Cargando…
Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data
Using the classical Susceptible-Infected-Recovered epidemiological model, an analytical formula is derived for the number of beds occupied by Covid-19 patients. The analytical curve is fitted to data in Belgium, France, New York City and Switzerland, with a correlation coefficient exceeding 98.8%, s...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857065/ https://www.ncbi.nlm.nih.gov/pubmed/33558855 http://dx.doi.org/10.1016/j.idm.2021.01.006 |
_version_ | 1783646372272013312 |
---|---|
author | Kozyreff, Gregory |
author_facet | Kozyreff, Gregory |
author_sort | Kozyreff, Gregory |
collection | PubMed |
description | Using the classical Susceptible-Infected-Recovered epidemiological model, an analytical formula is derived for the number of beds occupied by Covid-19 patients. The analytical curve is fitted to data in Belgium, France, New York City and Switzerland, with a correlation coefficient exceeding 98.8%, suggesting that finer models are unnecessary with such macroscopic data. The fitting is used to extract estimates of the doubling time in the ascending phase of the epidemic, the mean recovery time and, for those who require medical intervention, the mean hospitalization time. Large variations can be observed among different outbreaks. |
format | Online Article Text |
id | pubmed-7857065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78570652021-02-04 Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data Kozyreff, Gregory 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 Using the classical Susceptible-Infected-Recovered epidemiological model, an analytical formula is derived for the number of beds occupied by Covid-19 patients. The analytical curve is fitted to data in Belgium, France, New York City and Switzerland, with a correlation coefficient exceeding 98.8%, suggesting that finer models are unnecessary with such macroscopic data. The fitting is used to extract estimates of the doubling time in the ascending phase of the epidemic, the mean recovery time and, for those who require medical intervention, the mean hospitalization time. Large variations can be observed among different outbreaks. KeAi Publishing 2021-02-03 /pmc/articles/PMC7857065/ /pubmed/33558855 http://dx.doi.org/10.1016/j.idm.2021.01.006 Text en © 2021 The Author 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 Kozyreff, Gregory Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title | Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title_full | Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title_fullStr | Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title_full_unstemmed | Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title_short | Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data |
title_sort | hospitalization dynamics during the first covid-19 pandemic wave: sir modelling compared to belgium, france, italy, switzerland and new york city data |
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/PMC7857065/ https://www.ncbi.nlm.nih.gov/pubmed/33558855 http://dx.doi.org/10.1016/j.idm.2021.01.006 |
work_keys_str_mv | AT kozyreffgregory hospitalizationdynamicsduringthefirstcovid19pandemicwavesirmodellingcomparedtobelgiumfranceitalyswitzerlandandnewyorkcitydata |