Social network analysis and whole genome sequencing in a cohort study to investigate TB transmission in an educational setting

Simon Packer, Claire Green, Ellen Brooks-Pollock, Katerina Chaintarli, Sarah Harrison, Charles Beck*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Background: TB outbreaks in educational institutions can result in significant transmission and pose a considerable threat to TB control. Investigation using traditional microbiological and epidemiological tools can lead to imprecise screening strategies due to difficulties characterising complex transmission networks. Application of whole genome sequencing (WGS) and social network analysis can provide additional information that may facilitate rapid directed public health action. We report the utility of these methods in combination with traditional approaches for the first time to investigate a TB outbreak in an educational setting. Methods: Latent tuberculosis infection (LTBI) cases were screenees with a positive T-SPOT®.TB test. Active TB cases were defined through laboratory confirmation of M. tuberculosis on culture or through clinical or radiological findings consistent with infection. Epidemiological data were collected from institutional records and screenees. Samples were cultured and analysed using traditional M. tuberculosis typing and WGS. We undertook multivariable multinomial regression and social network analysis to identify exposures associated with case status and risk communities. Results: We identified 189 LTBI cases (13.7% positivity rate) and nine active TB cases from 1377 persons screened. The LTBI positivity rate was 39.1% (99/253) among persons who shared a course with an infectious case (odds ratio 7.3, 95% confidence interval [CI] 5.2 to 10.3). The community structure analysis divided the students into five communities based on connectivity, as opposed to the 11 shared courses. Social network analysis identified that the community including the suspected index case was at significantly elevated risk of active disease (odds ratio 7.5, 95% CI 1.3 to 44.0) and contained eight persons who were lost to follow-up. Five sputum samples underwent WGS, four had zero single nucleotide polymorphism (SNP) differences and one had a single SNP difference. Conclusion: This study demonstrates the public health impact an undiagnosed case of active TB disease can have in an educational setting within a low incidence area. Social network analysis and whole genome sequencing provided greater insight to evolution of the transmission network and identification of communities of risk. These tools provide further information over traditional epidemiological and microbiological approaches to direct public health action in this setting.

Original languageEnglish
Article number154
JournalBMC Infectious Diseases
Issue number1
Publication statusPublished - 13 Feb 2019

Bibliographical note

Funding Information:
We would like to thank the hard and invaluable work of the local TB services at Torbay and South Devon NHS Foundation Trust, the PHE South West Health Protection Team, the PHE National Mycobacterial Reference Laboratory in London and the PHE Regional Centre for Mycobacteriology in Birmingham. This work was partly supported by the National Institute for Health Research Health Protection Research Unit in Evaluation of Interventions at the University of Bristol in partnership with Public Health England. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, the Department of Health or PHE.

Publisher Copyright:
© 2019 The Author(s).


  • Outbreak
  • Screening
  • Social network analysis
  • Tuberculosis
  • Whole genome sequencing


Dive into the research topics of 'Social network analysis and whole genome sequencing in a cohort study to investigate TB transmission in an educational setting'. Together they form a unique fingerprint.

Cite this