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Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world.
Block, Per; Hoffman, Marion; Raabe, Isabel J; Dowd, Jennifer Beam; Rahal, Charles; Kashyap, Ridhi; Mills, Melinda C.
  • Block P; Leverhulme Centre for Demographic Science and Department of Sociology, University of Oxford, Oxford, UK. per.block@sociology.ox.ac.uk.
  • Hoffman M; Department of Humanities, Social and Political Sciences, ETH Zurich, Zurich, Switzerland.
  • Raabe IJ; Institute of Sociology, University of Zurich, Zurich, Switzerland.
  • Dowd JB; Leverhulme Centre for Demographic Science and Department of Sociology, University of Oxford, Oxford, UK.
  • Rahal C; Leverhulme Centre for Demographic Science and Department of Sociology, University of Oxford, Oxford, UK.
  • Kashyap R; Nuffield College, University of Oxford, Oxford, UK.
  • Mills MC; Leverhulme Centre for Demographic Science and Department of Sociology, University of Oxford, Oxford, UK.
Nat Hum Behav ; 4(6): 588-596, 2020 06.
Article in English | MEDLINE | ID: covidwho-531316
Semantic information from SemMedBD (by NLM)
1. Compliance PROCESS_OF World
Subject
Compliance
Predicate
PROCESS_OF
Object
World
2. Strategy PROCESS_OF Social Networks
Subject
Strategy
Predicate
PROCESS_OF
Object
Social Networks
3. Compliance PROCESS_OF World
Subject
Compliance
Predicate
PROCESS_OF
Object
World
4. Strategy PROCESS_OF Social Networks
Subject
Strategy
Predicate
PROCESS_OF
Object
Social Networks
ABSTRACT
Social distancing and isolation have been widely introduced to counter the COVID-19 pandemic. Adverse social, psychological and economic consequences of a complete or near-complete lockdown demand the development of more moderate contact-reduction policies. Adopting a social network approach, we evaluate the effectiveness of three distancing strategies designed to keep the curve flat and aid compliance in a post-lockdown world. These are limiting interaction to a few repeated contacts akin to forming social bubbles; seeking similarity across contacts; and strengthening communities via triadic strategies. We simulate stochastic infection curves incorporating core elements from infection models, ideal-type social network models and statistical relational event models. We demonstrate that a strategic social network-based reduction of contact strongly enhances the effectiveness of social distancing measures while keeping risks lower. We provide scientific evidence for effective social distancing that can be applied in public health messaging and that can mitigate negative consequences of social isolation.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Social Isolation / Communicable Disease Control / Coronavirus Infections / Pandemics / Social Networking / Models, Theoretical Limits: Humans Language: English Journal: Nat Hum Behav Year: 2020 Document Type: Article Affiliation country: S41562-020-0898-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Social Isolation / Communicable Disease Control / Coronavirus Infections / Pandemics / Social Networking / Models, Theoretical Limits: Humans Language: English Journal: Nat Hum Behav Year: 2020 Document Type: Article Affiliation country: S41562-020-0898-6