中山大学学报（医学科学版）2024，Vol.45Issue(2)：243-252,10.
基于Bayes时空模型分析HIV/AIDS晚发现的时空分布特征及其影响因素
Spatial-temporal Distribution and Influencing Factors of Late Diagnosis of HIV/AIDS Based on Bayes Spatial-temporal Model
摘要
Abstract
[Objectives]To analyze the spatial and temporal clustering characteristics and related influencing factors of late diagnosis of HIV/AIDS in Lanzhou,to identify its high-risk areas and time trends in Lanzhou,and to provide a theo-retical basis for developing targeted HIV/AIDS prevention and control strategies in Lanzhou.[Methods]The subjects of this study were adult HIV/AIDS cases reported in Lanzhou City between 2011 and 2018.Data used in the study were sourced from the Lanzhou Center for Disease Control and Prevention and the Lanzhou Statistical Yearbook.To analyze the spatial distribution characteristics and influencing factors of the relative risk(RR)of late HIV/AIDS diagnosis,Bayes spatial-temporal model was used.[Results]A total of 1984 new HIV/AIDS cases were reported in Lanzhou from 2011 to 2018,with an mean age of 37.51 years and predominantly male(91.8%).The number of late diagnosis cases was 982,with an mean age of 39.67 years and a predominance of males(91.8%).Late diagnosis was more common in older individuals and women with HIV/AIDS.Chengguan District(51.1%),Anning District(50.3%)and Yuzhong County(51.9%)had an above-average proportion of late diagnosis of HIV/AIDS.The proportion of late diagnosis cases in Lanzhou showed a fluctu-ating upward trend from 2011 to 2018.The results of Bayes spatial-temporal model showed that the risk of late HIV/AIDS diagnosis in Lanzhou had fluctuated from 2011 to 2015,and then increased rapidly after 2015[RR(95%credibility inter-val,95%CI)increased from 1.01(0.84,1.23)to 1.11(0.77,1.97)];the trends of risk of late diagnosis in Honggu dis-trict and three counties were similar to the overall trend in Lanzhou city,while the risk of late diagnosis in Chengguan Dis-trict and Qilihe District showed a decreasing trend.The regions with the RR for late diagnosis greater than 1 included Yong-deng County(RR=1.07,95%CI:0.55,1.96),Xigu District(RR=1.04,95%CI:0.67,1.49),Chengguan District(RR =2.41,95%CI:0.85,6.16),and Qilihe District(RR=2.03,95%CI:1.10,3.27).Besides,the heatmap analysis showed that Chengguan District and Qilihe District were the hot spots.The influencing factors analysis showed that the higher GDP per capita(RR=0.65,95%CI:0.35,0.90)and the larger proportion of males with HIV/AIDS cases(RR= 0.53,95%CI:0.19,0.92)could lead to the lower the relative risk of late HIV/AIDS diagnosis.However,the higher the population density(RR=1.35,95%CI:1.01,1.81)caused the higher the risk of late diagnosis.[Conclusion]Our study shows the risk of late diagnosis of HIV/AIDS in Lanzhou was on the rise,and there are significant regional differences.GDP per capita,the proportion of males in HIV/AIDS cases and population density are influencing factors in the late diag-nosis of HIV/AIDS.Therefore,for regions with a high risk of late diagnosis or related risk factors,targeted HIV screening and prevention services should be given priority in order to reduce the proportion and risk of late diagnosis of HIV/AIDS.关键词
艾滋病/人类免疫缺陷病毒/晚发现/Bayes时空模型/分布特征Key words
AIDS/HIV/late diagnosis/Bayes spatial-temporal model/distribution characteristics分类
医药卫生引用本文复制引用
邵莉,陈继军,张宇琦,许静,栗果,高文龙..基于Bayes时空模型分析HIV/AIDS晚发现的时空分布特征及其影响因素[J].中山大学学报（医学科学版）,2024,45(2):243-252,10.基金项目
兰州市卫生健康科技发展项目(A2023004 （）
2021018) （）
