Strategizing COVID-19 lockdowns using mobility patterns

During the COVID-19 pandemic, governments have attempted to control infections within their territories by implementing border controls and lockdowns. While large-scale quarantine has been the most successful short-term policy, the enormous costs exerted by lockdowns over long periods are unsustaina...

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Autores principales:	Olha Buchel, Anton Ninkov, Danise Cathel, Yaneer Bar-Yam, Leila Hedayatifar
Formato:	article
Lenguaje:	EN
Publicado:	The Royal Society 2021
Materias:	multi-scale analysis community detection mobility patterns COVID-19 exposure risk Science Q
Acceso en línea:	https://doaj.org/article/4285e5e1a30340b3a328439b6b3e5ef6
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spelling	oai:doaj.org-article:4285e5e1a30340b3a328439b6b3e5ef62021-12-01T08:05:33ZStrategizing COVID-19 lockdowns using mobility patterns10.1098/rsos.2108652054-5703https://doaj.org/article/4285e5e1a30340b3a328439b6b3e5ef62021-12-01T00:00:00Zhttps://royalsocietypublishing.org/doi/10.1098/rsos.210865https://doaj.org/toc/2054-5703During the COVID-19 pandemic, governments have attempted to control infections within their territories by implementing border controls and lockdowns. While large-scale quarantine has been the most successful short-term policy, the enormous costs exerted by lockdowns over long periods are unsustainable. As such, developing more flexible policies that limit transmission without requiring large-scale quarantine is an urgent priority. Here, the dynamics of dismantled community mobility structures within US society during the COVID-19 outbreak are analysed by applying the Louvain method with modularity optimization to weekly datasets of mobile device locations. Our networks are built based on individuals' movements from February to May 2020. In a multi-scale community detection process using the locations of confirmed cases, natural break points from mobility patterns as well as high risk areas for contagion are identified at three scales. Deviations from administrative boundaries were observed in detected communities, indicating that policies informed by assumptions of disease containment within administrative boundaries do not account for high risk patterns of movement across and through these boundaries. We have designed a multi-level quarantine process that takes these deviations into account based on the heterogeneity in mobility patterns. For communities with high numbers of confirmed cases, contact tracing and associated quarantine policies informed by underlying dismantled community mobility structures is of increasing importance.Olha BuchelAnton NinkovDanise CathelYaneer Bar-YamLeila HedayatifarThe Royal Societyarticlemulti-scale analysiscommunity detectionmobility patternsCOVID-19 exposure riskScienceQENRoyal Society Open Science, Vol 8, Iss 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multi-scale analysis community detection mobility patterns COVID-19 exposure risk Science Q
spellingShingle	multi-scale analysis community detection mobility patterns COVID-19 exposure risk Science Q Olha Buchel Anton Ninkov Danise Cathel Yaneer Bar-Yam Leila Hedayatifar Strategizing COVID-19 lockdowns using mobility patterns
description	During the COVID-19 pandemic, governments have attempted to control infections within their territories by implementing border controls and lockdowns. While large-scale quarantine has been the most successful short-term policy, the enormous costs exerted by lockdowns over long periods are unsustainable. As such, developing more flexible policies that limit transmission without requiring large-scale quarantine is an urgent priority. Here, the dynamics of dismantled community mobility structures within US society during the COVID-19 outbreak are analysed by applying the Louvain method with modularity optimization to weekly datasets of mobile device locations. Our networks are built based on individuals' movements from February to May 2020. In a multi-scale community detection process using the locations of confirmed cases, natural break points from mobility patterns as well as high risk areas for contagion are identified at three scales. Deviations from administrative boundaries were observed in detected communities, indicating that policies informed by assumptions of disease containment within administrative boundaries do not account for high risk patterns of movement across and through these boundaries. We have designed a multi-level quarantine process that takes these deviations into account based on the heterogeneity in mobility patterns. For communities with high numbers of confirmed cases, contact tracing and associated quarantine policies informed by underlying dismantled community mobility structures is of increasing importance.
format	article
author	Olha Buchel Anton Ninkov Danise Cathel Yaneer Bar-Yam Leila Hedayatifar
author_facet	Olha Buchel Anton Ninkov Danise Cathel Yaneer Bar-Yam Leila Hedayatifar
author_sort	Olha Buchel
title	Strategizing COVID-19 lockdowns using mobility patterns
title_short	Strategizing COVID-19 lockdowns using mobility patterns
title_full	Strategizing COVID-19 lockdowns using mobility patterns
title_fullStr	Strategizing COVID-19 lockdowns using mobility patterns
title_full_unstemmed	Strategizing COVID-19 lockdowns using mobility patterns
title_sort	strategizing covid-19 lockdowns using mobility patterns
publisher	The Royal Society
publishDate	2021
url	https://doaj.org/article/4285e5e1a30340b3a328439b6b3e5ef6
work_keys_str_mv	AT olhabuchel strategizingcovid19lockdownsusingmobilitypatterns AT antonninkov strategizingcovid19lockdownsusingmobilitypatterns AT danisecathel strategizingcovid19lockdownsusingmobilitypatterns AT yaneerbaryam strategizingcovid19lockdownsusingmobilitypatterns AT leilahedayatifar strategizingcovid19lockdownsusingmobilitypatterns
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Strategizing COVID-19 lockdowns using mobility patterns

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