A SIQRB delayed model for cholera and optimal control treatment

TL;DR

This paper introduces a delayed mathematical model for cholera that incorporates incubation time, analyzes its stability, and develops optimal quarantine strategies, demonstrating improved fit to real outbreak data from Haiti.

Contribution

It presents a novel delayed cholera model with stability analysis and optimal control strategies, enhancing outbreak prediction and management.

Findings

Delayed model better fits Haiti outbreak data

Optimal quarantine strategies reduce infection and bacterial levels

Stability analysis confirms model robustness

Abstract

We improve a recent mathematical model for cholera by adding a time delay that represents the time between the instant at which an individual becomes infected and the instant at which he begins to have symptoms of cholera disease. We prove that the delayed cholera model is biologically meaningful and analyze the local asymptotic stability of the equilibrium points for positive time delays. An optimal control problem is proposed and analyzed, where the goal is to obtain optimal treatment strategies, through quarantine, that minimize the number of infective individuals and the bacterial concentration, as well as treatment costs. Necessary optimality conditions are applied to the delayed optimal control problem, with a $L^1$ type cost functional. We show that the delayed cholera model fits better the cholera outbreak that occurred in the Department of Artibonite -- Haiti, from 1 November 2010 to 1 May 2011, than the non-delayed model. Considering the data of the cholera outbreak in Haiti, we solve numerically the delayed optimal control problem and propose solutions for the outbreak control and eradication.