Complex Systems applied to epidemiological models

Authors

  • João Paulo de Oliveira Lima Universidade de Brasília

Keywords:

Complex Systems. Epidemiological Models. Dynamic Systems.

Abstract

This work aims to discuss complex systems based on the epidemiological models SIR, SIRS, SEIR e SEIRS. It is expected that the importance of studying complex systems will be demonstrated since it also teaches us to recognize the limitations of models and even predictions via differential equations. This study area could be treated with other approaches, considering that it is a multidisciplinary area, but due to this historical moment of the COVID-19 pandemic, understanding how epidemiological models work is of paramount importance.

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References

Bill & Melinda Gates Foundation. SIR and SIRS models. Institute for Disease Modeling (IDM), 2021. Disponível em: <https://docs.idmod.org/projects/emod-hiv/en/latest/model-sir. html>. Acesso em: 05 jan. 2021. 61, 64, 66, 68, 69

LINGE SVEIN; PETTER LANGTANGEN, H. Programming for computations-MATLAB/Octave. [S.l.]: Springer Nature, 2016. 71

MELOTTI, G. Aplicaçao de autômatos celulares em sistemas complexos: Um estudo de caso em espalhamento de epidemias. [S.l.: s.n.], 2009. 60

MITCHELL, M. Complexity: A guided tour. [S.l.]: Oxford University Press, 2009. 60

Published

2021-04-20

How to Cite

de Oliveira Lima, J. P. (2021). Complex Systems applied to epidemiological models. Physicae Organum, 7(1), 59–71. Retrieved from https://periodicos.unb.br/index.php/physicae/article/view/36012