Estimation of COVID-19 cases in Brazil: mathematical modeling study

L. Y. Sheng; A. L. Sartori

doi:10.36560/14220211206

Estimation of COVID-19 cases in Brazil: mathematical modeling study

Authors

L. Y. Sheng Universidade Federal de Mato Grosso http://orcid.org/0000-0001-5913-2639
A. L. Sartori Universidade Federal de Mato Grosso http://orcid.org/0000-0003-3832-031X

DOI:

https://doi.org/10.36560/14220211206

Keywords:

epidemiological monitoring, COVID-19, estimation, mathematical modeling

Abstract

The objective was to describe a mathematical model to estimate cases by COVID-19 in Brazil in the short term and to identify the existence of forces to inhibit the spread of SARS-CoV2. Cases confirmed by COVID-19 in Brazil from March 16 to May 31, 2020 were used to develop a mathematical equation for estimating COVID-19 cases for up to 13 future days. Correction factors were calculated to identify whether there was an inhibition of the spread of infection in the country. The relative error and Pearson's correlation were analyzed to determine the model's performance. Six models were developed (gross, S1, S2, S3, S4 and corrected). The corrected model showed good adherence to the number of estimated and observed cases. Eight correction factors were calculated, which increased during the study period. The increase in correction factors expressed the loss of the inhibition force of interventions implemented in the country for the prevention and control of infection. The proposed mathematical model proved to be viable and feasible for implementation in epidemiological surveillance services.

References

BRASIL. Painel CoronavÃrus. [citado 15 jun 20120]. DisponÃvel em: https://covid.saude.gov.br/

Brasil. Lei nÂº 13.979, de 6 de fevereiro de 2020. DispÃµe sobre as medidas para enfrentamento da emergÃªncia de saÃºde pÃºblica de importÃ¢ncia internacional decorrente do coronavÃrus responsÃ¡vel pelo surto de 2019. [citado 15 jun 20120] DisponÃvel em: http://www.in.gov.br/web/dou/-/lei-n-13.979-de-6-de-fevereiro-de-2020-242078735

Ivorra B, FerrÃ¡ndez MR, Vela-PÃ©rez M, Ramos AM. Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China. Commun Nonlinear Sci Numer Simul. 2020;88:105303. https://doi.org/10.1016/j.cnsns.2020.105303

Predictive Mathematical Models of the COVID-19 Pandemic Underlying Principles and Value of Projections. JAMA. 2020;323:1893-4. https://doi.org/10.1001/jama.2020.6585

World Health Organization (WHO). Rolling updates on coronavirus disease (COVID-19) Updated 4 May 2020. [citado 15 jun 20120]. DisponÃvel em: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen

Downloads

PDF (Português (Brasil))

Published

2021-01-26

How to Cite

Sheng, L. Y., & Sartori, A. L. (2021). Estimation of COVID-19 cases in Brazil: mathematical modeling study. Scientific Electronic Archives, 14(2), 70–73. https://doi.org/10.36560/14220211206

Download Citation

Issue

Vol. 14 No. 2 (2021): Scientific Electronic Archives

Section

Mathematical Sciences / Engineering

License

The journal reserves the right to make changes to the original rules, spelling and grammatical order, in order to keep the language of worship default, respecting, however, the style of the authors. The finals will be sent to authors. Articles published are the property of Scientific Electronic Archives magazine, becoming its total or partial reprint, subject to the express authorization of the direction of the journal. The original source of publication should be retained. The originals will not be returned to the authors. Opinions expressed by authors of articles are solely your responsibility.

This journal uses the License Creative Commons Atribuição 4.0 Internacional.