble Ecological Niche Modeling.

Schistosomiasis caused by Schistosoma japonicum is one of the major neglected tropical diseases worldwide. The snail Oncomelania hupensis is the only intermediate host of S. japonicum, which is recognized as an indicator of the schistosomias occurrence. In order to evaluate the risk of schistosomiasis in China, this work investigate the potential geographical distribution of host snail habitus by developing an ensemble ecological niche model with reference to the suitable environmental factors. The historical records of snail habitus were collected form the national schistosomiasis surveillance program from the year of 2005 to 2014. A total of 25 environmental factors in terms of the climate, geographic, and socioeconomic determinants of snail habitats were collected and geographically coded with reference to the snail data. Based on the correlations among snail habitats and the geographically associated environmental factors, an ensemble ecological niche model was developed by integrating ten standard models, aiming for improving the predictive accuracy. Three indexes are used for model performance evaluation, including receiver operating characteristic curves, kappa statistics, and true skill statistics. The model was used for mapping the risk of schistosomiasis in the middle and lower reaches of the Yangtze River. The results have shown that the predicted risk areas were classified into low risk (4.55%), medium risk (2.01%), and high risk areas (4.40%), accounting for 10.96% of the land area of China. This study demonstrated that the developed ensemble ecological niche models was an effective tool for evaluating the risk of schistosomiasis, particularly for the endemic regions, which were not covered by the national schistosomiasis control program.

Assessment on the Diagnostic Capacity for Parasitic Diseases of Health Facilities - China, 2019.

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Morbidity and prevalence of several major parasitic diseases have been declining in China. To reduce the disease burden of parasitic diseases and protect public health security, conducting accurate diagnoses following timely treatment is important. WHAT IS ADDED BY THIS REPORT?: In the national competition held in 2019, the overall accuracy rates of participants for theoretical knowledge and slides interpretation for parasitic diseases were 80.44% and 66.87%, respectively. Significant differences in the accuracy rates of detecting schistosomiasis or malaria existed between endemic areas and non-endemic areas, respectively. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: The study results will help policymakers and health managers to identify the gaps in parasitic diseases, help to strengthen diagnostic capacity, and improve quality of control programs.

Spatio-temporal clustering of Mountain-type Zoonotic Visceral Leishmaniasis in China between 2015 and 2019.

With several decades of concerted control efforts, visceral leishmaniasis(VL) eradication had almost been achieved in China. However, VL cases continue to be detected in parts of western China recent years. Using data of reported cases, this study aimed to investigate the epidemiology and spatio⁃temporal distribution, of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China between the years 2015 and 2019. Epidemiological data pertaining to patients with visceral leishmaniasis (VL) were collected in Gansu, Shaanxi, Sichuan, Shanxi, Henan and Hebei provinces between the years 2015 and 2019. Joinpoint regression analysis was performed to determine changes in the epidemic trend of MT-ZVL within the time period during which data was collected. Spatial autocorrelation of infection was examined using the Global Moran's I statistic wand hotspot analysis was carried out using the Getis-Ord Gi* statistic. Spatio-temporal clustering analysis was conducted using the retrospective space-time permutation flexible spatial scanning statistics. A total of 529 cases of MT-ZVL were detected in the six provinces from which data were collected during the study time period, predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. A decline in VL incidence in China was observed during the study period, whereas an increase in MT-ZVL incidence was observed in the six provinces from which data was obtained (t = 4.87, P < 0.05), with highest incidence in Shanxi province (t = 16.91, P < 0.05). Significant differences in the Moran's I statistic were observed during study time period (P < 0.05), indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Hotspot and spatial autocorrelation analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and in east of Shanxi province, where transmission increased rapidly over the study duration, as well as in well know high transmission areas in the south of Gansu province and the north of the Sichuan province. It indicates resurgence of MT-ZVL transmission over the latter three years of the study. Spatial clustering of infection was observed in localized areas, as well as sporadic outbreaks of infection.

Potential impact of flooding on schistosomiasis in Poyang Lake regions based on multi-source remote sensing images.

BACKGROUND: Flooding is considered to be one of the most important factors contributing to the rebound of Oncomelania hupensis, a small tropical freshwater snail and the only intermediate host of Schistosoma japonicum, in endemic foci. The aim of this study was to assess the risk of intestinal schistosomiasis transmission impacted by flooding in the region around Poyang Lake using multi-source remote sensing images. METHODS: Normalized Difference Vegetation Index (NDVI) data collected by the Landsat 8 satellite were used as an ecological and geographical suitability indicator of O. hupensis habitats in the Poyang Lake region. The expansion of the water body due to flooding was estimated using dual-polarized threshold calculations based on dual-polarized synthetic aperture radar (SAR). The image data were captured from the Sentinel-1B satellite in May 2020 before the flood and in July 2020 during the flood. A spatial database of the distribution of snail habitats was created using the 2016 snail survey in Jiangxi Province. The potential spread of O. hupensis snails after the flood was predicted by an overlay analysis of the NDVI maps in the flood-affected areas around Poyang Lake. The risk of schistosomiasis transmission was classified based on O. hupensis snail density data and the related NDVI. RESULTS: The surface area of Poyang Lake was approximately 2207 km2 in May 2020 before the flood and 4403 km2 in July 2020 during the period of peak flooding; this was estimated to be a 99.5% expansion of the water body due to flooding. After the flood, potential snail habitats were predicted to be concentrated in areas neighboring existing habitats in the marshlands of Poyang Lake. The areas with high risk of schistosomiasis transmission were predicted to be mainly distributed in Yongxiu, Xinjian, Yugan and Poyang (District) along the shores of Poyang Lake. By comparing the predictive results and actual snail distribution, we estimated the predictive accuracy of the model to be 87%, which meant the 87% of actual snail distribution was correctly identified as snail habitats in the model predictions. CONCLUSIONS: Data on water body expansion due to flooding and environmental factors pertaining to snail breeding may be rapidly extracted from Landsat 8 and Sentinel-1B remote sensing images. Applying multi-source remote sensing data for the timely and effective assessment of potential schistosomiasis transmission risk caused by snail spread during flooding is feasible and will be of great significance for more precision control of schistosomiasis.

Construction and application of surveillance and response systems for parasitic diseases in China, led by NIPD-CTDR.

Parasitic diseases have been widely epidemic in China with a long history. Great endeavours made in past 70 years led to significant decrease in morbidity and mortablity caused by several major parasitic diseases, while challenges existed to eliminate parasitic diseases. Surveillance-response system has play a crucial role in identifying public health problems, ascertaining the distribution and epidemic dynamics, discovering outbreaks and epidemic anomalies, evaluating the effects of on-site intervention activities and identifying risk factors. In this article, we reviewed the progress of the surveillance system for parasitic diseases, analysed the role of NIPD in the construction and application of surveillance-response system of parasitic diseases through elaborating the surveillance activities and typical surveillance-response events led by NIPD. Suggestion and comments for improve the surveillance-response system were put forward for further control or elimination of parasitic diseases.

Temporal transcriptome change of Oncomelania hupensis revealed by Schistosoma japonicum invasion.

BACKGROUND: The freshwater snail Oncomelania hupensis is the obligate intermediate host for Schistosoma japonicum in China. Transcriptomic examination of snail-schistosome interactions can provide valuable information of host response at physiological and immune levels. METHODS: To investigate S. japonicum-induced changes in O. hupensis gene expression, we utilized high-throughput sequencing to identify transcripts that were differentially expressed between infected snails and their uninfected controls at two key time-point, Day 7 and Day 30 after challenge. Time-series transcriptomic profiles were analyzed using R package DESeq 2, followed by GO, KEGG and (weighted gene correlation network analysis) WGCNA analysis to elucidate and identify important molecular mechanism, and subsequently understand host-parasite relationship. The identified unigenes was verified by bioinformatics and real-time PCR. Possible adaptation molecular mechanisms of O. hupensis to S. japonicum challenge were proposed. RESULTS: Transcriptomic analyses of O. hupensis by S. japonicum invasion yielded billion reads including 92,144 annotated transcripts. Over 5000 differentially expressed genes (DEGs) were identified by pairwise comparisons of infected libraries from two time points to uninfected libraries in O. hupensis. In total, 6032 gene ontology terms and 149 KEGG pathways were enriched. After the snails were infected with S. japonicum on Day 7 and Day 30, DEGs were shown to be involved in many key processes associated with biological regulation and innate immunity pathways. Gene expression patterns differed after exposure to S. japonicum. Using WGCNA, 16 modules were identified. Module-trait analysis identified that a module involved in RNA binding, ribosome, translation, mRNA processing, and structural constituent of ribosome were strongly associated with S. japonicum invasion. Many of the genes from enriched KEGG pathways were involved in lysosome, spliceosome and ribosome, indicating that S. japonicum invasion may activate the regulation of ribosomes and immune response to infection in O. hupensis. CONCLUSIONS: Our analysis provided a temporally dynamic gene expression pattern of O. hupensis by S. japonicum invasion. The identification of gene candidates serves as a foundation for future investigations of S. japonicum infection. Additionally, major DEGs expression patterns and putative key regulatory pathways would provide useful information to construct gene regulatory networks between host-parasite crosstalk.

Intestinal microbiome profiles in Oncomelania hupensis in mainland China.

Oncomelania hupensis plays a significant role in the transmission of schistosomiasis japonica, which remains a major public health concern in China. Understanding the biological characteristics of O. hupensis is a prerequisite for its control; however, there are currently no studies investigating the intestinal microbiota of the O. hupensis snail. This study aimed to profile the intestinal microbiome of O. hupensis across different ecological landscapes in mainland China. DNA was extracted from the intestines of the collected snails and the bacterial communities were detected using 454 pyrosequencing. A total of 3,799 operational taxonomic units (OTUs) were obtained, and Proteobacteria, Firmicutes, and Actinobacteria were identified as the dominant bacterial taxa at the phylum level. Bacillus and Lactococcus were the most common genera in samples obtained from the four ecological landscapes. Snail specimens were clustered into three clades according to microbial community diversity, and thirty-seven genera that contributed to differential microbiota distributions were identified. Co-occurrence network analysis indicated a symbiotic relationship for the intestinal microbiota of O. hupensis, and PICRUSt analysis predicted forty-one metabolic functions in all snail samples, including membrane transport, amino acid metabolism, carbohydrate metabolism, replication and repair, energy metabolism, as well as xenobiotics biodegradation and metabolism. These findings improve our understanding of bacterial ecology in the O. hupensis intestine; further studies will focus on the relationship between O. hupensis intestinal microbiota and the microbiota in their specific ecological environments.

High-resolution remote sensing-based spatial modeling for the prediction of potential risk areas of schistosomiasis in the Dongting Lake area, China.

The geographical distribution of snail (i.e., the intermediate host of schistosomiasis) is consistent with that of endemic areas. The suitable snail habitus requires necessary environmental conditions for snail population. The high-resolution remote sensing provides an important tool for the spatio-temporal analysis of disease monitoring and prediction. This study conducted a typical schistosomiasis epidemic area in the marshland and lake regions along the Yangtze River, Yueyang City, Hunan Province of China. And three types of environmental factors, i.e., NDVI, soil moisture, and shortest distance to water body, associated with the geographical distribution of snail population, were extracted from the high-resolution remoting sensing data. The predicted distribution of snail habitus from the high-resolution environmental factors were compared with the data of annual program of snail survey. The results have shown that the application of high-resolution remote sensing can improve the accuracy of the modeled and predicted the potential risk areas of schistosomiasis, and may become an important tool for the ongoing national schistosomiasis control program.

High-resolution remote sensing-based spatial modeling for the prediction of potential risk areas of schistosomiasis in the Dongting Lake area, China.

The geographical distribution of snail (i.e., the intermediate host of schistosomiasis) is consistent with that of endemic areas. The suitable snail habitus requires necessary environmental conditions for snail population. The high-resolution remote sensing provides an important tool for the spatio-temporal analysis of disease monitoring and prediction. This study conducted a typical schistosomiasis epidemic area in the marshland and lake regions along the Yangtze River, Yueyang City, Hunan Province of China. And three types of environmental factors, i.e., NDVI, soil moisture, and shortest distance to water body, associated with the geographical distribution of snail population, were extracted from the high-resolution remoting sensing data. The predicted distribution of snail habitus from the high-resolution environmental factors were compared with the data of annual program of snail survey. The results have shown that the application of high-resolution remote sensing can improve the accuracy of the modeled and predicted the potential risk areas of schistosomiasis, and may become an important tool for the ongoing national schistosomiasis control program.

Assessing competence for helminthiases: A lesson learnt from national contest of parasitic diseases in China in 2012-2016.

This study aimed to assess the competency of health professionals on helminthiasis control in China. The assessment system comprised of two parts, one being the parasitological knowledge test and the other a technical skills assessment. The knowledge test mainly examined morphology, epidemiology, life history and diagnosis of common and important parasites. The skills assessment consisted of sample slides making and species identification using microscopy. From 2012 to 2016, a total of 616 participants from different levels of parasitic diseases prevention and control departments of CDC took part in the assessment. The results had shown a high level of academic knowledge among participants. Accuracy rates of schistosomiasis, echinococcosis, food-borne helminthiases, and soil-transmitted helminthiasis were all above 60%. This showed an excellent knowledge level of helminthiases by participants. However, among all 616 participants, 94.97% passed the thick-smear passing test (>= 60%), while in microscopy tests the equivalent was only 43.67%. Competencies in different districts varied. It is imperative to set up a North-South skill exchange mechanism of helminthiases diagnostic techniques and to apply new diagnostic tools widely to strengthen helminthiases prevention and control in China.

Village-based spatio-temporal cluster analysis of the schistosomiasis risk in the Poyang Lake Region, China.

BACKGROUND: The Poyang Lake Region, one of the major epidemic sites of schistosomiasis in China, remains a severe challenge. To improve our understanding of the current endemic status of schistosomiasis and to better control the transmission of the disease in the Poyang Lake Region, it is important to analyse the clustering pattern of schistosomiasis and detect the hotspots of transmission risk. RESULTS: Based on annual surveillance data, at the village level in this region from 2009 to 2014, spatial and temporal cluster analyses were conducted to assess the pattern of schistosomiasis infection risk among humans through purely spatial (Local Moran's I, Kulldorff and Flexible scan statistic) and space-time scan statistics (Kulldorff). A dramatic decline was found in the infection rate during the study period, which was shown to be maintained at a low level. The number of spatial clusters declined over time and were concentrated in counties around Poyang Lake, including Yugan, Yongxiu, Nanchang, Xingzi, Xinjian, De'an as well as Pengze, situated along the Yangtze River and the most serious area found in this study. Space-time analysis revealed that the clustering time frame appeared between 2009 and 2011 and the most likely cluster with the widest range was particularly concentrated in Pengze County. CONCLUSIONS: This study detected areas at high risk for schistosomiasis both in space and time at the village level from 2009 to 2014 in Poyang Lake Region. The high-risk areas are now more concentrated and mainly distributed at the river inflows Poyang Lake and along Yangtze River in Pengze County. It was assumed that the water projects including reservoirs and a recently breached dyke in this area were partly to blame. This study points out that attempts to reduce the negative effects of water projects in China should focus on the Poyang Lake Region.

[Analysis of schistosomiasis prevalence in endemic areas using retrospective space-time permutation scan statistics].

Objective: To analyze the characteristics of schistosomasis prevalence by using the spatial epidemiological method, and test the application of retrospective space-time permutation scan statistics in determining mountainous and lake-type endemic areas of schistosomiasis. Methods: The data of schistosomasis in humans, cattle and snails in Jiangxi Province during 2009-2014 and in Yunnan Province during 2004-2013 were collected and analyzed. The temporal and spatial distribution of schistosomiasis endemic areas in the two provinces was analyzed with retrospective space-time permutation scan statistics. Results: The prevalence of schistosomiasis in residents and Oncomelania snails showed a trend of decline in Jiangxi, from 0.21% and 0.03% in 2009 to 0.01% and zero in 2014. A similar trend was found in cattle, from 1.25% in 2012 to 0.12% in 2014. The average annual percentage change (APC) in residents was-47.36%(P < 0.05). The space-time permutation clustering analysis revealed a temporal and spatial clustering of schistosomiasis prevalence from 2009 to 2014 in residents, cattle, and snails, with 3,2 and 1 clustering areas, respectively, all distributed in Poyang Lake Region. A similar declining trend of schistosomiasis prevalence was found in residents, snails and cattle in Yunnan during 2004-2013, from 2.49%,0.70% and 3.76% in 2004 to no infection in residents and snails and 0.02% in cattle in 2013. The APC in residents was-49.17%(P < 0.05). There was a temporal and spatial clustering of schistosomiasis prevalence during 2004-2013 in residents, cattle, and snails, with 2,2 and 6 clustering areas, respectively. Conclusion: A declining trend of schistosomiasis prevalence is shown in lake-type endemic areas in Jiangxi during 2009-2014 and in mountainous endemic areas in Yunnan during 2004-2013. The retrospective space-time permutation scan statistics reveal a clustering of schistosomiasis in humans, cattle, and snails, suggesting its applicability in analyzing the temporal and spatial distribution of schistosomiasis.