Forecasting of COVID-19 in Egypt and Oman using Modified SEIR and Logistic Growth Models

Abstract

Understanding the transm ission dynam ics o f the novel coronavirus is the concern th at attracted m any researchers nowadays. In th is paper, two m athem atical m odels, m odified SEIR and logistic grow th, w ere im plem ented in M atlab to pred ict the transm ission o f COVID-19 in Egypt and Om an. To estim ate the m odels' param eters, the reported data w ere used to fit the m odels using Nelder-M ead, Levenberg-M arquardt, and Trust-R egion-R eflective optim ization algorithm s. Then, a sensitivity analysis w as m ade to understand the effect o f d ifferent param eters on the m odels' prediction. The application o f the two m odels on the reported data w as com pared despite their different nature. It was shown and verified that the tw o m odels are highly dependent on the param eters' values, referring to the im portance o f determ ining their estim ates u sing an optim ization algorithm . It was found ou t th at the m ost dom inant param eter is the one denoting the rate by w hich su sceptib le people are protected, w hich em phasizes the effect o f social distancing and quarantine.