The role of socio-demographic determinants in the geo-spatial distribution of newly diagnosed HIV infections in small areas of Catalonia (Spain)

Abstract

Abstract Background Spatial visualization of HIV surveillance data could improve the planning of programs to address the HIV epidemic. The objectives of the study were to describe the characteristics and the spatial distribution of newly diagnosed HIV infection in Catalonia and to identify factors associated with HIV infection rates. Methods Surveillance data from the national registry were presented in the form of descriptive and ring maps and used to study the spatial distribution of new HIV diagnoses in Catalonia (2012–2016) and associated risk factors at the small area level (ABS, acronym for “basic health area” in Catalan). Incident cases were modeled using the following as predictors: type of municipality, prevalence of young men and migrant groups, GBMSM activity indicators, and other variables at the aggregated level. Results New HIV diagnoses are heterogeneously distributed across Catalonia. The predictors that proved to be significantly associated with a higher rate of new HIV diagnoses were ABS located in the city of Barcelona (IRR, 2.520; P < 0.001), a higher proportion of men aged 15–44 years (IRR, 1.193; P = 0.003), a higher proportion of GBMSM (IRR, 1.230; P = 0.030), a higher proportion of men from Western Europe (IRR, 1.281; P = 0.003), a higher proportion of men from Latin America (IRR, 1.260; P = 0.003), and a higher number of gay locations (IRR, 2.665; P < 0.001). No association was observed between the HIV diagnosis rate and economic deprivation. Conclusions Ring maps revealed substantial spatial associations for the rate of new HIV diagnoses. New HIV diagnoses are concentrated in ABS located in urban areas. Our results show that, in the case of HIV infection, the socioeconomic deprivation index on which the Catalan government bases its budget allocation policies among the ABS should not be the only criterion used.

Keywords

• HIV
• Small areas
• Income inequality
• Neighborhood environment