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.
With global warming and socioeconomic developments, there is a tendency toward the emergence and spread of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China. Timely identification of the transmission risk and spread of MT-ZVL is, therefore, of great significance for effectively interrupting the spread of MT-ZVL and eliminating the disease. In this study, 26 environmental variables—namely, climatic, geographical, and 2 socioeconomic indicators were collected from regions where MT-ZVL patients were detected during the period from 2019 to 2021, to create 10 ecological niche models. The performance of these ecological niche models was evaluated using the area under the receiver-operating characteristic curve (AUC) and true skill statistic (TSS), and ensemble models were created to predict the transmission risk of MT-ZVL in China. All ten ecological niche models were effective at predicting the transmission risk of MT-ZVL in China, and there were significant differences in the mean AUC (H = 33.311, p < 0.05) and TSS values among these ten models (H = 26.344, p < 0.05). The random forest, maximum entropy, generalized boosted, and multivariate adaptive regression splines showed high performance at predicting the transmission risk of MT-ZVL (AUC > 0.95, TSS > 0.85). Ensemble models predicted a transmission risk of MT-ZVL in the provinces of Shanxi, Shaanxi, Henan, Gansu, Sichuan, and Hebei, which was centered in Shanxi Province and presented high spatial clustering characteristics. Multiple ensemble ecological niche models created based on climatic and environmental variables are effective at predicting the transmission risk of MT-ZVL in China. This risk is centered in Shanxi Province and tends towards gradual radiation dispersion to surrounding regions. Our results provide insights into MT-ZVL surveillance in regions at high risk of MT-ZVL.
: 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. Graphical
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.