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An evaluation of COVID-19 in Italy: A data-driven modeling analysis
The novel coronavirus (COVID-19) that has been spreading worldwide since December 2019 has sickened millions of people, lock down major cities and some countries, prompted unprecedented global travel restrictions. Real data-driven modeling is an effort to help evaluate and curb the spread of the nov...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347309/ https://www.ncbi.nlm.nih.gov/pubmed/32766461 http://dx.doi.org/10.1016/j.idm.2020.06.007 |
_version_ | 1783556565391900672 |
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author | Ding, Yongmei Gao, Liyuan |
author_facet | Ding, Yongmei Gao, Liyuan |
author_sort | Ding, Yongmei |
collection | PubMed |
description | The novel coronavirus (COVID-19) that has been spreading worldwide since December 2019 has sickened millions of people, lock down major cities and some countries, prompted unprecedented global travel restrictions. Real data-driven modeling is an effort to help evaluate and curb the spread of the novel virus. Lockdowns and the effectiveness of reduction in the contacts in Italy has been measured via our modified model, with the addition of auxiliary and state variables that represent, contacts with infected, conversion rate and latent propagation. Results show the decrease in infected people due to stay-at-home orders and tracing quarantine intervention. The effect of quarantine and centralized medical treatment was also measured through numerical modeling analysis. |
format | Online Article Text |
id | pubmed-7347309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-73473092020-07-10 An evaluation of COVID-19 in Italy: A data-driven modeling analysis Ding, Yongmei Gao, Liyuan Infect Dis Model Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu The novel coronavirus (COVID-19) that has been spreading worldwide since December 2019 has sickened millions of people, lock down major cities and some countries, prompted unprecedented global travel restrictions. Real data-driven modeling is an effort to help evaluate and curb the spread of the novel virus. Lockdowns and the effectiveness of reduction in the contacts in Italy has been measured via our modified model, with the addition of auxiliary and state variables that represent, contacts with infected, conversion rate and latent propagation. Results show the decrease in infected people due to stay-at-home orders and tracing quarantine intervention. The effect of quarantine and centralized medical treatment was also measured through numerical modeling analysis. KeAi Publishing 2020-07-09 /pmc/articles/PMC7347309/ /pubmed/32766461 http://dx.doi.org/10.1016/j.idm.2020.06.007 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu Ding, Yongmei Gao, Liyuan An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title | An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title_full | An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title_fullStr | An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title_full_unstemmed | An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title_short | An evaluation of COVID-19 in Italy: A data-driven modeling analysis |
title_sort | evaluation of covid-19 in italy: a data-driven modeling analysis |
topic | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347309/ https://www.ncbi.nlm.nih.gov/pubmed/32766461 http://dx.doi.org/10.1016/j.idm.2020.06.007 |
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