Evidence map›Paper›PMID 36049488›Full record

ArticleThe Lancet. Global health2022

Excess tuberculosis cases and deaths following an economic recession in Brazil: an analysis of nationally representative disease registry data.

Yunfei Li, Rodrigo de Macedo Couto, Daniele M Pelissari, Layana Costa Alves, Patricia Bartholomay, Ethel L Maciel, Mauro Sanchez, Marcia C Castro, Ted Cohen, Nicolas A Menzies

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
9.2field-weighted citation impact, top 2% of its field
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

15 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Yunfei LiDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA. Electronic address: yunfeili@hsph.harvard.edu.
Rodrigo de Macedo CoutoNational Tuberculosis Programme, Ministry of Health, Brasilia, Brazil.
Daniele M PelissariNational Tuberculosis Programme, Ministry of Health, Brasilia, Brazil.
Layana Costa AlvesNational Tuberculosis Programme, Ministry of Health, Brasilia, Brazil.
Patricia BartholomayNational Tuberculosis Programme, Ministry of Health, Brasilia, Brazil.
Ethel L MacielLaboratorio de Epidemiologia, Universidade Federal do Espirito Santo, Vitória, Brazil.
Mauro SanchezDepartment of Tropical Medicine, University of Brasilia, Brasilia, Brazil.
Marcia C CastroDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Nicolas A MenziesDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA.
Ministério da Saúde · BRHarvard Global Health Institute · USYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Optimal targeting for individual and population-level TB preventionR01AI146555 · NIAID · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI MENZIES, NICOLAS A · 2020 to 2024
$2.5M
NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI146555
6 · The paper itself

Abstract

backgroundIn 2019, tuberculosis incidence and mortality in Brazil were 46 and 3·3 per 100 000 population, respectively, and the country has reported rising tuberculosis case rates since 2016, following an economic crisis beginning in mid-2014. We aimed to estimate the number of excess tuberculosis cases and deaths during the recession period, and assessed potential causes.

methodsIn this multi-level regression modelling study, we extracted tuberculosis case notifications from Brazil's National Notifiable Disease Information System (known as SINAN), and tuberculosis deaths from the Mortality Information System (known as SIM), for all ages. We fitted mixed-effects regression models estimating trends in these outcomes-stratified by sex, age group, and state-during the pre-recession period (Jan 1, 2010-Dec 31, 2014). We calculated excess cases and deaths between Jan 1, 2015, and Dec 31, 2019 (the recession period) as the difference between reported values and a counterfactual of continued pre-recession trends. We examined the relationship between excess cases and possible explanatory factors using ordinary least squares regression. We tested the robustness of our findings to alternative model specifications related to the pre-recession period and criteria for defining tuberculosis deaths.

findingsWe estimated 22 900 excess tuberculosis cases (95% uncertainty interval 18 100-27 500) during 2015-19. By 2019, reported cases were 12% (10-13) higher than predicted by historical trends. 54% (44-66) of excess cases occurred among 20-29-year-old men. In this group, reported cases in 2019 were 30% (25-36) higher than predicted. Excess cases were positively associated with an increasing fraction of cases among incarcerated individuals (p=0·001) and higher unemployment (p=0·04) at the state level. Estimated excess deaths for 2015-19 were not statistically significant from 0 (-600 [-2100 to 1000]). These results were robust to alternative definitions of the pre-recession period and criteria for defining tuberculosis deaths.

interpretationTuberculosis cases in Brazil rose substantially in 2015-19 during the recession, largely affecting young men. This increase seems to be linked to increasing tuberculosis transmission among incarcerated populations. Rising tuberculosis case rates threaten tuberculosis control in Brazil, and highlight the threat posed by prison-based tuberculosis transmission.

fundingUS National Institutes of Health. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.

Indexed as

Economic RecessionTuberculosisAdultBrazilHumansMaleRegistriesUnemploymentYoung Adult

Identifiers

PMID36049488
PMCPMC9472578
OpenAlexW4293509753

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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 OpenQuestion graph.