A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil

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 perfo...

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Bibliographic Details
Published in:	Scientific reports Vol. 11; no. 1; p. 16400
Main Authors:	Tang, Yuanji, Serdan, Tamires D. A., Alecrim, Amanda L., Souza, Diego R., Nacano, Bruno R. M., Silva, Flaviano L. R., Silva, Eliane B., Poma, Sarah O., Gennari-Felipe, Matheus, Iser-Bem, Patrícia N., Masi, Laureane N., Tang, Sherry, Levada-Pires, Adriana C., Hatanaka, Elaine, Cury-Boaventura, Maria F., Borges, Fernanda T., Pithon-Curi, Tania C., Curpertino, Marli C., Fiamoncini, Jarlei, Leandro, Carol Gois, Gorjao, Renata, Curi, Rui, Hirabara, Sandro Massao
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 12-08-2021 Nature Publishing Group Nature Portfolio
Subjects:	631/114/2397 692/699/255/2514 692/700/478/174 Coronaviruses COVID-19 Epidemics Growth rate Heterogeneity Humanities and Social Sciences Mathematical models multidisciplinary Pandemics Science Science (multidisciplinary) Brazil
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Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2045-2322 2045-2322
DOI:	10.1038/s41598-021-95815-9