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Feng Y, Liu L, Xia S, Xu JF, Bergquist R, Yang GJ. Reaching the Surveillance-Response Stage of Schistosomiasis Control in The People's Republic of China: A Modelling Approach. ADVANCES IN PARASITOLOGY 2016; 92:165-96. [PMID: 27137447 DOI: 10.1016/bs.apar.2016.02.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
With the goal set to eliminate schistosomiasis nationwide by 2020, The People's Republic of China has initiated the surveillance-response stage to identify remaining sources of infection and potential pockets from where the disease could reemerge. Shifting the focus from classical monitoring and evaluation to rapid detection and immediate response, this approach requires modelling to bridge the surveillance and response components. We review here studies relevant to schistosomiasis modelling in a Chinese surveillance-response system with the expectation to achieve a practically useful understanding of the current situation and potential future study directions. We also present useful experience that could tentatively be applied in other endemic regions in the world. Modelling is discussed at length as it plays an essential role, both with regard to the intermediate snail host and in the definitive, mammal hosts. Research gaps with respect to snail infection, animal hosts and sectoral research cooperation are identified and examined against the prevailing background of ecosystem and socioeconomic changes with a focus on coexisting challenges and opportunities in a situation with increasing financial constraints.
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Affiliation(s)
- Y Feng
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Public Health Research Center, Jiangnan University, Wuxi, Jiangsu Province, The People's Republic of China
| | - L Liu
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Public Health Research Center, Jiangnan University, Wuxi, Jiangsu Province, The People's Republic of China
| | - S Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, The People's Republic of China; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, The People's Republic of China; WHO Collaborating Center for Tropical Diseases, Shanghai, The People's Republic of China
| | - J-F Xu
- Hubei University for Nationalities, The People's Republic of China
| | - R Bergquist
- Geospatial Health, University of Naples Federico II, Naples, Italy
| | - G-J Yang
- Key Laboratory of National Health and Family Planning Commission on Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Wuxi, The People's Republic of China; Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, The People's Republic of China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, The People's Republic of China; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
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Zhang Z, Bergquist R, Chen D, Yao B, Wang Z, Gao J, Jiang Q. Identification of parasite-host habitats in Anxiang county, Hunan Province, China based on multi-temporal China-Brazil earth resources satellite (CBERS) images. PLoS One 2013; 8:e69447. [PMID: 23922712 PMCID: PMC3726693 DOI: 10.1371/journal.pone.0069447] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2013] [Accepted: 06/08/2013] [Indexed: 11/19/2022] Open
Abstract
Remote sensing is a promising technique for monitoring the distribution and dynamics of various vector-borne diseases. In this study, we used the multi-temporal CBERS images, obtained free of charge, to predict the habitats of the snail Oncomelania hupensis, the sole intermediate host of schistosomiasis japonica, a snail-borne parasitic disease of considerable public health in China. Areas of suitable snail habitats were identified based on the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI), and the predictive model was tested against sites (snails present or absent) that were surveyed directly for O. hupensis. The model performed well (sensitivity and specificity were 63.64% and 78.09%, respectively), and with further development, we may provide an accurate, inexpensive tool for the broad-scale monitoring and control of schistosomiasis, and other similar vector-borne diseases.
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Affiliation(s)
- Zhijie Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, People's Republic of China.
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