Comparative analysis of practical identifiability methods for an SEIR model-Reference-Cited by-同舟云学术

Comparative analysis of practical identifiability methods for an SEIR model

Published:2024 Issue:9 Volume:9 Page:24722-24761
ISSN:2473-6988
Container-title:AIMS Mathematics
language:
Short-container-title:MATH

Author:

Saucedo Omar¹,Laubmeier Amanda²,Tang Tingting³,Levy Benjamin⁴,Asik Lale⁵,Pollington Tim⁶,Feldman Olivia Prosper⁷

Affiliation:

1. Department of Mathematics, Virginia Tech, Blacksburg, VA 24061, USA

2. Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409, USA

3. Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA

4. Division of Mathematics, Analytics, Science, and Technology, Babson College, Wellesley, MA 02481, USA

5. Department of Mathematics and Statistics, University of the Incarnate Word, San Antonio TX 78209, USA

6. Big Data Institute, University of Oxford, OX1 2JD, Oxford, UK

7. Department of Mathematics, University of Tennessee, Knoxville, TN 37996, USA

Abstract

<p>Identifiability of a mathematical model plays a crucial role in the parameterization of the model. In this study, we established the structural identifiability of a susceptible-exposed-infected-recovered (SEIR) model given different combinations of input data and investigated practical identifiability with respect to different observable data, data frequency, and noise distributions. The practical identifiability was explored by both Monte Carlo simulations and a correlation matrix approach. Our results showed that practical identifiability benefits from higher data frequency and data from the peak of an outbreak. The incidence data gave the best practical identifiability results compared to prevalence and cumulative data. In addition, we compared and distinguished the practical identifiability by Monte Carlo simulations and a correlation matrix approach, providing insights into when to use which method for other applications.</p>

Publisher

American Institute of Mathematical Sciences (AIMS)

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