Susceptibility Inference and Response on Transmission Dynamics of Ebola Virus in Fuzzy Environment

This article uses fuzzy parameters to develop a susceptibility inference and response (SIR) model for the Ebola virus. The construction of the SIR model involves considering several aspects, including immunization, therapy, compliance with medical protocols, and Ebola virus load. The parameters representing the infection, mortality, and recovery rates caused by the Ebola virus are expressed as fuzzy numbers. These parameters are then employed as fuzzy parameters in the model. The study of the model uses the generation matrix approach to get the fundamental reproduction number and assess the stability of the equilibrium point inside the model. The findings from the simulation indicate that the variation in the Ebola virus load is associated with disparities in the transmission patterns of the Ebola virus. Also, we compare the impact of the variables of vaccination and following the medical guidelines in reducing the spread of the Ebola virus. Using Matlab software, the numerical simulation for this model is carried out, and the analysis of Ebola virus transmission is investigated in the fuzzy environment.