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Record W4282841017 · doi:10.1371/journal.pmed.1004032

Scaling up target regimens for tuberculosis preventive treatment in Brazil and South Africa: An analysis of costs and cost-effectiveness

2022· article· en· W4282841017 on OpenAlexaff
Ntwali Placide Nsengiyumva, Jonathon R. Campbell, Olivia Oxlade, Juan F Vesga, Christian Lienhardt, Anete Trajman, Dennis Falzon, Saskia den Boon, Nimalan Arinaminpathy, Kevin Schwartzman

Bibliographic record

VenuePLoS Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersWorld Health Organization
KeywordsRegimenMedicineTuberculosisDeveloping countryTransmission (telecommunications)RifampicinEnvironmental healthDemographyPediatricsInternal medicineEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Shorter, safer, and cheaper tuberculosis (TB) preventive treatment (TPT) regimens will enhance uptake and effectiveness. WHO developed target product profiles describing minimum requirements and optimal targets for key attributes of novel TPT regimens. We performed a cost-effectiveness analysis addressing the scale-up of regimens meeting these criteria in Brazil, a setting with relatively low transmission and low HIV and rifampicin-resistant TB (RR-TB) prevalence, and South Africa, a setting with higher transmission and higher HIV and RR-TB prevalence. METHODS AND FINDINGS: We used outputs from a model simulating scale-up of TPT regimens meeting minimal and optimal criteria. We assumed that drug costs for minimal and optimal regimens were identical to 6 months of daily isoniazid (6H). The minimal regimen lasted 3 months, with 70% completion and 80% efficacy; the optimal regimen lasted 1 month, with 90% completion and 100% efficacy. Target groups were people living with HIV (PLHIV) on antiretroviral treatment and household contacts (HHCs) of identified TB patients. The status quo was 6H at 2019 coverage levels for PLHIV and HHCs. We projected TB cases and deaths, TB-associated disability-adjusted life years (DALYs), and costs (in 2020 US dollars) associated with TB from a TB services perspective from 2020 to 2035, with 3% annual discounting. We estimated the expected costs and outcomes of scaling up 6H, the minimal TPT regimen, or the optimal TPT regimen to reach all eligible PLHIV and HHCs by 2023, compared to the status quo. Maintaining current 6H coverage in Brazil (0% of HHCs and 30% of PLHIV treated) would be associated with 1.1 (95% uncertainty range [UR] 1.1-1.2) million TB cases, 123,000 (115,000-132,000) deaths, and 2.5 (2.1-3.1) million DALYs and would cost $1.1 ($1.0-$1.3) billion during 2020-2035. Expanding the 6H, minimal, or optimal regimen to 100% coverage among eligible groups would reduce DALYs by 0.5% (95% UR 1.2% reduction, 0.4% increase), 2.5% (1.8%-3.0%), and 9.0% (6.5%-11.0%), respectively, with additional costs of $107 ($95-$117) million and $51 ($41-$60) million and savings of $36 ($14-$58) million, respectively. Compared to the status quo, costs per DALY averted were $7,608 and $808 for scaling up the 6H and minimal regimens, respectively, while the optimal regimen was dominant (cost savings, reduced DALYs). In South Africa, maintaining current 6H coverage (0% of HHCs and 69% of PLHIV treated) would be associated with 3.6 (95% UR 3.0-4.3) million TB cases, 843,000 (598,000-1,201,000) deaths, and 36.7 (19.5-58.0) million DALYs and would cost $2.5 ($1.8-$3.6) billion. Expanding coverage with the 6H, minimal, or optimal regimen would reduce DALYs by 6.9% (95% UR 4.3%-95%), 15.5% (11.8%-18.9%), and 38.0% (32.7%-43.0%), respectively, with additional costs of $79 (-$7, $151) million and $40 (-$52, $140) million and savings of $608 ($443-$832) million, respectively. Compared to the status quo, estimated costs per DALY averted were $31 and $7 for scaling up the 6H and minimal regimens, while the optimal regimen was dominant. Study limitations included the focus on 2 countries, and no explicit consideration of costs incurred before the decision to prescribe TPT. CONCLUSIONS: Our findings suggest that scale-up of TPT regimens meeting minimum or optimal requirements would likely have important impacts on TB-associated outcomes and would likely be cost-effective or cost saving.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.373
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2022
Admission routes1
Has abstractyes

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