# On the Modeling of COVID-19 Transmission Dynamics with Two Strains: Insight through Caputo Fractional Derivative

Fatmawati, Endang Yuliani, Cicik Alfiniyah, Maureen L. Juga, Chidozie W. Chukwu

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

## Abstract

The infection dynamics of COVID-19 is difficult to contain due to the mutation nature of the SARS-CoV-2 virus. This has been a public health concern globally with the impact of the pandemic on the world’s economy and mode of living. In the present work, we formulate and examine a fractional model of COVID-19 considering the two variants of concern on the disease transmission pathways, namely SARS-CoV-2 and D614G on our model formulation. The existence and uniqueness of our model solutions were analyzed using the fixed point theory. Mathematical analyses were presented, and the model’s basic reproduction numbers R01 and R02 were determined. The model has three equilibria: the disease-free equilibrium, that endemic for strain 1, and that endemic for strain 2. The locally asymptotic stability of the equilibria was established based on the R01 and R02 values. Caputo fractional operator was used to simulate the model to study the dynamics of the model solution. Results from numerical simulations envisaged that an increase in the transmission parameters of strain 1 leads to an increase in the number of infected individuals. On the other hand, an increase in the strain 2 transmission rate gives rise to more infection. Furthermore, it was established that there is an increased number of infections with a negative impact of strain 1 on strain 2 dynamics and vice versa.

Original language English 346 Fractal and Fractional 6 7 https://doi.org/10.3390/fractalfract6070346 Published - Jul 2022

## Keywords

• COVID-19
• fractional order
• infectious disease
• mathematical analysis
• two strain

## Fingerprint

Dive into the research topics of 'On the Modeling of COVID-19 Transmission Dynamics with Two Strains: Insight through Caputo Fractional Derivative'. Together they form a unique fingerprint.