Estimating the yield of tuberculosis from key populations to inform targeted interventions in South Africa: a scoping review. Issue 7 (6th July 2020)

• Record Type: Journal Article
• Authors: Chimoyi, Lucy Andere; Lienhardt, Christian; Moodley, Nishila; Shete, Priya; Churchyard, Gavin J; Charalambous, Salome
• Is Part Of: BMJ global health. Volume 5:Issue 7(2020)
• Publication Date: 2020-07-06
• Subjects: epidemiology -- tuberculosis -- review; World health -- Periodicals; 362.105
• DOI: 10.1136/bmjgh-2020-002355
• Languages: English
• ISSNs: 2059-7908

Abstract

Abstract : Introduction: Tuberculosis (TB) case finding strategies are recommended to increase yield for TB in key populations. Several key populations are identified in the literature, but techniques for estimating yield and prioritising interventions are needed. Methods: We conducted a scoping review of existing evidence on TB burden to assess contribution of key populations to the TB epidemic in South Africa. Reports, articles and conference abstracts from January 2000 to December 2016 were reviewed to determine TB incidence, prevalence and size of key populations in South Africa. Meta-analysis summarised prevalence and incidence rates of TB in selected key populations assessed for heterogeneity. TB risk was calculated for each key population. Number needed to screen (NNS) to diagnose one case of TB disease was computed. Population attributable fraction estimated the potential impact of interventions on TB cases per population. Results: The search yielded 140 citations, of which 49 were included in the review and a final 32 were included in the meta-analysis. A high prevalence of TB disease was observed in HIV-infected patients with an estimated effect size (ES=0.25, 95% CI 0.20 to 0.30). Heterogeneity was high in this population ( I 2 =94.8%, p value=0.000). The highest incidence rate of TB disease was observed in the HIV-infected population (ES=6.07, 95% CI 4.90 to 7.51). The risk of TB disease in South Africa was high in informal settlements (RR=5.8), HIV-infected (RR=5.4) and inmates (RR=5.0). Most cases of TB would be found in inmates (NNS=26) and household contacts of patients with TB (NNS=25). A larger impact would be observed if interventions are directed towards inmates (31%), people living with HIV (PLHIV (37%) and informal settlements (43%). Conclusions: Our findings illustrate the of value using available epidemiological evidence to inform targeted TB interventions. This review suggests that targeting interventions towards inmates, PLHIV and informal settlements would have a bigger impact on TB burden in South Africa.