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A Tutorial on Structural Identifiability of Epidemic Models Using StructuralIdentifiability.j1
Yuganthi R Liyanage1, Omar Saucedo2, Necibe Tuncer1
1Department of Mathematics and Statistics, Florida Atlantic University, , Boca Raton, 33431, Florida, USA.
Arxiv
|April 27, 2026
Summary
Structural identifiability analysis is crucial for reliable epidemic modeling but is underused. This tutorial provides a reproducible framework and visual tools to integrate this analysis into workflows, improving parameter estimation and interdisciplinary communication.
Area of Science:
- Epidemiology
- Mathematical Biology
- Computational Science
Background:
- Structural identifiability is essential for accurate parameter estimation in epidemic models.
- Current application of structural identifiability analysis in infectious disease modeling is inconsistent and underutilized.
- Lack of standardized methods hinders reliable calibration and inference.
Purpose of the Study:
- To provide a user-oriented tutorial on systematically integrating global structural identifiability analysis into epidemic modeling.
- To present a reproducible framework using the Julia package StructuralIdentifiability.jl for ordinary differential equation models.
- To enhance interpretation and communication of identifiability results through visual strategies.
Main Methods:
- Demonstration of a workflow for global structural identifiability analysis.
- Application of the framework to various epidemic models (SEIR variants, vector-borne, hospitalization, mortality).
- Development of a visual communication strategy embedding results into compartmental diagrams.
Main Results:
- Identifiability is highly dependent on model structure, observed variables, and initial conditions.
- Identifiable parameter combinations can exist even when individual parameters are not globally identifiable.
- The framework ensures transparency, reproducibility, and facilitates comparative insights across different model classes.
Conclusions:
- This work offers practical guidance and a teaching resource for incorporating structural identifiability analysis into epidemic model development.
- The provided framework and visual tools aim to increase the consistent and effective use of identifiability analysis.
- Publicly available code and diagrams promote reproducibility and reuse in infectious disease modeling research.
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