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Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic

Since the beginning of the coronavirus (COVID-19) global pandemic, digital contact-tracing applications (apps) have been at the centre of attention as a digital tool to enable citizens to monitor their social distancing, which appears to be one of the leading practices for mitigating the spread of a...

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Autores principales: Shubina, Viktoriia, Ometov, Aleksandr, Basiri, Anahid, Lohan, Elena Simona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060546/
http://dx.doi.org/10.1017/S0373463321000175
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author Shubina, Viktoriia
Ometov, Aleksandr
Basiri, Anahid
Lohan, Elena Simona
author_facet Shubina, Viktoriia
Ometov, Aleksandr
Basiri, Anahid
Lohan, Elena Simona
author_sort Shubina, Viktoriia
collection PubMed
description Since the beginning of the coronavirus (COVID-19) global pandemic, digital contact-tracing applications (apps) have been at the centre of attention as a digital tool to enable citizens to monitor their social distancing, which appears to be one of the leading practices for mitigating the spread of airborne infectious diseases. Many countries have been working towards developing suitable digital contact-tracing apps to allow the measurement of the physical distance between citizens and to alert them when contact with an infected individual has occurred. However, the adoption of digital contact-tracing apps has faced several challenges so far, including interoperability between mobile devices and users’ privacy concerns. There is a need to reach a trade-off between the achievable technical performance of new technology, false-positive rates, and social and behavioural factors. This paper reviews a wide range of factors and classifies them into three categories of technical, epidemiological and social ones, and incorporates these into a compact mathematical model. The paper evaluates the effectiveness of digital contact-tracing apps based on received signal strength measurements. The results highlight the limitations, potential and challenges of the adoption of digital contact-tracing apps.
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spelling pubmed-80605462021-04-22 Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic Shubina, Viktoriia Ometov, Aleksandr Basiri, Anahid Lohan, Elena Simona Journal of Navigation Research Article Since the beginning of the coronavirus (COVID-19) global pandemic, digital contact-tracing applications (apps) have been at the centre of attention as a digital tool to enable citizens to monitor their social distancing, which appears to be one of the leading practices for mitigating the spread of airborne infectious diseases. Many countries have been working towards developing suitable digital contact-tracing apps to allow the measurement of the physical distance between citizens and to alert them when contact with an infected individual has occurred. However, the adoption of digital contact-tracing apps has faced several challenges so far, including interoperability between mobile devices and users’ privacy concerns. There is a need to reach a trade-off between the achievable technical performance of new technology, false-positive rates, and social and behavioural factors. This paper reviews a wide range of factors and classifies them into three categories of technical, epidemiological and social ones, and incorporates these into a compact mathematical model. The paper evaluates the effectiveness of digital contact-tracing apps based on received signal strength measurements. The results highlight the limitations, potential and challenges of the adoption of digital contact-tracing apps. Cambridge University Press 2021-04-07 /pmc/articles/PMC8060546/ http://dx.doi.org/10.1017/S0373463321000175 Text en © The Royal Institute of Navigation 2021 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Shubina, Viktoriia
Ometov, Aleksandr
Basiri, Anahid
Lohan, Elena Simona
Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title_full Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title_fullStr Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title_full_unstemmed Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title_short Effectiveness modelling of digital contact-tracing solutions for tackling the COVID-19 pandemic
title_sort effectiveness modelling of digital contact-tracing solutions for tackling the covid-19 pandemic
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060546/
http://dx.doi.org/10.1017/S0373463321000175
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