Evidence map›Paper›PMID 34330345›Full record

ArticleThe international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease2021

An approach for improving the quality of country-level TB modelling.

C F McQuaid, M C Clarkson, M Bellerose, K Floyd, R G White, N A Menzies

Abstract read
In one paragraph

Article in The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

C F McQuaidTB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
M C ClarksonTB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
M BelleroseDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
K FloydGlobal TB Programme, World Health Organization, Geneva, Switzerland.
R G WhiteTB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
N 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.

Funding

World Health Organization 001
6 · The paper itself

Abstract

Mathematical modelling is increasingly used to inform budgeting and strategic decision-making by national TB programmes. Despite the importance of these decisions, there is currently no mechanism to review and confirm the appropriateness of modelling analyses. We have developed a benchmarking, reporting, and review (BRR) approach and accompanying tools to allow constructive review of country-level TB modelling applications. This approach has been piloted in five modelling applications and the results of this study have been used to revise and finalise the approach. The BRR approach consists of 1) quantitative benchmarks against which model assumptions and results can be compared, 2) standardised reporting templates and review criteria, and 3) a multi-stage review process providing feedback to modellers during the application, as well as a summary evaluation after completion. During the pilot, use of the tools prompted important changes in the approaches taken to modelling. The pilot also identified issues beyond the scope of a review mechanism, such as a lack of empirical evidence and capacity constraints. This approach provides independent evaluation of the appropriateness of modelling decisions during the course of an application, allowing meaningful changes to be made before results are used to inform decision-making. The use of these tools can improve the quality and transparency of country-level TB modelling applications.

Indexed as

BenchmarkingModels, TheoreticalTuberculosisHumans

Identifiers

PMID34330345
PMCPMC8327628

What OpenQuestion holds

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LicenceCC BY
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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.