Evidence map›Paper›PMID 28109661›Full record

ArticleThe Science of the total environment2017

Mapping sites of high TB transmission risk: Integrating the shared air and social behaviour of TB cases and adolescents in a South African township.

Benjamin Patterson, Carl D Morrow, Daniel Kohls, Caroline Deignan, Samuel Ginsburg, Robin Wood

Abstract read
In one paragraph

Article in The Science of the total environment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Observational
  6. 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
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Pathogens (Basel, Switzerland) · 2022
    Review
  13. Article
  14. Article
  15. Review
  16. Spatial drivers of COVID-19 vulnerability in Nigeria.The Pan African medical journal · 2021
    Article
  17. Article
  18. Resource reprioritisation amid competing health risks for TB and COVID-19.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2020
    Article
  19. Performance of a household tuberculosis exposure survey among children in a Latin American setting.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2019
    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

6 authors.

Benjamin PattersonDivision of Infectious Diseases, Columbia University, College of Physicians and Surgeons, New York, NY, USA; Desmond Tutu HIV Centre, IDM, University of Cape Town, Cape Town, South Africa. Electronic address: Benjaminpattersonis@gmail.com.
Carl D MorrowInstitute of Infectious Disease and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Desmond Tutu HIV Centre, IDM, University of Cape Town, Cape Town, South Africa.
Daniel KohlsDesmond Tutu HIV Centre, IDM, University of Cape Town, Cape Town, South Africa.
Caroline DeignanDesmond Tutu HIV Centre, IDM, University of Cape Town, Cape Town, South Africa.
Samuel GinsburgDepartment of Electrical Engineering, Faculty of Engineering & the Built Environment, University of Cape Town, South Africa.
Robin WoodInstitute of Infectious Disease and Molecular Medicine (IDM), Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Desmond Tutu HIV Centre, IDM, University of Cape Town, Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis remains a major public health problem in poverty-stricken areas of the world. Communal gathering places account for the majority of TB transmission in high burden settings.

objectiveTo investigate the social behaviour patterns of individuals who have developed TB disease and adolescents at risk of infection. To develop a cheap and effective method to locate transmission hot spots in high burden communities.

designPortable, combined CO

resultsAnalysis of diaries found that the adolescent group spent greater time in congregate settings compared with the other two groups driven by time spent in school/work (new TB: 1%, recent TB: 8%, and adolescents: 23%). Adolescents also changed their location more frequently (9.0, 6.0, 14.3 changes per day; p<0.001). The RAVs reflected this divergence between the groups (44, 40, 127l; p<0.001). Communal buildings associated with high RAVs were found to be a clinic, two schools and a library. Hot spot analysis revealed the most intense clustering of high RAVs at a community school.

conclusionOur study demonstrates a new methodology to uncover TB transmission hot spots using a technique that avoids the need to pre-select locations. Investigation of a South African township highlighted the high risk potential of schools and high risk social behaviour of adolescents. Consequently the targeting of transmission reduction strategies to schools may prove highly efficacious in high burden settings.

Indexed as

Air MicrobiologyAdolescentAir Pollution, IndoorEnvironmental ExposureHumansMaleSocial BehaviorSouth AfricaTuberculosisAdolescentsGISHot spotSouth AfricaTransmissionTuberculosis

Identifiers

PMID28109661
PMCPMC5312671

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.