Evidence map›Paper›PMID 30239609›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2019

A Case-Control Study to Identify Community Venues Associated with Genetically-clustered, Multidrug-resistant Tuberculosis Disease in Lima, Peru.

David P Bui, Eyal Oren, Denise J Roe, Heidi E Brown, Robin B Harris, Gwenan M Knight, Robert H Gilman, Louis Grandjean

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Mobility patterns, activity locations, and TB in Nairobi, Kenya.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2025
    Article
  3. Article
  4. The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  5. Social Contact Patterns Associated With Tuberculosis: A Case-control Study in Southwest Iran.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2022
    Article
  6. Article
  7. Article
  8. 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

8 authors.

David P BuiDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson.
Eyal OrenSchool of Public Health, San Diego State University, California.
Denise J RoeDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson.
Heidi E BrownDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson.
Robin B HarrisDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, The University of Arizona, Tucson.
Gwenan M KnightLondon School of Hygiene and Tropical Medicine, United Kingdom.
Robert H GilmanUniversidad Peruana Cayetano Heredia, Lima, Peru.
Louis GrandjeanLondon School of Hygiene and Tropical Medicine, United Kingdom.

Funding

SOUTHWEST ENVIRONMENTAL HEALTH SCIENCES CENTERP30ES006694 · NIEHS · UNIVERSITY OF ARIZONA · PI DEAN BILLHEIMER · 1994 to 2026
$36.7M
NIEHS NIH HHS P30 ES006694
6 · The paper itself

Abstract

backgroundThe majority of tuberculosis transmission occurs in community settings. Our primary aim in this study was to assess the association between exposure to community venues and multidrug-resistant (MDR) tuberculosis. Our secondary aim was to describe the social networks of MDR tuberculosis cases and controls.

methodsWe recruited laboratory-confirmed MDR tuberculosis cases and community controls that were matched on age and sex. Whole-genome sequencing was used to identify genetically clustered cases. Venue tracing interviews (nonblinded) were conducted to enumerate community venues frequented by participants. Logistic regression was used to assess the association between MDR tuberculosis and person-time spent in community venues. A location-based social network was constructed, with respondents connected if they reported frequenting the same venue, and an exponential random graph model (ERGM) was fitted to model the network.

resultsWe enrolled 59 cases and 65 controls. Participants reported 729 unique venues. The mean number of venues reported was similar in both groups (P = .92). Person-time in healthcare venues (adjusted odds ratio [aOR] = 1.67, P = .01), schools (aOR = 1.53, P < .01), and transportation venues (aOR = 1.25, P = .03) was associated with MDR tuberculosis. Healthcare venues, markets, cinemas, and transportation venues were commonly shared among clustered cases. The ERGM indicated significant community segregation between cases and controls. Case networks were more densely connected.

conclusionsExposure to healthcare venues, schools, and transportation venues was associated with MDR tuberculosis. Intervention across the segregated network of case venues may be necessary to effectively stem transmission.

Indexed as

Drug Resistance, Multiple, BacterialSocial NetworkingAdultAntitubercular AgentsCase-Control StudiesCommerceContact TracingFemaleHealth FacilitiesHumansLogistic ModelsMaleMiddle AgedMotion PicturesMultigene FamilyMycobacterium tuberculosisAntitubercular Agentscommunity transmissiongenotypingmultidrug-resistantsocial networktuberculosis

Identifiers

PMID30239609
PMCPMC7181380

What OpenQuestion holds

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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.