Objective This study analyzes the spatial distribution characteristics of HIV/AIDS patients in townships(streets)of Liaocheng City from 1995 to 2021.The goal is to identify HIV epidemic hotspots and provide a theoretical basis for targeted prevention and control strategies,as well as improved patient management in Liaocheng City.Methods Data on reported HIV/AIDS cases in Liaocheng City from 1995 to 2021 was downloaded from the AIDS Prevention and Control Basic Information System of the China Information System for Disease Control and Prevention.ArcGIS 10.7 was used to generate distribution maps of HIV/AIDS cases and deaths at the township(street)level.Additionally,a spatial autocorrelation analysis was conducted.Results Between 1995 and 2021,a total of 1 140 HIV/AIDS patients were reported in Liaocheng City,with 169 deaths.The annual number of reported cases exhibited a significant upward trend with fluctuations.Deaths also increased but have stabilized in recent years.Among the eight districts(counties and cities)in Liaocheng City,Dongchangfu District reported the highest number of cases(358 cases,31.40％),followed by Chiping District(85 cases,7.46％).The spatial autocorrelation analysis revealed a positive spatial correlation(Moran's I=0.797,Z=13.994,P＜0.001)between the distributions of reported HIV/AIDS patients in Liaocheng City from 1995 to 2021.This indicated the clustering of cases and deaths.Specifically,high-incidence areas were identified in Yansi Street,Daokoupu Street,Beicheng Street,Xinqu Street,Gulou Street,Liuyuan Street,Jiangguantun Street,Dongcheng Street,and Lepingpu Town.Conversely,no spatial autocorrelation was found for the distribution of HIV/AIDS deaths(Moran's I=-0.062,Z=-0.902,P=0.367).Conclusions The clustering of HIV/AIDS patients in Liaocheng City from 1995 to 2021.Dongchangfu District and Chiping District are key areas for focused HIV epidemic prevention and control effects.Strengthening comprehensive measures in these hotspot areas and developing targeted prevention strategies are crucial to reduce the spread of HIV.
NETL
NSTL
万方数据
