Original Articles
8 September 2025

The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis

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Investigating the spatial effects of population mobility on Human Immunodeficiency Virus (HIV) epidemics provides valuable insights for effective disease control. Data on the incidence and prevalence of HIV and socioeconomic factors from 2013 to 2022 across 31 provinces in China were collected. The Baidu migration index was employed to construct inter-provincial population migration matrices for spatial lag models to evaluate spatial spill-overs and influx risks associated with HIV epidemics macroscopically. This study also analysed the impacts of socioeconomic variables, conducted robustness tests for validation, and performed subgroup analysis stratified by HIV incidence levels. Significant spatial autocorrelation of HIV morbidity was confirmed by finding a positive Moran’s I. The spatial lag model indicated that when a given province had a 1-unit increase in HIV incidence, its average outflow would cause a 0.7068-unit incidence rate increment in other destination provinces, while every unit increase of HIV incidence in other provinces would induce a 0.7013-unit HIV average incidence rise in the original one when it played the role of destination on average. Furthermore, higher population density and lower educational attainment were associated with elevated HIV incidence (p<0.001). The robustness of the findings was verified, and subgroup analysis indicated that reasons besides population mobility should be given priority consideration in regions with higher HIV incidence. The risks of population mobility related to the HIV epidemic were quantified, highlighting the necessity of developing effective and acceptable HIV prevention and control strategies specifically tailored for migrant populations.

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How to Cite



The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis. (2025). Geospatial Health, 20(2). https://doi.org/10.4081/gh.2025.1384