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Relevant mathematical modelling efforts for understanding COVID-19 dynamics: an educational challenge
1Department of Applied Mathematics, IMECC-UNICAMP, Campinas, SP Brazil.
ZDM : the International Journal on Mathematics Education
|December 7, 2022
Summary
Mathematical modeling, using difference and differential equations, helps understand epidemic behaviors like COVID-19. This approach aids in evaluating public health policies and disease dynamics under various scenarios.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- COVID-19 pandemic highlighted the need for understanding epidemic dynamics.
- Effective public health policies require robust analytical tools.
Purpose of the Study:
- To emphasize the importance of mathematical modeling in understanding epidemic behaviors.
- To suggest modeling techniques for evaluating public health decisions.
- To motivate learners to study and adapt SIR-type models for infectious diseases.
Main Methods:
- Utilizing nonlinear systems of difference equations (accessible with spreadsheets).
- Employing nonlinear systems of ordinary differential equations (suitable for undergraduate study).
- Modifying existing SIR-type models to simulate realistic scenarios.
Main Results:
- Demonstrated the application of mathematical models to understand COVID-19 dynamics.
- Explored various modeling choices reflecting real-life situations like social distancing and vaccination.
- Analyzed model behaviors under different scenarios, including vaccine hesitancy.
Conclusions:
- Mathematical modeling is crucial for understanding and predicting epidemic trajectories.
- The study provides a framework for using mathematical tools in educational settings.
- Encourages further research and application of these modeling techniques in public health and education.
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