FRACTIONAL SEIR MODEL SOLUTION TO STUDY THE DISSEMINATION OF MPOX IN THE DEMOCRATIC REPUBLIC OF THE CONGO

Authors

DOI:

https://doi.org/10.21575/25254782rmetg2025vol10n42457

Keywords:

Fractional Calculus, Numerical Methods, Caputo Derivative, SEIR Model, Mpox

Abstract

This document presents an analysis of the fractional SEIR (Susceptible, Exposed, Infectious, and Removed) epidemiological model, that is, a model based on non-integer (arbitrary) order Caputo derivatives, with the aim of studying the spread of mpox in the Democratic Republic of the Congo (DRC). Considering the importance of rapid and accurate response by public health authorities, fractional modeling offers significant advantages in describing the memory and heritability of infectious processes (Pooseh, 2011). We used real data from daily and cumulative cases to calibrate and validate the model. Numerical simulations performed with the fractional Adams-Bashforth-Moulton predictor-corrector method reveal a better fit compared to the integer-derivative SEIR model.

Author Biographies

  • Antonio Marcos de Oliveira dos Santos, Federal University of Rio Grande

    He holds a Bachelor's degree in Mathematics (UESPI) and a Master’s degree in Mathematical Modeling (UFPel). He is a Mathematics teacher in the municipal school system and a Ph.D. candidate in Computational Modeling at FURG. His work focuses on Applied Mathematics, particularly epidemiological modeling and infectious disease models.

  • Matheus Jatkoske Lazo, Federal University of Rio Grande

    He holds a B.Sc., M.Sc., and Ph.D. in Physics from the University of São Paulo (USP). An Associate Professor at FURG, he also serves on the Physics and Astronomy Advisory Committee of FAPERGS. His work focuses on Mathematical Physics, particularly Statistical Mechanics and Fractional Calculus, including integrable models, spin glass systems, variational principles, and Lagrangian formulations for nonconservative systems.

  • Daniela Buske, Federal University of Pelotas

    A Full Professor at the Federal University of Pelotas, she holds a Bachelor’s degree in Mathematics (UFSM), an M.Sc. and Ph.D. in Mechanical Engineering (UFRGS), and a postdoctoral fellowship in Nuclear Engineering (UFRGS), including a doctoral internship at ISAC/CNR in Bologna, Italy. A CNPq research productivity fellow, she is a faculty member of the Graduate Programs in Mathematical Modeling and Environmental Sciences at UFPel. Her research focuses on applied mathematics in atmospheric physics, pollutant dispersion, transport phenomena, climate change, extreme events, epidemiological modeling, and artificial intelligence.

References

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Published

2025-12-15

Issue

Section

Edição Especial do XII ERMAC RS