Bifurcation Thresholds and Optimal Control in Transmission Dynamics of Arboviral Diseases

TL;DR

This paper develops a mathematical model for arboviral disease transmission, analyzing bifurcation thresholds and optimal control strategies, including vaccination and vector control, to inform effective disease eradication policies.

Contribution

It introduces a comprehensive model incorporating imperfect vaccination and multiple control measures, analyzing bifurcation phenomena and deriving optimal control strategies for disease elimination.

Findings

Existence of disease-free and endemic equilibria.

Identification of bifurcation thresholds including backward bifurcation.

Optimal control strategies combining vaccination and vector control are effective.

Abstract

In this paper, we derive and analyse a model for the control of arboviral diseases which takes into account an imperfect vaccine combined with some other mechanisms of control already studied in the literature. We begin by analyse the basic model without controls. We prove the existence of two disease-free equilibrium points and the possible existence of up to two endemic equilibrium points (where the disease persists in the population). We show the existence of a transcritical bifurcation and a possible saddle-node bifurcation and explicitly derive threshold conditions for both, including defining the basic reproduction number, R 0 , which determines whether the disease can persist in the population or not. The epidemiological consequence of saddle-node bifurcation (backward bifurcation) is that the classical requirement of having the reproduction number less than unity, while necessary, is no longer sufficient for disease elimination from the population. It is further shown that in the absence of disease--induced death, the model does not exhibit this phenomenon. We perform the sensitivity analysis to determine the model robustness to parameter values. That is to help us to know the parameters that are most influential in determining disease dynamics. The model is extended by reformulating the model as an optimal control problem, with the use of five time dependent controls, to assess the impact of vaccination combined with treatment, individual protection and vector control strategies (killing adult vectors, reduction of eggs and larvae). By using optimal control theory, we establish optimal conditions under which the disease can be eradicated and we examine the impact of a possible combined control tools on the disease transmission. The Pontryagin's maximum principle is used to characterize the optimal control. Numerical simulations, efficiency analysis and cost effectiveness analysis show that, vaccination combined with other control mechanisms, would reduce the spread of the disease appreciably, and this at low cost.