A Comparative Study for COVID-19 Forecasting Models

Abstract

The COVID-19 was declared as an international health emergency concern by World HealthOrganization (WHO) in 2020. It caused about 7 million deaths and has taken interest in various disciplines.On the other hand, modeling infectious diseases can provide critical planning to control the outbreak andpublic health research. In this work, we consider three classical epidemic models, namely, the SI(Susceptible, Infectious) model, SIS (Susceptible, Infectious, Susceptible) model and SIR (Susceptible,Infectious, Recovered) model to simulate the spread of COVID-19 in Türkiye. We compare theirperformances by applying recent data of COVID-19 outbreak. We present numerical experiments toindicate which models can reproduce the epidemic dynamics qualitatively and quantitatively forforecasting.