The Role of Quarantine and Isolation in Controlling COVID-19 Hospitalization in Oman

TL;DR

This study develops a mathematical model to evaluate how quarantine and isolation strategies impact COVID-19 hospitalizations in Oman, using data from 2020 to inform policy decisions during the pre-vaccine period.

Contribution

The paper introduces a comprehensive COVID-19 model incorporating quarantine and isolation, calibrated with Oman data, and analyzes their effects on hospitalization rates.

Findings

Quarantine and isolation significantly reduce hospitalization cases.

The model identifies key parameters influencing disease spread.

Sensitivity analysis highlights critical factors for controlling COVID-19.

Abstract

In this paper, we build a mathematical model for the dynamics of COVID-19 to assess the impact of placing healthy individuals in quarantine and isolating infected ones on the number of hospitalization and intensive care unit cases. The proposed model is fully analyzed in order to prove the positivity of solutions, to study the local and global stability of the disease-free equilibria and to drive the basic and control reproduction numbers of the model. Oman COVID-19 data is used to calibrate the model and estimate the parameters. In particular, the published data for the year 2020 is used, when two waves of the disease hit the country. Moreover, this period of time is chosen when no vaccine had been introduced, but only the non-pharmaceutical intervention (NPI) strategies were the only effective methods to control the spread and, consequently, control the hospitalization cases to avoid pressuring the health system. Based on the estimated parameters, the reproduction number and contribution of different transmission routes are approximated numerically. Sensitivity analysis is performed to identify the significant parameters in spreading the disease. Numerical simulation is carried out to demonstrate the effects of quarantine and isolation on the number of hospitalized cases.