Evidence map›Paper›PMID 39095134›Full record

ArticleThe Lancet. Public health2024

The long-term effects of domestic and international tuberculosis service improvements on tuberculosis trends within the USA: a mathematical modelling study.

Nicolas A Menzies, Nicole A Swartwood, Ted Cohen, Suzanne M Marks, Susan A Maloney, Courtney Chappelle, Jeffrey W Miller, Garrett R Beeler Asay, Anand A Date, C Robert Horsburgh and 1 more

Abstract read
In one paragraph

Article in The Lancet. Public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Nicolas A MenziesDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA, USA. Electronic address: nmenzies@hsph.harvard.edu.
Nicole A SwartwoodDepartment 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.
Suzanne M MarksDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Susan A MaloneyDivision of Global HIV and Tuberculosis, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Courtney ChappelleDivision of Global Migration Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Jeffrey W MillerDepartment of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA.
Garrett R Beeler AsayDivision of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Anand A DateDivision of Global HIV and Tuberculosis, Centers for Disease Control and Prevention, Atlanta, GA, USA.
C Robert HorsburghDepartment of Epidemiology, Department of Biostatistics, and Department of Global Health, Boston University School of Public Health, Boston, MA, USA; Department of Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
Joshua A SalomonDepartment of Health Policy, Stanford University, Palo Alto, CA, USA.

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

backgroundFor settings with low tuberculosis incidence, disease elimination is a long-term goal. We investigated pathways to tuberculosis pre-elimination (incidence <1·0 cases per 100 000 people) and elimination (incidence <0·1 cases per 100 000 people) in the USA, where incidence was estimated at 2·9 per 100 000 people in 2023.

methodsUsing a mathematical modelling framework, we simulated how US tuberculosis incidence could be affected by changes in tuberculosis services in the countries of origin for future migrants to the USA, as well as changes in tuberculosis services inside the USA. To do so, we used a linked set of transmission dynamic models, calibrated to demographic and epidemiological data for each setting. We constructed intervention scenarios representing improvements in tuberculosis services internationally and within the USA, individually and in combination, plus a base-case scenario representing continuation of current services. We simulated health and economic outcomes until 2100, using a Bayesian approach to quantify uncertainty in these outcomes.

findingsUnder the base-case scenario, US tuberculosis incidence was projected to decline to 1·8 cases per 100 000 (95% uncertainty interval [UI] 1·5-2·1) in the total population by 2050. Intervention scenarios produced substantial reductions in tuberculosis incidence, with the combination of all domestic and international interventions projected to achieve pre-elimination by 2033 (95% UI 2031-2037). Compared with the base-case scenario, this combination of interventions could avert 101 000 tuberculosis cases (95% UI 84 000-120 000) and 13 300 tuberculosis deaths (95% UI 10 500-16 300) in the USA from 2025 to 2050. Tuberculosis elimination was not projected before 2100.

interpretationStrengthening tuberculosis services domestically, promoting the development of more effective technologies and interventions, and supporting tuberculosis programmes in countries with a high tuberculosis burden are key strategies for accelerating progress towards tuberculosis elimination in the USA.

fundingUS Centers for Disease Control and Prevention.

Indexed as

Models, TheoreticalTuberculosisDisease EradicationHumansIncidenceUnited States

Identifiers

PMID39095134
PMCPMC11344642

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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.