Fuzzy fractional epidemiological model for Middle East respiratory syndrome coronavirus on complex heterogeneous network using Caputo derivative

Abstract

This study presents a new fuzzy fractional epidemiological model to investigate the Middle East respiratory syndrome coronavirus on a complex heterogeneous network using fuzzy Caputo gH-differentiability. The model configuration follows a susceptible-infectious-susceptible (SIS) structure for human and camel populations. The equations for the camel population are developed due to its significant role as an animal source for spreading the virus, together with the direct interaction between human and animal populations. Some characteristic properties and results are extracted using fuzzy Caputo derivative. Theoretical findings regarding the existence and uniqueness of mild solutions to fuzzy initial value problems are presented using the general contraction principle. The virus outbreak behavior is discussed using two approaches: an analytical approach using fuzzy Laplace transform and a proposed numerical scheme using integral equations. To enhance the novelty of the work, the proposed numerical scheme is used to solve the fuzzy fractional epidemiological model and provides graphical representations to illustrate the uncertain behavior of the fractional epidemiological model. These numerical experiments show that the magnitude of the disease effect depends on the fractional order and the value of degree in the network. The results of this study suggest that we can overcome the impact of spreading the disease by adhering to infection prevention measures when dealing with animal populations.