The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities

Author:

Marquez Carina1ORCID,Chen Yiqun2,Atukunda Mucunguzi3,Chamie Gabriel1,Balzer Laura B4,Kironde Joel3,Ssemmondo Emmanuel3,Mwangwa Florence3,Kabami Jane3,Owaraganise Asiphas3,Kakande Elijah3,Abbott Rachel1,Ssekyanzi Bob3,Koss Catherine1,Kamya Moses R35,Charlebois Edwin D6,Havlir Diane V1,Petersen Maya L4

Affiliation:

1. Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California , San Francisco, California , USA

2. Department of Biostatistics, University of Washington , Seattle, Washington , USA

3. Infectious Diseases Research Collaboration , Kampala , Uganda

4. Division of Biostatistics, School of Public Health, University of California, Berkeley , Berkeley, California , USA

5. School of Medicine, Makerere University College of Health Sciences , Kampala , Uganda

6. Center for AIDS Prevention Studies, School of Medicine, University of California, San Francisco , San Francisco, California , USA

Abstract

Abstract Background Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies. Methods We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette–Guérin [BCG] vaccination) with targeted maximum likelihood estimation. Results Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1–1.1]) and the most (top 10%) male contacts (1.5 [1.3–1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1–1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2–2.9]). Conclusions Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

Funder

National Institute of Allergy and Infectious Diseases

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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