Geographic patterns of poor HIV/AIDS care continuum in District of Columbia

Abstract

Abstract Background Concurrent with the UNAIDS 90-90-90 and NHAS plans, the District of Columbia (DC) launched its 90/90/90/50 plan (Plan) in 2015. The Plan proposes that by 2020, 90% of all DC residents will know their HIV status; 90% of residents living with HIV will be in sustained treatment; 90% of those in treatment will reach “Viral Suppression” and DC will achieve 50% reduction of new HIV cases. To achieve these goals targeted prevention strategies are imperative for areas where the relative risk (RR) of not being linked to care (NL), not retained in any care (NRC) and low viral suppression (NVSP) are highest in the District. These outcomes are denoted in this study as poor outcomes of HIV care continuum. This study applies the Bayesian model for RR for area specific random effects to identify the census tracts with poor HIV care continuum outcomes for DC. Methods This analysis was conducted using cases diagnosed from 2010 to 2015 and reported to the surveillance system from the District of Columbia Department of Health (DC DOH), HIV/AIDS, Hepatitis, STD and TB Administration. The jurisdictions of the District of Columbia is divided into 179 census tracts. It is challenging to plot sparse data in ‘small’ local administrative areas, characteristically which may have a single-count datum for each geographic area. Bayesian methods overcome this problem by assimilating prior information to the underlying RR, making the predicted RR estimates robust. Results The RR of NL is higher in 59 (33%) out of 179 census tracts in DC. The RR of NRC was high in 46 (26%) of the census tracts while 52 census tracts (29%) show a high risk of having NVSP among its residents. This study also identifies clear correlated heterogeneity or clustering is evident in the northern tracts of the district. Conclusion The study finds census tracts with higher RR of poor linkage to care outcomes in the District. These results will inform the Plan which aims to increase targeted testing leading to early initiation of antiretroviral therapy. The uniqueness of this study lies in its translational scope where surveillance data can be used to inform local public health programs and enhance the quality of health for the people with HIV.

Keywords

• HIV care continuum
• Bayesian relative risk
• Disease mapping
• District of Columbia
• Area based prevention intervention strategies