Modeling, dynamics and optimal control of Ebola virus spread

TL;DR

This paper develops a mathematical SIR model incorporating demographic effects and optimal control strategies to analyze and predict Ebola virus spread, validated with real-world data from Guinea in 2015.

Contribution

It introduces an enhanced SIR model with vital dynamics and optimal control for Ebola, validated with actual outbreak data and providing insights into effective intervention strategies.

Findings

Model accurately predicts Ebola transmission dynamics.

Optimal control reduces infection numbers effectively.

Model parameters align with WHO data.

Abstract

We present a mathematical analysis of the early detection of Ebola virus. The propagation of the virus is analysed by using a Susceptible, Infected, Recovered (SIR) model. In order to provide useful predictions about the potential transmission of the virus, we analyse and simulate the SIR model with vital dynamics, by adding demographic effects and an induced death rate. Then, we compute the equilibria of the model. The numerical simulations confirm the theoretical analysis. Our study describes the 2015 detection of Ebola virus in Guinea, the parameters of the model being identified from the World Health Organization data. Finally, we consider an optimal control problem of the propagation of the Ebola virus, minimizing the number of infected individuals while taking into account the cost of vaccination.