Study of COVID-19 anti-pandemic strategies by using optimal control

TL;DR

This paper develops a new COVID-19 epidemiological model incorporating confirmed and unreported cases, and uses optimal control theory to identify strategies that minimize infections and deaths.

Contribution

It introduces a novel epidemiological model and applies optimal control to evaluate intervention strategies for COVID-19.

Findings

Optimal control strategies reduce infection and death rates.

Distancing, case finding, and case holding are effective controls.

Model stability analyzed without intervention measures.

Abstract

In this study, we present a new epidemiological model, with contamination from confirmed and unreported. We also compute equilibria and study their stability without intervention strategies. Optimal control theory has proven to be a successful tool in understanding ways to curtail the spread of infectious diseases by devising the optimal disease intervention strategies. We investigate the impact of distancing, case finding, and case holding controls while at the same time, we minimize the number of infected and dead individuals. The method consists of minimizing the cost functional related to infectious, death, and controls through some strategies to reduce the spread of the COVID19 epidemic.