Optimal models for estimating future infected cases of COVID-19 in Oman

Volume 9, Issue 2, Article 1 - 2020

Authors: Ahmed Al-Siyabi; Mehiddin Al-Baali; Anton Purnama

Copyright © 2020 . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

 Download PDF File

 Share on GOOGLE+  Share on Twitter  Share on LinkedIn Open XML File

Abstract

The recent coronavirus disease 2019 (COVID-19) outbreak is of high importance in research topics due to its fast spreading and high rate of infections across the world. In this paper, we test certain optimal models of forecasting daily new cases of COVID-19 in Oman. It is based on solving a certain nonlinear least-squares optimization problem that determines some unknown parameters in fitting some mathematical models. We also consider extension to these models to predict the future number of infection cases in Oman. The modification technique introduces a simple ratio rate of changes in the daily infected cases. This average ratio is computed by employing the rule of Al-Baali [Numerical experience with a class of self-scaling quasi-Newton algorithms, JOTA, 96 (1998), pp. 533–553], in a sense to be defined, for measuring the infection changes.

How To Cite This Article

A. Al-Siyabi, M. Al-Baali and A. Purnama, Optimal models for estimating future infected cases of COVID-19 in Oman, General Letters in Mathematics, 9(2) (2020), 53-66. https://doi.org/10.31559/glm2020.9.2.1