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Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge

The purpose of the work described in this paper is to emphasize the importance of using mathematical models and mathematical modelling in order to be able to understand and to learn possible behaviours in epidemic situations such as that of the COVID-19 pandemic, besides suggesting modelling techniq...

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Autores principales: Meyer, J. F. C. A., Lima, M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716171/
https://www.ncbi.nlm.nih.gov/pubmed/36475296
http://dx.doi.org/10.1007/s11858-022-01447-2
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author Meyer, J. F. C. A.
Lima, M.
author_facet Meyer, J. F. C. A.
Lima, M.
author_sort Meyer, J. F. C. A.
collection PubMed
description The purpose of the work described in this paper is to emphasize the importance of using mathematical models and mathematical modelling in order to be able to understand and to learn possible behaviours in epidemic situations such as that of the COVID-19 pandemic, besides suggesting modelling techniques with which to evaluate certain sanitary decisions and policies which do, in fact, affect society as a whole. The mathematical tools that are used derive from nonlinear systems of difference equations (possibly viable at a high school level, using spreadsheets or adequate software) as well as nonlinear systems of ordinary differential equations (therefore using mathematical tools and software well within the reach of undergraduate students of many courses). This purpose is accomplished by motivating students and learners to study existing SIR-type models and modifying them in order to have a fully understandable translation of dynamics for infectious diseases such as COVID-19 in several different realistic scenarios, that is to say, situations that consider social distancing policies, widespread vaccination programmes, as well as possible and even probable results when in the presence of negationist postures and attitudes. Several modelling choices referring to real-life situations are shown and explored. These models are analysed and discussed, implicitly proposing similar attitudes and evaluations in learning environments. Conclusions are drawn, stimulating further work using the described mathematical tools and resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11858-022-01447-2.
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spelling pubmed-97161712022-12-02 Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge Meyer, J. F. C. A. Lima, M. ZDM Original Paper The purpose of the work described in this paper is to emphasize the importance of using mathematical models and mathematical modelling in order to be able to understand and to learn possible behaviours in epidemic situations such as that of the COVID-19 pandemic, besides suggesting modelling techniques with which to evaluate certain sanitary decisions and policies which do, in fact, affect society as a whole. The mathematical tools that are used derive from nonlinear systems of difference equations (possibly viable at a high school level, using spreadsheets or adequate software) as well as nonlinear systems of ordinary differential equations (therefore using mathematical tools and software well within the reach of undergraduate students of many courses). This purpose is accomplished by motivating students and learners to study existing SIR-type models and modifying them in order to have a fully understandable translation of dynamics for infectious diseases such as COVID-19 in several different realistic scenarios, that is to say, situations that consider social distancing policies, widespread vaccination programmes, as well as possible and even probable results when in the presence of negationist postures and attitudes. Several modelling choices referring to real-life situations are shown and explored. These models are analysed and discussed, implicitly proposing similar attitudes and evaluations in learning environments. Conclusions are drawn, stimulating further work using the described mathematical tools and resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11858-022-01447-2. Springer Berlin Heidelberg 2022-12-02 2023 /pmc/articles/PMC9716171/ /pubmed/36475296 http://dx.doi.org/10.1007/s11858-022-01447-2 Text en © FIZ Karlsruhe 2022, corrected publication 2022Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Meyer, J. F. C. A.
Lima, M.
Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title_full Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title_fullStr Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title_full_unstemmed Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title_short Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
title_sort relevant mathematical modelling efforts for understanding covid-19 dynamics: an educational challenge
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716171/
https://www.ncbi.nlm.nih.gov/pubmed/36475296
http://dx.doi.org/10.1007/s11858-022-01447-2
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