EPIDEMIC: a didactic tool for teaching mathematical epidemiology

Autores

  • Bruna Pavlack
  • Malú Grave
  • Eber Dantas
  • Julio Basilio
  • Leonardo de la Roca
  • João Pedro Norenberg
  • Michel Tosin
  • Lucas Chaves
  • Diego Matos
  • Marcos Issa
  • Roberto Luo
  • Amanda Cunha Guyt
  • Luthiana Soares
  • Rodrigo Burgos
  • Lisandro Lovisolo
  • Américo Cunha Jr

DOI:

https://doi.org/10.5540/03.2021.008.01.0402

Palavras-chave:

Epidemiology, Educational Code, Compartmental Models, Octave, Trend and Forecast Graphs

Resumo

Due to the COVID-19 pandemic, there was a growing interest in society in the area of epidemiology.  In this context, emerged the initiative COVID-19: Observatório Fluminense (COVID19RJ), which  is managed by a group of independent researchers affiliated with different Brazilian institutions.  COVID19RJ publishes trend and monitoring graphs of the COVID-19 pandemic in Brazil and some  countries around the world. Due to this demand, the need for an educational code for research in  epidemiology arose, with the objective of encouraging and allowing the entry of more researchers  in this area. So, EPIDEMIC was developed, this being a code that is organized in a didactic  way and divided into three modules: modeling, trends and forecasts. In the modeling module,  compartmental models are used to simulate population dynamics during an epidemic. In the trends  module, it is possible to monitor the behavior of epidemics in countries, states or municipalities.  And in the forecasts module, a statistical regressor is used to obtain predictions about the short-  term behavior of epidemic curves. EPIDEMIC provides a tutorial with explanations and examples  of use. The code was developed on the free software GNU Octave and is compatible with the  proprietary software MATLAB. EPIDEMIC presents itself as a good aid tool for the teaching and  learning process of epidemiology and, consequently, for the increase of researchers in the área.

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Biografia do Autor

Bruna Pavlack

Federal Institute of Mato Grosso do Sul, Três Lagoas, MS. State University of São Paulo, Ilha Solteira, SP

Malú Grave

Federal University of Rio de Janeiro, Rio de Janeiro, RJ

Eber Dantas

Federal University of Rio de Janeiro, Rio de Janeiro, RJ

Julio Basilio

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Leonardo de la Roca

Rio de Janeiro St ate University, Rio de Janeiro, RJ

João Pedro Norenberg

State University of São Paulo, Ilha Solteira, SP

Michel Tosin

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Lucas Chaves

Federal University of Uberlândia, Uberlândia, MG

Diego Matos

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Marcos Issa

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Roberto Luo

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Amanda Cunha Guyt

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Luthiana Soares

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Rodrigo Burgos

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Lisandro Lovisolo

Rio de Janeiro St ate University, Rio de Janeiro, RJ

Américo Cunha Jr

Rio de Janeiro St ate University, Rio de Janeiro, RJ

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Publicado

2021-12-20

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