SEIR Mathematical Model of COVID-19 Epidemic Transmission in France
Year: 2025
Type: article
Abstract: The COVID-19 pandemic, first identified in Wuhan, China, in December 2019, rapidly spread across the globe, necessitating mathematical models to understand its transmission dynamics. This study presents a susceptible-exposed-infected-removed (SEIR) model to analyze the spread of COVID-19 in France. The model incorporates key epidemiological parameters, including the transmission rate (α) and social interaction factor (κ), which influence disease spread. To solve the system of differential equations, we employ the fourth-order Runge-Kutta (RK4) method. A parametric study is conducted to validate the model, and the basic reproduction number (R0) is derived to assess disease stability. The results align with real-world data, confirming the model’s effectiveness in describing the outbreak. Our findings highlight the critical role of social distancing, recovery rates, and transmission reduction measures in mitigating the spread of COVID-19.
Source: SciNexuses.
Author: Midra Tahir
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4408212500