Space-time clustering of recently-diagnosed tuberculosis and impact of ART scale-up: Evidence from an HIV hyper-endemic rural South African population

Abstract

In HIV hyperendemic sub-Saharan African communities, particularly in southern Africa, the likelihood of achieving the Sustainable Development Goal of ending the tuberculosis (TB) epidemic by 2030 is low, due to lack of cost-effective and practical interventions in population settings. We used one of Africa's largest population-based prospective cohorts from rural KwaZulu-Natal Province, South Africa, to measure the spatial variations in the prevalence of recently-diagnosed TB disease, and to quantify the impact of community coverage of antiretroviral therapy (ART) on recently-diagnosed TB disease. We collected data on TB disease episodes from a population-based sample of 41,812 adult individuals between 2009 and 2015. Spatial clusters ('hotspots') of recently-diagnosed TB were identified using a space-time scan statistic. Multilevel logistic regression models were fitted to investigate the relationship between community ART coverage and recently-diagnosed TB. Spatial clusters of recently-diagnosed TB were identified in a region characterized by a high prevalence of HIV and population movement. Every percentage increase in ART coverage was associated with a 2% decrease in the odds of recently-diagnosed TB (aOR = 0.98, 95% CI:0.97-0.99). We identified for the first time the clear occurrence of recently-diagnosed TB hotspots, and quantified potential benefit of increased community ART coverage in lowering tuberculosis, highlighting the need to prioritize the expansion of such effective population interventions targeting high-risk areas.

Figure 1

Estimated HIV prevalence for males (15–49) and females (15–54) in the study surveillance area. Percentage (y-axis) depicts recently-diagnosed TB within the previous 12 months. Horizontal number indicates year.

Figure 2

The study area with high-risk, overlapping space-time recently-diagnosed TB clusters (p < 0.05) identified by the Kulldorff statistic in peri-urban communities near the National Road (in grey color). The National Road continues along the eastern boundary of the surveillance area towards Mozambique. “All” panel shows locations of TB clusters through the entire study period, overlaid on the average prevalence of recently-diagnosed TB. Blue shaded areas show locations of previously identified HIV clusters. Cluster relative risks: A, 2.1; B, 4.4; C, 1.3; D, 1.6; E, 1.3; F, 3.3, G, 6.2, H, 10.1; I, 1.9.

Figure 3

Margin plot of community ART coverage and recently-diagnosed TB