Evidence map›Paper›PMID 22357260›Full record

SynthesisProceedings. Biological sciences2012

How host heterogeneity governs tuberculosis reinfection?

M Gabriela M Gomes, Ricardo Aguas, João S Lopes, Marta C Nunes, Carlota Rebelo, Paula Rodrigues, Claudio J Struchiner

Open access · bronzeAbstract readMeta-Analysis
In one paragraph

Synthesis in Proceedings. Biological sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

29 citing papers in PubMed, 57 citations in OpenAlex.

  1. Article
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  4. Review
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  12. The Importance of Heterogeneity to the Epidemiology of Tuberculosis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2019
    Article
  13. Article
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  15. Article
  16. Article
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  18. Is IPT more effective in high-burden settings? Modelling the effect of tuberculosis incidence on IPT impact.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2017
    Article
  19. 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

7 authors at 4 institutions in 4 countries.

M Gabriela M GomesInstituto Gulbenkian de Ciência, Apartado 14, 2781-901 Oeiras, Portugal. ggomes@igc.gulbenkian.pt
Ricardo Aguas
João S Lopes
Marta C Nunes
Carlota Rebelo
Paula Rodrigues
Claudio J Struchiner
Instituto Gulbenkian de Ciência · PTFundação Oswaldo Cruz · BRFundação para a Ciência e Tecnologia · PTRespiratory and Meningeal Pathogens Research Unit · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recurrent episodes of tuberculosis (TB) can be due to relapse of latent infection or exogenous reinfection, and discrimination is crucial for control planning. Molecular genotyping of Mycobacterium tuberculosis isolates offers concrete opportunities to measure the relative contribution of reinfection in recurrent disease. Here, a mathematical model of TB transmission is fitted to data from 14 molecular epidemiology studies, enabling the estimation of relevant epidemiological parameters. Meta-analysis reveals that rates of reinfection after successful treatment are higher than rates of new TB, raising an important question about the underlying mechanism. We formulate two alternative mechanisms within our model framework: (i) infection increases susceptibility to reinfection or (ii) infection affects individuals differentially, thereby recruiting high-risk individuals to the group at risk for reinfection. The second mechanism is better supported by the fittings to the data, suggesting that reinfection rates are inflated through a population phenomenon that occurs in the presence of heterogeneity in individual risk of infection. As a result, rates of reinfection are higher when measured at the population level even though they might be lower at the individual level. Finally, differential host recruitment is modulated by transmission intensity, being less pronounced when incidence is high.

Indexed as

Disease SusceptibilityGenotypeHumansIncidenceModels, BiologicalMycobacterium tuberculosisSecondary PreventionTuberculosis

Identifiers

PMID22357260
PMCPMC3350683
OpenAlexW2118787988

What OpenQuestion holds

Textmetadata
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.