Evidence map›Paper›PMID 21514304›Full record

ArticleJournal of theoretical biology2011

Models to understand the population-level impact of mixed strain M. tuberculosis infections.

Rinat Sergeev, Caroline Colijn, Ted Cohen

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Within-Host Mathematical Models of Antibiotic Resistance.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
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  10. How could preventive therapy affect the prevalence of drug resistance? Causes and consequences.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015
    Article
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  14. Review
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  16. Old and new selective pressures on Mycobacterium tuberculosis.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2012
    Review
  17. Article
  18. 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

3 authors at 3 institutions in 3 countries.

Rinat SergeevDivision of Global Health Equity, Brigham and Women's Hospital, 641 Huntington Ave, 02115 Boston, MA, USA. rsergeev@partners.org
Caroline Colijn
Ted Cohen
Harvard University · USPartners In Health · USUniversity of Bristol · GB

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIPSITCH, MARC · 2009 to 2018
$26.4M
Prevalence, risk factors and consequences of complex M. Tuberculosis infectionsDP2OD006663 · OD · BRIGHAM AND WOMEN'S HOSPITAL · PI COHEN, THEODORE H · 2010 to 2010
$2.7M
NIGMS NIH HHS U54 GM088558NIGMS NIH HHS U54GM088558NIH HHS DP2 OD006663NIH HHS DP2OD006663
6 · The paper itself

Abstract

Over the past decade, numerous studies have identified tuberculosis patients in whom more than one distinct strain of Mycobacterium tuberculosis is present. While it has been shown that these mixed strain infections can reduce the probability of treatment success for individuals simultaneously harboring both drug-sensitive and drug-resistant strains, it is not yet known if and how this phenomenon impacts the long-term dynamics for tuberculosis within communities. Strain-specific differences in immunogenicity and associations with drug resistance suggest that a better understanding of how strains compete within hosts will be necessary to project the effects of mixed strain infections on the future burden of drug-sensitive and drug-resistant tuberculosis. In this paper, we develop a modeling framework that allows us to investigate mechanisms of strain competition within hosts and to assess the long-term effects of such competition on the ecology of strains in a population. These models permit us to systematically evaluate the importance of unknown parameters and to suggest priority areas for future experimental research. Despite the current scarcity of data to inform the values of several model parameters, we are able to draw important qualitative conclusions from this work. We find that mixed strain infections may promote the coexistence of drug-sensitive and drug-resistant strains in two ways. First, mixed strain infections allow a strain with a lower basic reproductive number to persist in a population where it would otherwise be outcompeted if has competitive advantages within a co-infected host. Second, some individuals progressing to phenotypically drug-sensitive tuberculosis from a state of mixed drug-sensitive and drug-resistant infection may retain small subpopulations of drug-resistant bacteria that can flourish once the host is treated with antibiotics. We propose that these types of mixed infections, by increasing the ability of low fitness drug-resistant strains to persist, may provide opportunities for compensatory mutations to accumulate and for relatively fit, highly drug-resistant strains of M. tuberculosis to emerge.

Indexed as

Models, TheoreticalAnti-Bacterial AgentsDrug Resistance, BacterialHumansMutationMycobacterium tuberculosisSpecies SpecificityTuberculosisAnti-Bacterial Agents

Identifiers

PMID21514304
PMCPMC3111980
OpenAlexW1985861186

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.