A Comparative Study for COVID-19 Forecasting Models


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Authors

  • Ali Sendur Alanya Alaaddin Keykubat University, 07490 Antalya, Türkiye
  • Zafer Cakir Alanya Alaaddin Keykubat University, 07490 Antalya, Türkiye

DOI:

https://doi.org/10.59287/icsis.600

Keywords:

Infectious Diseases, COVID-19, Epidemic Model, SI Model, SIS Model, SIR Model

Abstract

The COVID-19 was declared as an international health emergency concern by World Health Organization (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 and public 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 their performances by applying recent data of COVID-19 outbreak. We present numerical experiments to indicate which models can reproduce the epidemic dynamics qualitatively and quantitatively for forecasting.

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Published

2023-04-14

How to Cite

Sendur, A., & Cakir, Z. (2023). A Comparative Study for COVID-19 Forecasting Models. International Conference on Scientific and Innovative Studies, 1(1), 195–199. https://doi.org/10.59287/icsis.600