title: Geographical information systems-based spatial analysis and implications for syphilis interventions in Jiangsu province, People's Republic of China.
abstract: Spatial distribution rules and risk factors for syphilis were studied in Jiangsu province, People's Republic of China during 2005 and 2009. Trend surface analysis, spatial autocorrelation analysis and spatio-temporal clustering were applied with the incidence rates of the various counties in the province to determine spatial distribution rules and risk factors. Syphilis was found to be most severe in the southern region of the province where many counties could be shown to be hotspots with positive autocorrelation. Clusters were detected in the south-western region of Jiangsu with the county-level city of Yixing as the centre. Temperature, distance from railways and highways, and the normalised difference vegetation index were determined as supporting variables with regard to the transmission of the disease by both univariate and multivariate spatial correlation analyses. Interventions, including health education and awareness campaigns, should be strengthened throughout the province targeting the south-western areas, especially the clusters and hotspots detected in order to improve the situation.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 210029, People's Republic of China.
authors.forename: Yue-Jia
authors.initials: YJ
authors.lastname: Cheng
authors.forename: Jessie
authors.initials: J
authors.lastname: Norris
authors.forename: Chang-Jun
authors.initials: CJ
authors.lastname: Bao
authors.forename: Qi
authors.initials: Q
authors.lastname: Liang
authors.forename: Jian-Li
authors.initials: JL
authors.lastname: Hu
authors.forename: Ying
authors.initials: Y
authors.lastname: Wu
authors.forename: Fen-Yang
authors.initials: FY
authors.lastname: Tang
authors.forename: Wen-Dong
authors.initials: WD
authors.lastname: Liu
authors.forename: Ke-Qin
authors.initials: KQ
authors.lastname: Ding
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhao
authors.forename: Zhi-Hang
authors.initials: ZH
authors.lastname: Peng
authors.forename: Rong-Bin
authors.initials: RB
authors.lastname: Yu
authors.forename: Hua
authors.initials: H
authors.lastname: Wang
authors.forename: Hong-Bing
authors.initials: HB
authors.lastname: Shen
authors.forename: Feng
authors.initials: F
authors.lastname: Chen
mesh_terms: D002681:China / Q000453:epidemiology; D040362:Geographic Information Systems; D006801:Humans; D015994:Incidence; D016012:Poisson Distribution; D011156:Population Density; D015995:Prevalence; D011890:Railroads / Q000706:statistics & numerical data; D012044:Regression Analysis; D012307:Risk Factors; D012621:Seasons; D060386:Sex Workers / Q000706:statistics & numerical data*; D013029:Space-Time Clustering; D013587:Syphilis / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission; D014171:Transients and Migrants / Q000706:statistics & numerical data*; D014186:Transportation / Q000379:methods / Q000706:statistics & numerical data*