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Int. J. Environ. Res. Public Health 2015, 12(9), 11756-11769; doi:10.3390/ijerph120911756

Identifying Spatial Clusters of Schistosomiasis in Anhui Province of China: A Study from the Perspective of Application

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Department of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai 200032, China
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Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
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Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai 200032, China
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Faculty of Medicine, School of Epidemiology, Pubic Health and Preventive Medicine, University of Ottawa, 451 Smyth Rd., Ottawa ON K1N 6N5, Canada
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Anhui Institute of Parasitic Diseases, Wuhu 230061, China
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Authors to whom correspondence should be addressed.
Academic Editor: Peter Congdon
Received: 24 July 2015 / Revised: 10 September 2015 / Accepted: 10 September 2015 / Published: 18 September 2015
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Abstract

With the strategy shifting from morbidity control to transmission interruption, the burden of schistosomiasis in China has been declining over the past decade. However, further controls of the epidemic in the lake and marshland regions remain a challenge. Prevalence data at county level were obtained from the provincial surveillance system in Anhui during 1997–2010. Spatial autocorrelation analysis and spatial scan statistics were combined to assess the spatial pattern of schistosomiasis. The spatial-temporal cluster analysis based on retrospective space-time scan statistics was further used to detect risk clusters. The Global Moran’s I coefficients were mostly statistically significant during 1997–2004 but not significant during 2005–2010. The clusters detected by two spatial cluster methods occurred in Nanling, Tongling, Qingyang and Wuhu during 1997–2004, and Guichi and Wuhu from 2005 to 2010, respectively. Spatial-temporal cluster analysis revealed 2 main clusters, namely Nanling (1999–2002) and Guichi (2005–2008). The clustering regions were significantly narrowed while the spatial extent became scattered during the study period. The high-risk areas shifted from the low reaches of the Yangtze River to the upper stream, suggesting the focus of schistosomiasis control should be shifted accordingly and priority should be given to the snail habitats within the high-risk areas of schistosomiasis. View Full-Text
Keywords: schistosomiasis; spatial pattern; spatial clustering; spatial-temporal clustering; China schistosomiasis; spatial pattern; spatial clustering; spatial-temporal clustering; China
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sun, L.; Chen, Y.; Lynn, H.; Wang, Q.; Zhang, S.; Li, R.; Xia, C.; Jiang, Q.; Hu, Y.; Gao, F.; Zhang, Z. Identifying Spatial Clusters of Schistosomiasis in Anhui Province of China: A Study from the Perspective of Application. Int. J. Environ. Res. Public Health 2015, 12, 11756-11769.

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