On the use of aggregated human mobility data to estimate the reproduction number
Abstract The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. W...
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Nature Portfolio
2021
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oai:doaj.org-article:329e30d2cf8842e095d5c9beff2bdf422021-12-05T12:15:39ZOn the use of aggregated human mobility data to estimate the reproduction number10.1038/s41598-021-02760-82045-2322https://doaj.org/article/329e30d2cf8842e095d5c9beff2bdf422021-12-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-02760-8https://doaj.org/toc/2045-2322Abstract The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. We introduce a theoretical framework to explain and predict changes in the reproduction number of SARS-CoV-2 in terms of aggregated individual mobility and interpersonal proximity (alongside other epidemiological and environmental variables) during and after the lockdown period. We use an infection-age structured model described by a renewal equation. The model predicts the evolution of the reproduction number up to a week ahead of well-established estimates used in the literature. We show how lockdown policies, via reduction of proximity and mobility, reduce the impact of CoViD-19 and mitigate the risk of disease resurgence. We validate our theoretical framework using data from Google, Voxel51, Unacast, The CoViD-19 Mobility Data Network, and Analisi Distribuzione Aiuti.Fabio VanniDavid LambertLuigi PalatellaPaolo GrigoliniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021) |
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Medicine R Science Q Fabio Vanni David Lambert Luigi Palatella Paolo Grigolini On the use of aggregated human mobility data to estimate the reproduction number |
description |
Abstract The reproduction number of an infectious disease, such as CoViD-19, can be described through a modified version of the susceptible-infected-recovered (SIR) model with time-dependent contact rate, where mobility data are used as proxy of average movement trends and interpersonal distances. We introduce a theoretical framework to explain and predict changes in the reproduction number of SARS-CoV-2 in terms of aggregated individual mobility and interpersonal proximity (alongside other epidemiological and environmental variables) during and after the lockdown period. We use an infection-age structured model described by a renewal equation. The model predicts the evolution of the reproduction number up to a week ahead of well-established estimates used in the literature. We show how lockdown policies, via reduction of proximity and mobility, reduce the impact of CoViD-19 and mitigate the risk of disease resurgence. We validate our theoretical framework using data from Google, Voxel51, Unacast, The CoViD-19 Mobility Data Network, and Analisi Distribuzione Aiuti. |
format |
article |
author |
Fabio Vanni David Lambert Luigi Palatella Paolo Grigolini |
author_facet |
Fabio Vanni David Lambert Luigi Palatella Paolo Grigolini |
author_sort |
Fabio Vanni |
title |
On the use of aggregated human mobility data to estimate the reproduction number |
title_short |
On the use of aggregated human mobility data to estimate the reproduction number |
title_full |
On the use of aggregated human mobility data to estimate the reproduction number |
title_fullStr |
On the use of aggregated human mobility data to estimate the reproduction number |
title_full_unstemmed |
On the use of aggregated human mobility data to estimate the reproduction number |
title_sort |
on the use of aggregated human mobility data to estimate the reproduction number |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/329e30d2cf8842e095d5c9beff2bdf42 |
work_keys_str_mv |
AT fabiovanni ontheuseofaggregatedhumanmobilitydatatoestimatethereproductionnumber AT davidlambert ontheuseofaggregatedhumanmobilitydatatoestimatethereproductionnumber AT luigipalatella ontheuseofaggregatedhumanmobilitydatatoestimatethereproductionnumber AT paologrigolini ontheuseofaggregatedhumanmobilitydatatoestimatethereproductionnumber |
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1718372067052617728 |