Evidence map›Paper›PMID 20877639›Full record

ArticlePloS one2010

Heightened vulnerability to MDR-TB epidemics after controlling drug-susceptible TB.

Jason D Bishai, William R Bishai, David M Bishai

Abstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Jason D BishaiSchool of Humanities and Sciences, Stanford University, Stanford, California, USA.
William R Bishai
David M Bishai

Funding

Mycobacterium tuberculosis Survival Regulatory GenesR01AI037856 · NIAID · JOHNS HOPKINS UNIVERSITY · PI BISHAI, WILLIAM RAMSES · 1997 to 2020
$7.2M
GENE REGULATION AND VIRULENCE IN TB AND MACR01AI036973 · NIAID · JOHNS HOPKINS UNIVERSITY · PI BISHAI, WILLIAM RAMSES · 1999 to 2014
$5.7M
NIAID NIH HHS 5R01AI036973-15NIAID NIH HHS 5R01AI037856-10NIAID NIH HHS R01 AI036973NIAID NIH HHS R01 AI037856
6 · The paper itself

Abstract

backgroundPrior infection with one strain TB has been linked with diminished likelihood of re-infection by a new strain. This paper attempts to determine the role of declining prevalence of drug-susceptible TB in enabling future epidemics of MDR-TB.

methodsA computer simulation of MDR-TB epidemics was developed using an agent-based model platform programmed in NetLogo (See http://mdr.tbtools.org/). Eighty-one scenarios were created, varying levels of treatment quality, diagnostic accuracy, microbial fitness cost, and the degree of immunogenicity elicited by drug-susceptible TB. Outcome measures were the number of independent MDR-TB cases per trial and the proportion of trials resulting in MDR-TB epidemics for a 500 year period after drug therapy for TB is introduced.

resultsMDR-TB epidemics propagated more extensively after TB prevalence had fallen. At a case detection rate of 75%, improving therapeutic compliance from 50% to 75% can reduce the probability of an epidemic from 45% to 15%. Paradoxically, improving the case-detection rate from 50% to 75% when compliance with DOT is constant at 75% increases the probability of MDR-TB epidemics from 3% to 45%.

conclusionsThe ability of MDR-TB to spread depends on the prevalence of drug-susceptible TB. Immunologic protection conferred by exposure to drug-susceptible TB can be a crucial factor that prevents MDR-TB epidemics when TB treatment is poor. Any single population that successfully reduces its burden of drug-susceptible TB will have reduced herd immunity to externally or internally introduced strains of MDR-TB and can experience heightened vulnerability to an epidemic. Since countries with good TB control may be more vulnerable, their self interest dictates greater promotion of case detection and DOTS implementation in countries with poor control to control their risk of MDR-TB.

Indexed as

EpidemicsAntitubercular AgentsComputer SimulationHumansModels, BiologicalPrevalenceTuberculosis, Multidrug-ResistantAntitubercular Agents

Identifiers

PMID20877639
PMCPMC2943899

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.