Geographical information systems-based spatial analysis and implications for syphilis interventions in Jiangsu province, People’s Republic of China

  • Yue-Jia Cheng Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Jessie Norris National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
  • Chang-Jun Bao Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Qi Liang Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Jian-Li Hu Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Ying Wu Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Fen-Yang Tang Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Wen-Dong Liu Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Ke-Qin Ding Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Yang Zhao Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Zhi-Hang Peng | zhihangpeng@yahoo.com.cn Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Rong-Bin Yu Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Hua Wang Jiangsu Province Center for Disease Control and Prevention, Nanjing, China.
  • Hong-Bing Shen Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
  • Feng Chen Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 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.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.
Published
2012-11-01
Info
Issue
Section
Original Articles
Keywords:
syphilis, geographical information systems, trend surface analysis, spatial autocorrelation analysis, spatial correlation analysis, People’s Republic of China.
Statistics
  • Abstract views: 990

  • PDF: 538
How to Cite
Cheng, Y.-J., Norris, J., Bao, C.-J., Liang, Q., Hu, J.-L., Wu, Y., Tang, F.-Y., Liu, W.-D., Ding, K.-Q., Zhao, Y., Peng, Z.-H., Yu, R.-B., Wang, H., Shen, H.-B., & Chen, F. (2012). Geographical information systems-based spatial analysis and implications for syphilis interventions in Jiangsu province, People’s Republic of China. Geospatial Health, 7(1), 63-72. https://doi.org/10.4081/gh.2012.105

Most read articles by the same author(s)