Geographic variation in 5-year mortality following HIV diagnosis: implications for clinical interventions

Abstract

Characterizing spatial distribution of HIV outcomes is vital for targeting interventions to areas most at risk. We performed spatial analysis to identify geographic clusters and factors associated with mortality in KwaZulu-Natal, South Africa. We utilized Sizanani trial (NCT01188941) data, which enrolled participants August 2010-January 2013 and obtained vital status at 5.8 (IQR 5.0-6.4) years of follow-up. We mapped geocoded addresses to 2011 Census-defined small area layer (SAL) centroids, used Kulldorff's spatial scan statistic to identify mortality clusters, and compared socio-demographic factors for SALs within and outside mortality clusters. We assigned 1,143 participants living with HIV (260 [23%] of whom died during follow-up) to 677 SALs. One lower mortality cluster (n = 90, RR = 0.23, p = 0.022) was identified near a hospital outside Durban. SALs in the cluster were younger (24y vs 25y, p < 0.001); had fewer bedrooms/household (3 vs 4, p < 0.001); had more females (52% vs 51%, p = 0.013) and residents with no schooling past age 20 (4% vs 3%, p < 0.001) or no education at all (4% vs 3%, p < 0.001); had fewer residents with income >3,200 ZAR/month (5% vs 9%, p < 0.001); and had reduced access to piped water (p < 0.001), refuse disposal (p < 0.001), and toilets (p < 0.001). Targeted interventions may improve outcomes in areas with similar characteristics.

Keywords: HIV/AIDS; South Africa; geographical information systems; mortality.

Figure 1.

Spatial cluster of lower mortality. (A) Distribution of small area layer centroids of study participants throughout KwaZuluNatal. (B) Lower mortality cluster in relation to the greater Durban area.