Intersectional forces of urban inequality and the global HIV pandemic: a retrospective analysis

Abstract

To determine how the intersection of increased urban growth and poverty has impacted HIV incidence and prevalence, given growing HIV inequalities globally. Retrospective analysis using combined data from five publicly available, population-level datasets to determine city- and within-urban countrywide estimates of 95-95-95 treatment targets, prevalence and incidence rates from 2015 to 2019. For city-level estimates, we analysed combined data from: Fast-Track City (FTC), SINAN from Brazil and UNAIDS Naomi-Spectrum. Countrywide estimates of HIV prevalence in the urban slum versus non-slum since 2012 were compiled from Population-Based HIV Impact Assessment (PHIA) surveys in 12 countries and Demographic Health Surveys (DHS) in 28 countries. HIV prevalence is generally higher among the urban slum, compared to their non-slum counterparts, thus resulting in national HIV estimates masking nuances in HIV inequalities between the urban slum and non-slum. Specifically, national and city-level HIV estimates mask inequalities within and between cities, with secondary cities often having higher HIV prevalence and incidence rates than capital cities and large urban areas. The urban divide between slum and non-slum populations is a contributor to HIV inequality, often with poorer outcomes in smaller cities than their larger counterparts. Interventions tailored to cities, and particularly those considering local nuances in subpopulations (eg, different genders, ages, roles), are necessary to reduce HIV inequality. Focused HIV programming accounting for structural drivers of inequalities between urban slum and non-slum populations such as inequalities in wealth, education, employment and housing are crucial to closing gaps driving HIV inequalities globally.

Keywords: Global Health; HIV; Public Health.

Figure 1. HIV prevalence (top) and incidence (bottom) since 2015, by city. Sources: Naomi-Spectrum model estimates (81% of prevalence and 91% of incidence data), Fast-Track Cities direct reports (13% of prevalence and 9% of incidence data) and SINAN direct reports (6% of prevalence data).

Figure 2. Prevalence of HIV in Eastern and Southern African Countries by setting (urban ‘slum’ and non-‘slum’). DHS, Demographic Health Surveys; PHIA, Population-Based HIV Impact Assessment.

Figure 3. Prevalence of HIV in West and Central African Countries by setting (urban ‘slum’ and non-‘slum’). DHS, Demographic Health Surveys; PHIA, Population-Based HIV Impact Assessment.

Figure 4. Prevalence of HIV in Latin America and Asia by setting (urban ‘slum’ and non-‘slum’). DHS, Demographic Health Surveys; PHIA, Population-Based HIV Impact Assessment.