About: Using social contact data to predict and compare the impact of social distancing policies with implications for school re-opening

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Using social contact data to predict and compare the impact of social distancing policies with implications for school re-opening
Creator	Danon, Leon Brooks-Pollock, Ellen Keeling, Matt Mclean, Angela Read, Jonathan
source	MedRxiv
abstract	Background Social distancing measures, including school closures, are being used to control SARS-CoV-2 transmission in many countries. Once %22lockdown%22 has driven incidence to low levels, selected activities are being permitted. Re-opening schools is a priority because of the welfare and educational impact of closures on children. However, the impact of school re-opening needs to be considered within the context of other measures. Methods We use social contact data from the UK to predict the impact of social distancing policies on the reproduction number. We calibrate our tool to the COVID-19 epidemic in the UK using publicly available death data and Google Community Mobility Reports. We focus on the impact of re-opening schools against a back-drop of wider social distancing easing. Results We demonstrate that pre-collected social contact data, combined with incidence data and Google Community Mobility Reports, is able to provide a time-varying estimate of the reproduction number (R). From an pre-control setting when R=2.7 (95%CI 2.5, 2.9), we estimate that the minimum reproduction number that can be achieved in the UK without limiting household contacts is 0.45 (95%CI:0.41-0.50); in the absence of other changes, preventing leisure contacts has a smaller impact (R=2.0,95%CI:1.8-2.4) than preventing work contacts (R=1.5,95%CI:1.4-1.7). We find that following lockdown (when R=0.7 (95% CI 0.6, 0.8)), opening primary schools in isolation has a modest impact on transmission R=0.83 (95%CI:0.77-0.90) but that high adherence to other measures is needed. Opening secondary schools as well as primary school is predicted to have a larger overall impact (R=0.95,95%CI:0.85-1.07), however transmission could still be controlled with effective contact tracing. Conclusions Our findings suggest that primary school children can return to school without compromising transmission, however other measures, such as social distancing and contract tracing, are required to control transmission if all age groups are to return to school. Our tool provides a mapping from policies to the reproduction number and can be used by policymakers to compare the impact of social-easing measures, dissect mitigation strategies and support careful localized control strategies.
has issue date	2020-07-27(xsd:dateTime)
bibo:doi	10.1101/2020.07.25.20156471
has license	medrxiv
sha1sum (hex)	4201423d7c7a10b228abea894563d9508acc37bf
schema:url	https://doi.org/10.1101/2020.07.25.20156471
resource representing a document's title	Using social contact data to predict and compare the impact of social distancing policies with implications for school re-opening
resource representing a document's body	covid:4201423d7c7a10b228abea894563d9508acc37bf#body_text
is schema:about of	named entity 'permitted' named entity 'measures' named entity 'COUNTRIES' named entity 'SCHOOLS' named entity 'CONTEXT' »more»

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