title: Village-based spatio-temporal cluster analysis of the schistosomiasis risk in the Poyang Lake Region, China.
abstract: 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.
authors.affiliation: Department of Epidemiology and Biostatistics, 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.|Collaborative Innovation Center of Social Risks Governance in Health, School of Public Health, Fudan University, Shanghai, 200032, China.
authors.forename: Congcong
authors.initials: C
authors.lastname: Xia
authors.affiliation: Ingerod, Brastad, Sweden.
authors.forename: Robert
authors.initials: R
authors.lastname: Bergquist
authors.affiliation: Department of Epidemiology and Biostatistics, 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.|Collaborative Innovation Center of Social Risks Governance in Health, School of Public Health, Fudan University, Shanghai, 200032, China.
authors.forename: Henry
authors.initials: H
authors.lastname: Lynn
authors.affiliation: Jiangxi Institute of Schistosomiasis Prevention and Control, Nanchang, 330000, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Hu
authors.affiliation: Jiangxi Institute of Schistosomiasis Prevention and Control, Nanchang, 330000, China.
authors.forename: Dandan
authors.initials: D
authors.lastname: Lin
authors.affiliation: National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200032, China.
authors.forename: Yuwan
authors.initials: Y
authors.lastname: Hao
authors.affiliation: National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200032, China. Lisz@chinacdc.cn.
authors.forename: Shizhu
authors.initials: S
authors.lastname: Li
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, 200032, China. huy@lreis.ac.cn.|Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China. huy@lreis.ac.cn.|Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, 200032, China. huy@lreis.ac.cn.|Collaborative Innovation Center of Social Risks Governance in Health, School of Public Health, Fudan University, Shanghai, 200032, China. huy@lreis.ac.cn.
authors.forename: Yi
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai, 200032, China. epistat@gmail.com.|Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China. epistat@gmail.com.|Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, 200032, China. epistat@gmail.com.|Collaborative Innovation Center of Social Risks Governance in Health, School of Public Health, Fudan University, Shanghai, 200032, China. epistat@gmail.com.
authors.forename: Zhijie
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000818:Animals; D002681:China / Q000453:epidemiology; D006801:Humans; D060106:Lakes / Q000469:parasitology*; D012423:Rural Health; D012549:Schistosoma japonicum / Q000502:physiology; D012552:Schistosomiasis / Q000453:epidemiology* / Q000469:parasitology; D012908:Snails / Q000469:parasitology; D062211:Spatio-Temporal Analysis
keywords: Poyang Lake Region, China; Schistosomiasis; Spatio-temporal