Control of COVID-19 dynamics through a fractional-order model

TL;DR

This paper presents a fractional-order mathematical model to analyze COVID-19 transmission dynamics and evaluates control strategies like social distancing, mask use, and quarantine through optimal control theory.

Contribution

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

Findings

Optimal control strategies reduce infection numbers.

Numerical solutions demonstrate effectiveness of social distancing and quarantine.

Fractional calculus provides a more accurate modeling of disease dynamics.

Abstract

We investigate, through a fractional mathematical model, the effects of physical distance on the SARS-CoV-2 virus transmission. Two controls are considered in our model for eradication of the spread of COVID-19: media education, through campaigns explaining the importance of social distancing, use of face masks, etc., towards all population, while the second one is quarantine social isolation of the exposed individuals. A general fractional order optimal control problem, and associated optimality conditions of Pontryagin type, are discussed, with the goal to minimize the number of susceptible and infected while maximizing the number of recovered. The extremals are then numerically obtained.