Social network analysis of COVID-19 transmission in Karnataka, India.
Epidemiol Infect
; 148: e230, 2020 09 25.
Article
em En
| MEDLINE
| ID: mdl-32972463
ABSTRACT
We used social network analysis (SNA) to study the novel coronavirus (COVID-19) outbreak in Karnataka, India, and to assess the potential of SNA as a tool for outbreak monitoring and control. We analysed contact tracing data of 1147 COVID-19 positive cases (mean age 34.91 years, 61.99% aged 11-40, 742 males), anonymised and made public by the Karnataka government. Software tools, Cytoscape and Gephi, were used to create SNA graphics and determine network attributes of nodes (cases) and edges (directed links from source to target patients). Outdegree was 1-47 for 199 (17.35%) nodes, and betweenness, 0.5-87 for 89 (7.76%) nodes. Men had higher mean outdegree and women, higher mean betweenness. Delhi was the exogenous source of 17.44% cases. Bangalore city had the highest caseload in the state (229, 20%), but comparatively low cluster formation. Thirty-four (2.96%) 'super-spreaders' (outdegree ⩾ 5) caused 60% of the transmissions. Real-time social network visualisation can allow healthcare administrators to flag evolving hotspots and pinpoint key actors in transmission. Prioritising these areas and individuals for rigorous containment could help minimise resource outlay and potentially achieve a significant reduction in COVID-19 transmission.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Pneumonia Viral
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Busca de Comunicante
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Infecções por Coronavirus
Limite:
Adolescent
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Adult
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Aged
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Aged80
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Child
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Child, preschool
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Female
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Humans
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Infant
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Male
País como assunto:
Asia
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article