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Predicting COVID-19 in very large countries: The case of Brazil
This work presents a practical proposal for estimating health system utilization for COVID-19 cases. The novel methodology developed is based on the dynamic model known as Susceptible, Infected, Removed and Dead (SIRD). The model was modified to focus on the healthcare system dynamics, rather than m...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248665/ https://www.ncbi.nlm.nih.gov/pubmed/34197489 http://dx.doi.org/10.1371/journal.pone.0253146 |
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author | Parro, V. C. Lafetá, M. L. M. Pait, F. Ipólito, F. B. Toporcov, T. N. |
author_facet | Parro, V. C. Lafetá, M. L. M. Pait, F. Ipólito, F. B. Toporcov, T. N. |
author_sort | Parro, V. C. |
collection | PubMed |
description | This work presents a practical proposal for estimating health system utilization for COVID-19 cases. The novel methodology developed is based on the dynamic model known as Susceptible, Infected, Removed and Dead (SIRD). The model was modified to focus on the healthcare system dynamics, rather than modeling all cases of the disease. It was tuned using data available for each Brazilian state and updated with daily figures. A figure of merit that assesses the quality of the model fit to the data was defined and used to optimize the free parameters. The parameters of an epidemiological model for the whole of Brazil, comprising a linear combination of the models for each state, were estimated considering the data available for the 26 Brazilian states. The model was validated, and strong adherence was demonstrated in most cases. |
format | Online Article Text |
id | pubmed-8248665 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-82486652021-07-09 Predicting COVID-19 in very large countries: The case of Brazil Parro, V. C. Lafetá, M. L. M. Pait, F. Ipólito, F. B. Toporcov, T. N. PLoS One Research Article This work presents a practical proposal for estimating health system utilization for COVID-19 cases. The novel methodology developed is based on the dynamic model known as Susceptible, Infected, Removed and Dead (SIRD). The model was modified to focus on the healthcare system dynamics, rather than modeling all cases of the disease. It was tuned using data available for each Brazilian state and updated with daily figures. A figure of merit that assesses the quality of the model fit to the data was defined and used to optimize the free parameters. The parameters of an epidemiological model for the whole of Brazil, comprising a linear combination of the models for each state, were estimated considering the data available for the 26 Brazilian states. The model was validated, and strong adherence was demonstrated in most cases. Public Library of Science 2021-07-01 /pmc/articles/PMC8248665/ /pubmed/34197489 http://dx.doi.org/10.1371/journal.pone.0253146 Text en © 2021 Parro et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Parro, V. C. Lafetá, M. L. M. Pait, F. Ipólito, F. B. Toporcov, T. N. Predicting COVID-19 in very large countries: The case of Brazil |
title | Predicting COVID-19 in very large countries: The case of Brazil |
title_full | Predicting COVID-19 in very large countries: The case of Brazil |
title_fullStr | Predicting COVID-19 in very large countries: The case of Brazil |
title_full_unstemmed | Predicting COVID-19 in very large countries: The case of Brazil |
title_short | Predicting COVID-19 in very large countries: The case of Brazil |
title_sort | predicting covid-19 in very large countries: the case of brazil |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248665/ https://www.ncbi.nlm.nih.gov/pubmed/34197489 http://dx.doi.org/10.1371/journal.pone.0253146 |
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