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Zhang X, Lv Z, Dai J, Ke Y, Chen X, Hu Y. Precision mapping of snail habitat in lake and marshland areas: Integrating environmental and textural indicators using Random Forest modeling. Heliyon 2024; 10:e36300. [PMID: 39262947 PMCID: PMC11388569 DOI: 10.1016/j.heliyon.2024.e36300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 08/07/2024] [Accepted: 08/13/2024] [Indexed: 09/13/2024] Open
Abstract
Schistosomiasis japonica continues to pose a significant public health challenge in China, primarily due to the widespread distribution of Oncomelania hupensis, the sole intermediate host of Schistosoma. This study aims to address the constraints of existing remote sensing analyses for identifying snail habitats, which frequently neglect spatial scale and seasonal variations. To this end, we adopt a multi-source data-driven Random Forest approach that integrates bottomland and ground-surface texture data with traditional environmental variables, enhancing the accuracy of snail habitat assessments. We developed four distinct models for the lake and marshland areas of Guichi, China: a baseline model incorporating ground-surface texture, bottomland variables, and environmental variables; Model 1 with only environmental variables; Model 2 adding ground-surface texture and environmental variables; and Model 3 integrating bottomland with environmental variables. The baseline model outperformed the others, achieving a true skill statistic of 0.93, an accuracy of 0.97, a kappa statistic of 0.94, and an area under the curve of 0.99. Our analysis pinpointed critical high-risk snail habitats distributed in a belt-like pattern along major water bodies, near the Yangtze River, QiuPu River, and around Shengjin Lake, Jiuhua River, and Qingtong River. These insights can aid local health authorities in more efficiently allocating limited resources, developing effective snail surveillance and control strategies to combat schistosomiasis. Additionally, this approach can be adapted to localize other endemic hosts with similar ecological characteristics.
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Affiliation(s)
- Xuedong Zhang
- School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing, 102627, China
- Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing, 100038, China
| | - Zelan Lv
- School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing, 102627, China
| | - Jianjun Dai
- Schistosomiasis Station of Prevention and Control in Guichi District 247100, Anhui Province, China
| | - Yongwen Ke
- Schistosomiasis Station of Prevention and Control in Guichi District 247100, Anhui Province, China
| | - Xinyue Chen
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
- Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Yi Hu
- Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
- Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
- Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, 200032, China
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Song J, Wang H, Li S, Du C, Qian P, Wang W, Shen M, Zhang Z, Zhou J, Zhang Y, Li C, Hao Y, Dong Y. The genetic diversity of Oncomelania hupensis robertsoni, intermediate hosts of Schistosoma japonicum in hilly regions of China, using microsatellite markers. Parasit Vectors 2024; 17:147. [PMID: 38515113 PMCID: PMC10956175 DOI: 10.1186/s13071-024-06227-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/01/2024] [Indexed: 03/23/2024] Open
Abstract
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.
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Affiliation(s)
- Jing Song
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Hongqiong Wang
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Shizhu Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Tropical Diseases Research; NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research on Tropical Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Shanghai, 200025, China
- School of Global Health, Chinese Center for Tropical Diseases Research-Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunhong Du
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Peijun Qian
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Tropical Diseases Research; NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research on Tropical Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Shanghai, 200025, China
| | - Wenya Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Tropical Diseases Research; NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research on Tropical Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Shanghai, 200025, China
| | - Meifen Shen
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Zongya Zhang
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Jihua Zhou
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Yun Zhang
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China
| | - Chunying Li
- School of Public Health, Kunming Medical University, Kunming, 650500, China
| | - Yuwan Hao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Tropical Diseases Research; NHC Key Laboratory of Parasite and Vector Biology; WHO Collaborating Center for Tropical Diseases; National Center for International Research on Tropical Diseases, National Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention, Shanghai, 200025, China.
| | - Yi Dong
- Department of Schistosomiasis Control and Prevention, Yunnan Institute of Endemic Disease Control and Prevention, Dali, 671000, China.
- Yunnan Key Laboratory of Natural Focus Disease Control Technology, Dali, 671000, China.
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Zhang JY, Gu MM, Yu QF, Sun MT, Zou HY, Zhou ZJ, Lu DB. Genetic diversity and structure of Oncomelania hupensis hupensis in two eco-epidemiological settings as revealed by the mitochondrial COX1 gene sequences. Mol Biol Rep 2021; 49:511-518. [PMID: 34725747 DOI: 10.1007/s11033-021-06907-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 10/29/2021] [Indexed: 10/19/2022]
Abstract
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.
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Affiliation(s)
- Jie-Ying Zhang
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China
| | - Man-Man Gu
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China
| | - Qiu-Fu Yu
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China
| | - Meng-Tao Sun
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China
| | - Hui-Ying Zou
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China
| | - Zhi-Jun Zhou
- Center for Disease Prevention and Control of Wuzhong District, Suzhou, China
| | - Da-Bing Lu
- Department of Epidemiology and Statistics, School of Public Health, Soochow University, Suzhou, China.
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Li S, Shi Y, Deng W, Ren G, He H, Hu B, Li C, Zhang N, Zheng Y, Wang Y, Dong S, Chen Y, Jiang Q, Zhou Y. Spatio-temporal variations of emerging sites infested with schistosome-transmitting Oncomelania hupensis in Hunan Province, China, 1949-2016. Parasit Vectors 2021; 14:7. [PMID: 33407789 PMCID: PMC7789244 DOI: 10.1186/s13071-020-04526-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 12/07/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Constant emerging sites infested with Oncomelania hupensis (O. hupensis) impede the goal realization of eliminating schistosomiasis. The study assessed the spatial and temporal distributions of new Oncomelania snail habitats in Hunan Province from 1949 to 2016. METHODS We used the data from annual snail surveys throughout Hunan Province for the period from 1949 to 2016. Global Moran's I, Anselin local Moran's I statistics (LISA) and a retrospective space-time permutation model were applied to determine the spatial and temporal distributions of emerging snail-infested sites. RESULTS There were newly discovered snail-infested sites almost every year in 1949-2016, except for the years of 1993, 2009 and 2012. The number of emerging sites varied significantly in the five time periods (1949-1954, 1955-1976, 1977-1986, 1986-2003 and 2004-2016) (H = 25.35, p < 0.05). The emerging sites lasted 37.52 years in marshlands, 30.04 years in hills and 24.63 at inner embankments on average, with the values of Global Moran's I being 0.52, 0.49 and 0.44, respectively. High-value spatial clusters (HH) were mainly concentrated along the Lishui River and in Xiangyin County. There were four marshland clusters, two hill clusters and three inner embankment clusters after 1976. CONCLUSIONS Lower reaches of the Lishui River and the Dongting Lake estuary were the high-risk regions for new Oncomelania snail habitats with long durations. Snail surveillance should be strengthened at stubborn snail-infested sites at the inner embankments. Grazing prohibition in snail-infested grasslands should be a focus in marshlands. The management of bovines in Xiangyin County is of great importance.
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Affiliation(s)
- Shengming Li
- Hunan Institute for Schistosomiasis Control, Yueyang, Hunan, China
| | - Ying Shi
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Weicheng Deng
- Hunan Institute for Schistosomiasis Control, Yueyang, Hunan, China
| | - Guanghui Ren
- Hunan Institute for Schistosomiasis Control, Yueyang, Hunan, China
| | - Hongbin He
- Hunan Institute for Schistosomiasis Control, Yueyang, Hunan, China
| | - Benjiao Hu
- Hunan Institute for Schistosomiasis Control, Yueyang, Hunan, China
| | - Chunlin Li
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Na Zhang
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Yingyan Zheng
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Yingjian Wang
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Shurong Dong
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, 600 Peter Morand Crescent, Ottawa, Ontario, K1G 5Z3, Canada
| | - Qingwu Jiang
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China
| | - Yibiao Zhou
- Fudan University School of Public Health, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China. .,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China. .,Fudan University Center for Tropical Disease Research, Building 8, 130 Dong'an Road, Xuhui District, Shanghai, 200032, China.
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