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Tuberculosis and Social Networks:A Narrative Review on How Social Network Data and Metrics Help Explain Tuberculosis Transmission


Affiliations
1 Department of Health Economics, National Institute for Research in Tuberculosis, No. 1, Mayor Sathyamoorthy Road Chetpet, Chennai 600 031, India
2 Department of Statistics, School of Public Health, SRM University Campus, Kattankulathur, Kancheepuram 603 203, India
 

Social network data of tuberculosis (TB) patients could explain the source and pattern of disease spread. A review of the published literature highlights that social network data could identify hidden social or epidemiological links among TB patients and improved TB case finding. Index and betweenness position of patients explained TB transmission. Social networks of TB cases were centred in the hotspots of alcohol, substance uses, sexual activities and hospitals. Multiple sources of TB infection in the community were identified. The findings highlight the potential of social network methods for understanding TB spread in high-burden countries like India.

Keywords

Epidemiological Links, Hotspots, Social Network Matrics, Transmission, Tuberculosis.
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  • Tuberculosis and Social Networks:A Narrative Review on How Social Network Data and Metrics Help Explain Tuberculosis Transmission

Abstract Views: 369  |  PDF Views: 113

Authors

Karikalan Nagarajan
Department of Health Economics, National Institute for Research in Tuberculosis, No. 1, Mayor Sathyamoorthy Road Chetpet, Chennai 600 031, India
Bagavan Das
Department of Statistics, School of Public Health, SRM University Campus, Kattankulathur, Kancheepuram 603 203, India

Abstract


Social network data of tuberculosis (TB) patients could explain the source and pattern of disease spread. A review of the published literature highlights that social network data could identify hidden social or epidemiological links among TB patients and improved TB case finding. Index and betweenness position of patients explained TB transmission. Social networks of TB cases were centred in the hotspots of alcohol, substance uses, sexual activities and hospitals. Multiple sources of TB infection in the community were identified. The findings highlight the potential of social network methods for understanding TB spread in high-burden countries like India.

Keywords


Epidemiological Links, Hotspots, Social Network Matrics, Transmission, Tuberculosis.

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DOI: https://doi.org/10.18520/cs%2Fv116%2Fi7%2F1068-1080