AUTHOR=Zheng LiangTing , Liao Bin , Li Yi , Lian Jun , Wang Jingying , Ma Yanli , Feng Ruilin , Hu Wenying , Bai Xianfu 

TITLE=Analysis of influencing factors of AIDS epidemic in Kunming based on PCA-GWR method

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1658700

DOI=10.3389/fpubh.2025.1658700

ISSN=2296-2565

ABSTRACT=BackgroundAs of 2024, an estimated 40.8 million people worldwide were living with HIV, making HIV/AIDS one of the most pressing global public health challenges. Accurate identification of the factors shaping the HIV/AIDS epidemic is essential for developing targeted prevention and control strategies.MethodsThis study uses Principal Component Analysis (PCA) and Geographically Weighted Regression (GWR) to examine spatially varying associations between HIV/AIDS prevalence and three domains—socioeconomic conditions, educational attainment, and healthcare capacity—using Kunming, China, as a case study.ResultsThe results indicate that: (1) the effects of socioeconomic conditions, educational attainment, and healthcare capacity on HIV/AIDS prevalence exhibit significant spatial heterogeneity across Kunming; (2) in the northern part of Kunming—particularly Dongchuan District, Luquan County, Xundian County, and Fumin County—higher prevalence is largely associated with the combined influence of lower economic development and limited educational attainment, with economic development negatively correlated with prevalence and lower educational levels positively correlated with infection rates; and (3) HIV/AIDS prevalence is also related to the level of healthcare services, which is generally negatively correlated with prevalence—i.e., better healthcare conditions are associated with lower infection rates—although areas with more advanced healthcare systems may show higher detection and reporting.ConclusionThe AIDS epidemic results from the interplay of multiple factors, with dominant determinants varying geographically. These findings provide spatially explicit evidence to guide targeted policy development and resource allocation.