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Using a real-world network to model localized COVID-19 control strategies

Abstract:
Case isolation and contact tracing can contribute to the control of COVID-19 outbreaks1,2. However, it remains unclear how real-world social networks could influence the effectiveness and efficiency of such approaches. To address this issue, we simulated control strategies for SARS-CoV-2 transmission in a real-world social network generated from high-resolution GPS data that were gathered in the course of a citizen-science experiment3,4. We found that tracing the contacts of contacts reduced the size of simulated outbreaks more than tracing of only contacts, but this strategy also resulted in almost half of the local population being quarantined at a single point in time. Testing and releasing non-infectious individuals from quarantine led to increases in outbreak size, suggesting that contact tracing and quarantine might be most effective as a ‘local lockdown’ strategy when contact rates are high. Finally, we estimated that combining physical distancing with contact tracing could enable epidemic control while reducing the number of quarantined individuals. Our findings suggest that targeted tracing and quarantine strategies would be most efficient when combined with other control measures such as physical distancing.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41591-020-1036-8

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Zoology
Sub department:
Zoology
Oxford college:
Merton College
Role:
Author
ORCID:
0000-0001-7183-4115
More by this author
Role:
Author
ORCID:
0000-0003-2683-0849
More by this author
Role:
Author
ORCID:
0000-0001-6000-8387


Publisher:
Nature Research
Journal:
Nature Medicine More from this journal
Volume:
26
Issue:
2020
Pages:
1616–1622
Publication date:
2020-08-07
Acceptance date:
2020-07-27
DOI:
EISSN:
1546-170X
ISSN:
1078-8956


Language:
English
Keywords:
Pubs id:
1124145
Local pid:
pubs:1124145
Deposit date:
2020-08-07
ARK identifier:

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