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

Authors: Maryam Al-Yahyai (Department of Mathematics, College of Science, Sultan Qaboos University, Muscat, Oman), Fatma Al-Musalhi (Department of Mathematics, College of Science, Sultan Qaboos University, Muscat, Oman), Nasser Al-Salti (Department of Applied Mathematics and Science, National University of Science and Technology, Muscat, Oman), Ibrahim Elmojtaba (Department of Mathematics, College of Science, Sultan Qaboos University, Muscat, Oman)

arXiv: 2305.02223v1 - DOI (q-bio.PE)
34 pages

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.

Submitted to arXiv on 03 May. 2023

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.