Zhi-Hang Peng
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
Yue-Jia Cheng
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
Kathleen H. Reilly
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China; Tulane University Health Sciences Center, School of Public Health and Tropical Medicine, New Orleans, LA, United States.
Lu Wang
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Qian-Qian Qin
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zheng-Wei Ding
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Guo-Wei Ding
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Ke-Qin Ding
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.
Feng Chen
Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
Ning Wang
*
National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Abstract
Risk maps for the geographical distribution of human immunodeficiency virus (HIV) and the acquired immune deficiency syndrome (AIDS) are needed for the direction of HIV prevention interventions. Our study, based on county-level data on the numbers of HIV/AIDS patients in the Yunnan province, People’s Republic of China, applied trend surface analysis and spatial autocorrelation analysis to demonstrate the geographical distribution of HIV-positive patients in the province. The case load of HIV was found to be most severe in the central-west region of the province. While Kunming county was shown to be negatively correlated with its surrounding counties, many high-burden counties are surrounded by other counties with similar case numbers. We conclude that intervention efforts in Yunnan province should concentrate on the western and northeast regions, targeting the hotspots of infection.