Spatial-temporal Distribution and Influencing Factors of Late Diagnosis of HIV/AIDS Based on Bayes Spatial-temporal Model
10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240305.008
- VernacularTitle: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
- Author:
Li SHAO
1
;
Jijun CHEN
2
;
Yuqi ZHANG
3
;
Jing XU
2
;
Guo LI
1
;
Wenlong GAO
3
Author Information
1. School of Medicine， Xizang Minzu University， Xianyang， Shanxi Province， 712082， China
2. Department of Venereal Diseases and AIDS Prevention and Control， Lanzhou Center for Disease Control and Prevention， 730030， China
3. Department of Epidemiology and Health Statistics， School of Public Health， Lanzhou University， 730000， China
- Publication Type:Journal Article
- Keywords:
AIDS;
HIV;
late diagnosis;
Bayes spatial-temporal model;
distribution characteristics
- From:
Journal of Sun Yat-sen University(Medical Sciences)
2024;45(2):243-252
- CountryChina
- Language:Chinese
-
Abstract:
ObjectivesTo 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 theoretical basis for developing targeted HIV/AIDS prevention and control strategies in Lanzhou. MethodsThe 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. ResultsA 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 fluctuating 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 interval， 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 district and three counties were similar to the overall trend in Lanzhou city， while the risk of late diagnosis in Chengguan District and Qilihe District showed a decreasing trend. The regions with the RR for late diagnosis greater than 1 included Yongdeng 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. ConclusionOur 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 diagnosis 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.
