Evidence map›Paper›PMID 29653698›Full record

SynthesisThe Lancet. Infectious diseases2018

Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions.

Nicolas A Menzies, Emory Wolf, David Connors, Meghan Bellerose, Alyssa N Sbarra, Ted Cohen, Andrew N Hill, Reza Yaesoubi, Kara Galer, Peter J White and 2 more

Erratum issuedAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The Lancet. Infectious diseases, 2018. 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 90 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 4 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

90 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  15. CD4Frontiers in cellular and infection microbiology · 2026
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30 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Nicolas A MenziesDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA. Electronic address: nmenzies@hsph.harvard.edu.
Emory WolfDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
David ConnorsDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
Meghan BelleroseDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
Alyssa N SbarraDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Ted CohenDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Andrew N HillDivision of TB Elimination, US Centers for Disease Control and Prevention, Atlanta, GA, USA.
Reza YaesoubiDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Kara GalerDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
Peter J WhiteMRC Centre for Outbreak Analysis and Modelling and NIHR Health Protection Research Unit in Modelling Methodology, Imperial College London, London, UK; Modelling and Economics Unit, National Infection Service, Public Health England, London, UK.
Ibrahim AbubakarInstitute for Global Health, University College London, London, UK.
Joshua A SalomonDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Center for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.

Funding

Economic Modeling for HIV, Viral Hepatitis, STD, TB and School HealthU38PS004644 · PS · HARVARD SCHOOL OF PUBLIC HEALTH · PI SALOMON, JOSHUA A · 2014 to 2015
$2.9M
Improving the control of multidrug-resistant tuberculosis through targeted screening and use of novel anti-tuberculosis drugsK01AI119603 · NIAID · YALE UNIVERSITY · PI YAESOUBI, REZA · 2016 to 2019
$518k
Medical Research Council MR/K010174/1Medical Research Council MR/R015600/1NCHHSTP CDC HHS U38 PS004644NIAID NIH HHS K01 AI119603Wellcome Trust
6 · The paper itself

Abstract

Mathematical modelling is commonly used to evaluate infectious disease control policy and is influential in shaping policy and budgets. Mathematical models necessarily make assumptions about disease natural history and, if these assumptions are not valid, the results of these studies can be biased. We did a systematic review of published tuberculosis transmission models to assess the validity of assumptions about progression to active disease after initial infection (PROSPERO ID CRD42016030009). We searched PubMed, Web of Science, Embase, Biosis, and Cochrane Library, and included studies from the earliest available date (Jan 1, 1962) to Aug 31, 2017. We identified 312 studies that met inclusion criteria. Predicted tuberculosis incidence varied widely across studies for each risk factor investigated. For population groups with no individual risk factors, annual incidence varied by several orders of magnitude, and 20-year cumulative incidence ranged from close to 0% to 100%. A substantial proportion of modelled results were inconsistent with empirical evidence: for 10-year cumulative incidence, 40% of modelled results were more than double or less than half the empirical estimates. These results demonstrate substantial disagreement between modelling studies on a central feature of tuberculosis natural history. Greater attention to reproducing known features of epidemiology would strengthen future tuberculosis modelling studies, and readers of modelling studies are recommended to assess how well those studies demonstrate their validity.

Indexed as

Disease ProgressionModels, TheoreticalHumansIncidenceRisk FactorsTuberculosis

Identifiers

PMID29653698
PMCPMC6070419

What OpenQuestion holds

Textmetadata
LicenceTDM
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.