Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment
Abstract Targeted contact-tracing through mobile phone apps has been proposed as an instrument to help contain the spread of COVID-19 and manage the lifting of nation-wide lock-downs currently in place in USA and Europe. However, there is an ongoing debate on its potential efficacy, especially in li...
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Format: | Article |
Language: | English |
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Nature Portfolio
2021-01-01
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Series: | npj Digital Medicine |
Online Access: | https://doi.org/10.1038/s41746-020-00374-4 |
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author | Alberto Ferrari Enrico Santus Davide Cirillo Miguel Ponce-de-Leon Nicola Marino Maria Teresa Ferretti Antonella Santuccione Chadha Nikolaos Mavridis Alfonso Valencia |
author_facet | Alberto Ferrari Enrico Santus Davide Cirillo Miguel Ponce-de-Leon Nicola Marino Maria Teresa Ferretti Antonella Santuccione Chadha Nikolaos Mavridis Alfonso Valencia |
author_sort | Alberto Ferrari |
collection | DOAJ |
description | Abstract Targeted contact-tracing through mobile phone apps has been proposed as an instrument to help contain the spread of COVID-19 and manage the lifting of nation-wide lock-downs currently in place in USA and Europe. However, there is an ongoing debate on its potential efficacy, especially in light of region-specific demographics. We built an expanded S I R model of COVID-19 epidemics that accounts for region-specific population densities, and we used it to test the impact of a contact-tracing app in a number of scenarios. Using demographic and mobility data from Italy and Spain, we used the model to simulate scenarios that vary in baseline contact rates, population densities, and fraction of app users in the population. Our results show that, in support of efficient isolation of symptomatic cases, app-mediated contact-tracing can successfully mitigate the epidemic even with a relatively small fraction of users, and even suppress altogether with a larger fraction of users. However, when regional differences in population density are taken into consideration, the epidemic can be significantly harder to contain in higher density areas, highlighting potential limitations of this intervention in specific contexts. This work corroborates previous results in favor of app-mediated contact-tracing as mitigation measure for COVID-19, and draws attention on the importance of region-specific demographic and mobility factors to achieve maximum efficacy in containment policies. |
first_indexed | 2024-03-09T09:02:50Z |
format | Article |
id | doaj.art-1dd0165ab9d2495b8cccf21a610df530 |
institution | Directory Open Access Journal |
issn | 2398-6352 |
language | English |
last_indexed | 2024-03-09T09:02:50Z |
publishDate | 2021-01-01 |
publisher | Nature Portfolio |
record_format | Article |
series | npj Digital Medicine |
spelling | doaj.art-1dd0165ab9d2495b8cccf21a610df5302023-12-02T11:06:36ZengNature Portfolionpj Digital Medicine2398-63522021-01-01411810.1038/s41746-020-00374-4Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containmentAlberto Ferrari0Enrico Santus1Davide Cirillo2Miguel Ponce-de-Leon3Nicola Marino4Maria Teresa Ferretti5Antonella Santuccione Chadha6Nikolaos Mavridis7Alfonso Valencia8FROM Research Foundation, Papa Giovanni XXIII HospitalBayer, Decision Science & Advanced Analytics for MA, PV & RA DivisionBarcelona Supercomputing Center (BSC)Barcelona Supercomputing Center (BSC)Women’s Brain Project (WBP)Women’s Brain Project (WBP)Women’s Brain Project (WBP)Women’s Brain Project (WBP)Barcelona Supercomputing Center (BSC)Abstract Targeted contact-tracing through mobile phone apps has been proposed as an instrument to help contain the spread of COVID-19 and manage the lifting of nation-wide lock-downs currently in place in USA and Europe. However, there is an ongoing debate on its potential efficacy, especially in light of region-specific demographics. We built an expanded S I R model of COVID-19 epidemics that accounts for region-specific population densities, and we used it to test the impact of a contact-tracing app in a number of scenarios. Using demographic and mobility data from Italy and Spain, we used the model to simulate scenarios that vary in baseline contact rates, population densities, and fraction of app users in the population. Our results show that, in support of efficient isolation of symptomatic cases, app-mediated contact-tracing can successfully mitigate the epidemic even with a relatively small fraction of users, and even suppress altogether with a larger fraction of users. However, when regional differences in population density are taken into consideration, the epidemic can be significantly harder to contain in higher density areas, highlighting potential limitations of this intervention in specific contexts. This work corroborates previous results in favor of app-mediated contact-tracing as mitigation measure for COVID-19, and draws attention on the importance of region-specific demographic and mobility factors to achieve maximum efficacy in containment policies.https://doi.org/10.1038/s41746-020-00374-4 |
spellingShingle | Alberto Ferrari Enrico Santus Davide Cirillo Miguel Ponce-de-Leon Nicola Marino Maria Teresa Ferretti Antonella Santuccione Chadha Nikolaos Mavridis Alfonso Valencia Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment npj Digital Medicine |
title | Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment |
title_full | Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment |
title_fullStr | Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment |
title_full_unstemmed | Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment |
title_short | Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment |
title_sort | simulating sars cov 2 epidemics by region specific variables and modeling contact tracing app containment |
url | https://doi.org/10.1038/s41746-020-00374-4 |
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