Evidence map›Paper›PMID 42609173›Full record

ArticleGlobal health action2026

Towards ending tuberculosis in South Africa: an uncertainty analysis of the programmes and factors most critical to future declines.

Leigh F Johnson, Mmamapudi Kubjane, Jeffrey W Imai-Eaton, Lauren R Brown, Lise Jamieson, Pren Naidoo, Gaurang Tanna, Gesine Meyer-Rath

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Article in Global health action, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Leigh F JohnsonCentre for Integrated Data and Epidemiological Research, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-2717-011X
Mmamapudi KubjaneHealth Economics and Epidemiology Research Office, University of Witwatersrand, Johannesburg, South Africa.ORCID 0000-0003-1873-198X
Jeffrey W Imai-EatonCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.ORCID 0000-0001-7728-728X
Lauren R BrownSouth African Centre for Epidemiological Modelling and Analysis (SACEMA), Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.ORCID 0000-0002-7697-2397
Lise JamiesonHealth Economics and Epidemiology Research Office, University of Witwatersrand, Johannesburg, South Africa.ORCID 0000-0003-2354-4580
Pren NaidooIndependent Researcher.ORCID 0000-0002-2681-7110
Gaurang TannaGates Foundation, Johannesburg, South Africa.ORCID 0000-0002-0692-2175
Gesine Meyer-RathHealth Economics and Epidemiology Research Office, University of Witwatersrand, Johannesburg, South Africa.ORCID 0000-0003-0439-381X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe WHO End Tuberculosis (TB) strategy targets 80% and 90% reductions in TB incidence and mortality, respectively, between 2015 and 2030.

objectiveTo assess which policy-changeable and external factors are most critical to reducing future TB in South Africa.

methodsWe adapted an existing mathematical model of TB and HIV in South Africa. Prior distributions were specified to represent uncertainty ranges for 27 model parameters that are highly uncertain and potentially important in driving future TB dynamics. Latin Hypercube Sampling was used to sample 1000 parameter combinations from these distributions, and the model was projected to 2040 for each. Partial rank correlation coefficients (PRCCs) were calculated to assess correlation between each parameter and average adult TB incidence and mortality rates over 2025-2040.

resultsAdult TB incidence and mortality rates in South Africa were projected to decline by 46% (95% uncertainty interval [UI]: 17-69%) and 54% (95% UI: 21-84%) respectively by 2030, relative to 2015. The parameters most strongly associated with future TB incidence were the increase in microbiological testing in symptomatic individuals due to near-point-of-care/tongue swab (NPOC/TS) testing (PRCC = -0.67), reductions in social contact rates post-COVID (PRCC = -0.61), the probability of sputum testing in symptomatic individuals in the absence of NPOC/TS testing (PRCC = -0.39), and the efficacy of TB preventive therapy (PRCC = -0.35). TB mortality predictors were similar.

conclusionsIncreasing testing among people with TB symptoms, including through new NPOC/TS technologies, is likely to have the largest impact on progress towards End TB goals in South Africa, though attainment by 2030 is unlikely.

Indexed as

TuberculosisHIV InfectionsHumansIncidenceModels, TheoreticalSouth AfricaUncertaintymathematical modelnear-point-of-care diagnosticsSouth AfricaTongue swab testingtuberculosis

Identifiers

PMID42609173
PMCPMC13487854

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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 Socratic graph.