SynthesisBMJ global health2020
Estimating the yield of tuberculosis from key populations to inform targeted interventions in South Africa: a scoping review.
Synthesis in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Experiences of key populations in multidrug-resistant TB and HIV.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2025Article
- Inferring bivariate associations with continuous data from studies using respondent-driven sampling.Journal of the Royal Statistical Society. Series C, Applied statistics · 2025Article
- Survival analysis shows tuberculosis patients with silicosis experience earlier mortality and need employer-led care models in occupational settings in India.Scientific reports · 2024Article
- Serial Mass Screening for Tuberculosis Among Incarcerated Persons in Brazil.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
- Global efforts to identify and support people with tuberculosis.BMC global and public health · 2024Article
- Burden of tuberculosis in underserved populations in South Africa: A systematic review and meta-analysis.PLOS global public health · 2024Article
- Burden of tuberculosis among vulnerable populations worldwide: an overview of systematic reviews.The Lancet. Infectious diseases · 2023Review
- Prevalence of subclinical pulmonary tuberculosis and its association with HIV in household contacts of index tuberculosis patients in two South African provinces: a secondary, cross-sectional analysis of a cluster-randomised trial.BMC global and public health · 2023Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
introductionTuberculosis (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.
methodsWe 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.
resultsThe 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 (
conclusionsOur 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.