Evidence map›Paper›PMID 39759249›Full record

ArticleLancet regional health. Americas2025

Impact of strategic public health interventions to reduce tuberculosis incidence in Brazil: a Bayesian structural time-series scenario analysis.

Klauss Villalva-Serra, Beatriz Barreto-Duarte, Moreno M Rodrigues, Artur T L Queiroz, Leonardo Martinez, Julio Croda, Valeria C Rolla, Afrânio L Kritski, Marcelo Cordeiro-Santos, Timothy R Sterling and 2 more

Erratum issuedAbstract read
In one paragraph

Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Klauss Villalva-SerraCurso de Medicina, Universidade Salvador, Salvador, Brazil.
Beatriz Barreto-DuarteMultinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil.
Moreno M RodriguesMultinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil.
Artur T L QueirozMultinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil.
Leonardo MartinezDepartment of Epidemiology, School of Public Health, Boston University, Boston, MA, USA.
Julio CrodaFiocruz Mato Grosso do Sul, Fundação Oswaldo Cruz, Campo Grande, Brazil.
Valeria C RollaInstituto Nacional de Infectologia Evandro Chagas, Fiocruz, Rio de Janeiro, Brazil.
Afrânio L KritskiPrograma Acadêmico de Tuberculose, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
Marcelo Cordeiro-SantosFundação Medicina Tropical Dr Heitor Vieira Dourado, Manaus, Brazil.
Timothy R SterlingDivision of Infectious Diseases, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA.
Mariana Araújo-PereiraMultinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil.
Bruno B AndradeCurso de Medicina, Universidade Salvador, Salvador, Brazil.

Funding

CCASAnet: Caribbean, Central and South America NetworkU01AI069923 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Pedro Enrique Cahn, Jessica L Castilho · 2006 to 2026
$41.6M
Regional Prospective Observational Research in Tuberculosis (RePORT) – Brazil NetworkU01AI172064 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BRUNO DE BEZERRIL ANDRADE, TIMOTHY R STERLING · 2023 to 2026
$4.0M
NIAID NIH HHS U01 AI069923NIAID NIH HHS U01 AI172064
6 · The paper itself

Abstract

Background: Despite government efforts, tuberculosis (TB) remains a major public health threat in Brazil. In 2023, TB incidence was 39.8 cases per 100,000 population, far above the WHO's target of 6.7 cases per 100,000. Using national-level datasets, we investigated and forecasted the potential impact of proposed public health interventions aimed at reducing TB incidence in Brazil. Methods: Monthly TB surveillance data (January 2018-December 2023) were collected from Brazilian national reporting systems: SINAN-TB (TB cases), SITE-TB (TB drug resistance), and IL-TB (preventive therapy). These data were used to create a multivariable Bayesian Structural Time-Series (BSTS) model, with 5000 Monte-Carlo simulations, which identified key predictors of TB incidence and forecasted these rates from 2024 to 2030 under various scenarios. Findings: Vulnerabilities including incarceration, TB-HIV coinfection and TB-diabetes mellitus, as well as coverages of directly observed therapy (DOT), contact investigation and preventive treatment (TPT) completion rates, were identified as key predictors of TB incidence. Under current trends, we forecasted TB incidence in Brazil to be 42.1 [34.1-49.8] per 100,000 person-years by 2030 (mean [95% prediction intervals]). A scenario considering decreases in TB cases among vulnerable populations resulted in an absolute reduction of -10.6 [-9.4 to -12.0] in projected TB incidence. Additional reductions were seen with increased coverage of DOT, TPT adherence, and contact investigation rates (-14.4 [-13 to -16.2]), and by combining these with efforts to reduce TB cases among vulnerable populations (-23.6 [-26.3 to -41.4]), potentially lowering incidence to 18.5 [7.8-28.4] per 100,000, though still above WHO targets. Interpretation: Our findings demonstrate that interventions focused on enhancing health policies focused on decreasing TB cases among vulnerable populations, such as individuals with TB-HIV coinfection, incarcerated populations, and those with TB-diabetes comorbidity, along with improvements in health management indicators such as DOT implementation, contact investigation coverage, and TPT completion rates, are effective in reducing TB incidence nationwide. Funding: Oswaldo Cruz Foundation.

Indexed as

Directly observed therapyForecastingPublic healthTuberculosisTuberculosis preventive therapyVulnerabilities

Identifiers

PMID39759249
PMCPMC11697790

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.