A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
Abstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-95815-9 |
| _version_ | 1818422463263932416 |
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| author | Yuanji Tang Tamires D. A. Serdan Amanda L. Alecrim Diego R. Souza Bruno R. M. Nacano Flaviano L. R. Silva Eliane B. Silva Sarah O. Poma Matheus Gennari-Felipe Patrícia N. Iser-Bem Laureane N. Masi Sherry Tang Adriana C. Levada-Pires Elaine Hatanaka Maria F. Cury-Boaventura Fernanda T. Borges Tania C. Pithon-Curi Marli C. Curpertino Jarlei Fiamoncini Carol Gois Leandro Renata Gorjao Rui Curi Sandro Massao Hirabara |
| author_facet | Yuanji Tang Tamires D. A. Serdan Amanda L. Alecrim Diego R. Souza Bruno R. M. Nacano Flaviano L. R. Silva Eliane B. Silva Sarah O. Poma Matheus Gennari-Felipe Patrícia N. Iser-Bem Laureane N. Masi Sherry Tang Adriana C. Levada-Pires Elaine Hatanaka Maria F. Cury-Boaventura Fernanda T. Borges Tania C. Pithon-Curi Marli C. Curpertino Jarlei Fiamoncini Carol Gois Leandro Renata Gorjao Rui Curi Sandro Massao Hirabara |
| author_sort | Yuanji Tang |
| collection | DOAJ |
| description | Abstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic. |
| first_indexed | 2024-12-14T13:26:39Z |
| format | Article |
| id | doaj.art-6489676b149943b9be31d453fad56b73 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-14T13:26:39Z |
| publishDate | 2021-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-6489676b149943b9be31d453fad56b732022-12-21T22:59:49ZengNature PortfolioScientific Reports2045-23222021-08-0111111110.1038/s41598-021-95815-9A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in BrazilYuanji Tang0Tamires D. A. Serdan1Amanda L. Alecrim2Diego R. Souza3Bruno R. M. Nacano4Flaviano L. R. Silva5Eliane B. Silva6Sarah O. Poma7Matheus Gennari-Felipe8Patrícia N. Iser-Bem9Laureane N. Masi10Sherry Tang11Adriana C. Levada-Pires12Elaine Hatanaka13Maria F. Cury-Boaventura14Fernanda T. Borges15Tania C. Pithon-Curi16Marli C. Curpertino17Jarlei Fiamoncini18Carol Gois Leandro19Renata Gorjao20Rui Curi21Sandro Massao Hirabara22Applied NanoFemto Technologies, LLCInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityKaiser Southern California Permanente Medical GroupInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityMedical School, Faculdade Dinâmica do Vale do PirangaSchool of Pharmaceutical Sciences, University of Sao PauloFederal University of PernambucoInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityInterdisciplinary Program of Health Sciences, Cruzeiro do Sul UniversityAbstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.https://doi.org/10.1038/s41598-021-95815-9 |
| spellingShingle | Yuanji Tang Tamires D. A. Serdan Amanda L. Alecrim Diego R. Souza Bruno R. M. Nacano Flaviano L. R. Silva Eliane B. Silva Sarah O. Poma Matheus Gennari-Felipe Patrícia N. Iser-Bem Laureane N. Masi Sherry Tang Adriana C. Levada-Pires Elaine Hatanaka Maria F. Cury-Boaventura Fernanda T. Borges Tania C. Pithon-Curi Marli C. Curpertino Jarlei Fiamoncini Carol Gois Leandro Renata Gorjao Rui Curi Sandro Massao Hirabara A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil Scientific Reports |
| title | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil |
| title_full | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil |
| title_fullStr | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil |
| title_full_unstemmed | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil |
| title_short | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil |
| title_sort | simple mathematical model for the evaluation of the long first wave of the covid 19 pandemic in brazil |
| url | https://doi.org/10.1038/s41598-021-95815-9 |
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