Mapping priority neighborhoods: A novel approach to cluster identification in HIV/AIDS population

Abstract BackgroundUrban disadvantaged neighborhoods have higher HIV risk behavior and higher levels of AIDS-related mortality. Studies demonstrate that interventions at the community level focusing on risk groups have increased success rates than individual patient-based based management in the context of HIV/AIDS. We tested a novel approach to identify population groups in need of greater public health efforts to achieve UNAIDS 90-90-90.MethodsWe extracted retrospective data on 2141 HIV/AIDS patients, recruited from 1997-2017 in the regional hospitals in French Guiana. Self-organizing maps were constructed and clusters were identified based on demographic and socioeconomic variables such as age, sex, CD4 counts at Nadir, type of neighborhood, unemployment rate, and presence of opportunistic illness such as Histoplasmosis and Hepatitis B in the sample population.ResultsNeighborhood unemployment rates were identified to have a large impact in the distribution of HIV/AIDS. Also, the risk of disseminated histoplasmosis, the most common AIDS-defining illness in French Guiana, was not associated to any particular neighborhood suggesting that urban socioeconomic features are not the primary drivers of exposure risk.ConclusionSocioeconomically disadvantaged neighborhoods remain hotspots for HIV/AIDS. We conclude that SOM is an effective tool in the identification of risk clusters that may guide public health efforts to optimize HIV prevention and testing in French Guiana and other developing countries.