Evidence map›Paper›PMID 28826444›Full record

ReviewThe international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease2017

Modelling the social and structural determinants of tuberculosis: opportunities and challenges.

D Pedrazzoli, D Boccia, P J Dodd, K Lönnroth, D W Dowdy, A Siroka, M E Kimerling, R G White, R M G J Houben

Abstract readReview
In one paragraph

Review in The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Perspectives from the 2IJTLD open · 2024
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Opportunities to prevent and manage undernutrition to amplify efforts to end TB.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Article
  17. Article
  18. Observational
  19. A scoping review on climate change and tuberculosis.International journal of biometeorology · 2021
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

D PedrazzoliTB Modelling Group, TB Centre and Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London.
D BocciaDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London.
P J DoddHealth Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK.
K LönnrothWorld Health Organization, Global Tuberculosis Programme, Geneva, Switzerland, Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
D W DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
A SirokaWorld Health Organization, Global Tuberculosis Programme, Geneva, Switzerland.
M E KimerlingKNCV, Tuberculosis Foundation, The Hague, The Netherlands.
R G WhiteTB Modelling Group, TB Centre and Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London.
R M G J HoubenTB Modelling Group, TB Centre and Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London.

Funding

World Health Organization 001
6 · The paper itself

Abstract

introductionDespite the close link between tuberculosis (TB) and poverty, most mathematical models of TB have not addressed underlying social and structural determinants.

objectiveTo review studies employing mathematical modelling to evaluate the epidemiological impact of the structural determinants of TB.

methodsWe systematically searched PubMed and personal libraries to identify eligible articles. We extracted data on the modelling techniques employed, research question, types of structural determinants modelled and setting.

resultsFrom 232 records identified, we included eight articles published between 2008 and 2015; six employed population-based dynamic TB transmission models and two non-dynamic analytic models. Seven studies focused on proximal TB determinants (four on nutritional status, one on wealth, one on indoor air pollution, and one examined overcrowding, socio-economic and nutritional status), and one focused on macro-economic influences.

conclusionsFew modelling studies have attempted to evaluate structural determinants of TB, resulting in key knowledge gaps. Despite the challenges of modelling such a complex system, models must broaden their scope to remain useful for policy making. Given the intersectoral nature of the interrelations between structural determinants and TB outcomes, this work will require multidisciplinary collaborations. A useful starting point would be to focus on developing relatively simple models that can strengthen our knowledge regarding the potential effect of the structural determinants on TB outcomes.

Indexed as

Social Determinants of HealthAir Pollution, IndoorHumansModels, TheoreticalNutritional StatusPolicy MakingPopulation DensityPovertySocioeconomic FactorsTuberculosis

Identifiers

PMID28826444
PMCPMC5566999

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.