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Transmission network analysis in tuberculosis contact investigations
Victoria J Cook1, Sumi J Sun, Jane Tapia
1Department of Medicine, University of British Columbia, 655 W. 12th Avenue, Vancouver, BC, Canada. mailvictoria.cook@bccdc.ca
The Journal of Infectious Diseases
|November 17, 2007
Summary
Social network analysis (SNA) effectively identifies Mycobacterium tuberculosis transmission patterns and connections missed by traditional methods. This approach aids in prioritizing tuberculosis contact investigations by revealing social links and high-risk locations.
Area of Science:
- Epidemiology
- Public Health
- Network Science
Background:
- Social network analysis (SNA) offers a novel method for collecting and analyzing infectious disease transmission data.
- Investigating the utility of SNA in detecting Mycobacterium tuberculosis (TB) transmission patterns and optimizing TB contact investigations.
Purpose of the Study:
- To assess the effectiveness of SNA in identifying TB transmission networks.
- To determine if SNA can enhance the prioritization of contact investigations for tuberculosis.
Main Methods:
- Collected demographic and clinical data, alongside social aggregation place data via questionnaires.
- Analyzed social networks using case-contact, contact-contact, case-place, and contact-place links.
- Utilized molecular genotyping to validate SNA-identified TB transmission clusters.
Main Results:
- SNA connected TB patients missed by conventional methods through shared contacts or locations.
- SNA identified transmission clusters before genotyping confirmation in some cases.
- A significant correlation (P<.01) was found between positive tuberculin skin tests (TST) and denser network areas.
Conclusions:
- Collecting data on social aggregation places is valuable for prioritizing TB contact investigations.
- Developing SNA capacity can improve the systematic collection, analysis, and interpretation of TB contact investigation data.
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