TITLE:
Delayed Dynamics of SIR Model for COVID-19
AUTHORS:
Hameed K. Ebraheem, Nizar Alkhateeb, Hussein Badran, Ebraheem Sultan
KEYWORDS:
COVID-19, SIR, Compartmental Model, Forecasting
JOURNAL NAME:
Open Journal of Modelling and Simulation,
Vol.9 No.2,
April
29,
2021
ABSTRACT: This paper presents a
new modified SIR model which incorporates appropriate delay parameters leading
to a more precise prediction of COVID-19 real time data. The efficacy of the
newly developed SIR model is proven by comparing its predictions to real data
obtained from four counties namely Germany, Italy, Kuwait, and Oman. Two
included delay periods for incubation and recovery within the SIR model produce
a sensible and more accurate representation of the real time data. In the
absence of the two-delay period () the dynamical behavior of the
model will not correspond to today’s picture and lag the detection of the
epidemic peak. The reproductive number R0 is defined for the
model for values of recovery time delay of the infective case. The effect of recovery time may produce second wave, and/or an oscillation which could destabilize the
behavior of the system and a periodic oscillation can arise due to Hopf
bifurcation phenomenon.