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Association between tuberculosis in men and social network structure in Kampala, Uganda

BACKGROUND: Globally, tuberculosis disease (TB) is more common among males than females. Recent research proposes that differences in social mixing by sex could alter infection patterns in TB. We examine evidence for two mechanisms by which social-mixing could increase men’s contact rates with TB ca...

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Detalles Bibliográficos
Autores principales: Miller, Paige B., Zalwango, Sarah, Galiwango, Ronald, Kakaire, Robert, Sekandi, Juliet, Steinbaum, Lauren, Drake, John M., Whalen, Christopher C., Kiwanuka, Noah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482622/
https://www.ncbi.nlm.nih.gov/pubmed/34592946
http://dx.doi.org/10.1186/s12879-021-06475-z
Descripción
Sumario:BACKGROUND: Globally, tuberculosis disease (TB) is more common among males than females. Recent research proposes that differences in social mixing by sex could alter infection patterns in TB. We examine evidence for two mechanisms by which social-mixing could increase men’s contact rates with TB cases. First, men could be positioned in social networks such that they contact more people or social groups. Second, preferential mixing by sex could prime men to have more exposure to TB cases. METHODS: We compared the networks of male and female TB cases and healthy matched controls living in Kampala, Uganda. Specifically, we estimated their positions in social networks (network distance to TB cases, degree, betweenness, and closeness) and assortativity patterns (mixing with adult men, women, and children inside and outside the household). RESULTS: The observed network consisted of 11,840 individuals. There were few differences in estimates of node position by sex. We found distinct mixing patterns by sex and TB disease status including that TB cases have proportionally more adult male contacts and fewer contacts with children. CONCLUSIONS: This analysis used a network approach to study how social mixing patterns are associated with TB disease. Understanding these mechanisms may have implications for designing targeted intervention strategies in high-burden populations.