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Estimative of real number of infections by COVID-19 in Brazil and possible scenarios
This paper attempts to provide methods to estimate the real scenario of the novel coronavirus pandemic in Brazil, specifically in the states of Sao Paulo, Pernambuco, Espirito Santo, Amazonas and the Federal District. By the use of a SEIRD mathematical model with age division, we predict the infecti...
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/PMC7513932/ https://www.ncbi.nlm.nih.gov/pubmed/32995682 http://dx.doi.org/10.1016/j.idm.2020.09.004 |
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author | Cintra, H.P.C. Fontinele, F.N. |
author_facet | Cintra, H.P.C. Fontinele, F.N. |
author_sort | Cintra, H.P.C. |
collection | PubMed |
description | This paper attempts to provide methods to estimate the real scenario of the novel coronavirus pandemic in Brazil, specifically in the states of Sao Paulo, Pernambuco, Espirito Santo, Amazonas and the Federal District. By the use of a SEIRD mathematical model with age division, we predict the infection and death curves, stating the peak date for Brazil and above states. We also carry out a prediction for the ICU demand in these states and for how severe possible collapse in the local health system would be. Finally, we establish some future scenarios including the relaxation on social isolation and the introduction of vaccines and other efficient therapeutic treatments against the virus. |
format | Online Article Text |
id | pubmed-7513932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-75139322020-09-25 Estimative of real number of infections by COVID-19 in Brazil and possible scenarios Cintra, H.P.C. Fontinele, F.N. 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 This paper attempts to provide methods to estimate the real scenario of the novel coronavirus pandemic in Brazil, specifically in the states of Sao Paulo, Pernambuco, Espirito Santo, Amazonas and the Federal District. By the use of a SEIRD mathematical model with age division, we predict the infection and death curves, stating the peak date for Brazil and above states. We also carry out a prediction for the ICU demand in these states and for how severe possible collapse in the local health system would be. Finally, we establish some future scenarios including the relaxation on social isolation and the introduction of vaccines and other efficient therapeutic treatments against the virus. KeAi Publishing 2020-09-24 /pmc/articles/PMC7513932/ /pubmed/32995682 http://dx.doi.org/10.1016/j.idm.2020.09.004 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/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 Cintra, H.P.C. Fontinele, F.N. Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title | Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title_full | Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title_fullStr | Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title_full_unstemmed | Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title_short | Estimative of real number of infections by COVID-19 in Brazil and possible scenarios |
title_sort | estimative of real number of infections by covid-19 in brazil and possible scenarios |
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/PMC7513932/ https://www.ncbi.nlm.nih.gov/pubmed/32995682 http://dx.doi.org/10.1016/j.idm.2020.09.004 |
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