Beyond the Best Fit: Fitting SIR-style Models to Data While Prioritizing Biological Meaning

Authors

• Meredith L. Greer, Bates CollegeFollow

Publication Date

6-12-2026

Keywords

SIR model, compartmental model, model fitting, active learning, mathematical epidemiology

Disciplines

Biology | Mathematics | Physical Sciences and Mathematics | Science and Mathematics Education

Abstract

Many students find comfort in mathematics because math classes have been a place where they can find the “right answer” to exercises. Modeling courses typically emphasize more nuance, teaching students to try modeling approaches, compare back with real-world mechanisms and data, and then refine their models, in an ongoing cycle. One topic, however, can cause students to quickly revert into “right answer” mode: fitting a model to data. Phrases such as best fit and minimize the distance suggest there is one optimal solution that can be determined by an algorithm, and these algorithms typically have no relationship to the biology underlying the model we have created.

This article presents modeling activities meant to counteract the “right answer” mindset by emphasizing the biology in SIR-style models, encouraging careful justification for each modeling decision, and demonstrating reasons to consider ranges of parameter values, rather than a single “best” answer. Students work with algorithms, yet also experiment widely by hand and debate what their goals should be. They contemplate the fact that there may be infinitely many choices for each parameter in a model, with 𝑛 parameter values creating an 𝑛-dimensional set of options. Putting it all together, students grapple with the sophisticated mathematical aspects of fitting models with data, while building their understanding of the need to bring human decisionmaking and priority-setting to model analysis.

Recommended Citation

Greer, Meredith L. (2026) "Beyond the Best Fit: Fitting SIR-style Models to Data While Prioritizing Biological Meaning," CODEE Journal: Vol. 20: Iss. 2, Article 4.
Available at: https://scholarship.claremont.edu/codee/vol20/iss2/4

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