Computational models to study the infectious disease COVID-19: a review
by Amit Sharma; Gaurang Sharma; Fateh Singh
International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO), Vol. 13, No. 4, 2023

Abstract: The current COVID-19 pandemic that is still waging in the world is a threat to humanity, and the cure for it is a big challenge for researchers, scientists, and the bio-medical community. However, the vaccine is available nowadays, but the infection is still increasing globally. In this paper, the different types of existing mathematical models related to the COVID-19 outbreak, namely, SI, SIS, SEIS, SIR, SIRS, SEIR, AI, logistic growth model, Poisson model and the expanded models are discussed. The basic reproduction number is one of the most important parameters for predicting the future of COVID-19, and existing models use it to forecast coronavirus disease around the globe. The motive of present study is to elaborate the key factors related to control of pandemic and to introduce the different type of existing mathematical models and applications to the readers under one platform. The initial description of the existing mathematical models gives us better insight of the disease and based on existing literature, future prediction of the spread of COVID-19 can be done more accurately and efficiently.

Online publication date: Thu, 12-Oct-2023

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