Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

Abstract A contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of C...

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Autores principales:	Jonatan Almagor, Stefano Picascia
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/80883192ef6e4a80ae1b639f9539f25a
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spelling	oai:doaj.org-article:80883192ef6e4a80ae1b639f9539f25a2021-12-02T13:34:00ZExploring the effectiveness of a COVID-19 contact tracing app using an agent-based model10.1038/s41598-020-79000-y2045-2322https://doaj.org/article/80883192ef6e4a80ae1b639f9539f25a2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79000-yhttps://doaj.org/toc/2045-2322Abstract A contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.Jonatan AlmagorStefano PicasciaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jonatan Almagor Stefano Picascia Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
description	Abstract A contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.
format	article
author	Jonatan Almagor Stefano Picascia
author_facet	Jonatan Almagor Stefano Picascia
author_sort	Jonatan Almagor
title	Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
title_short	Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
title_full	Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
title_fullStr	Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
title_full_unstemmed	Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model
title_sort	exploring the effectiveness of a covid-19 contact tracing app using an agent-based model
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/80883192ef6e4a80ae1b639f9539f25a
work_keys_str_mv	AT jonatanalmagor exploringtheeffectivenessofacovid19contacttracingappusinganagentbasedmodel AT stefanopicascia exploringtheeffectivenessofacovid19contacttracingappusinganagentbasedmodel
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Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

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