Sensitivity analysis of an infectious disease model under fuzzy impreciseness

Abstract

A non-linear dynamic model describing the spread of any infectious disease, based on different categories of individuals: susceptible (S), exposed (E), infected (I), quarantined (Q), recovered (R), dead (D), and vaccinated (V) is presented. The aim of the analysis is to develop a sensitivity technique for fuzzy systems, leveraging the application of fuzzy set theory and its differential calculus. This designed method can significantly generate the sensitivity profile of each measured model output with respect to varying values of input parameters. Additionally, the collective influence of all parameters sensitivities on model is simulated in terms of system sensitivities. Numerical simulations by MATLAB, demonstrate the solution of the fuzzy model and its sensitivities concerning the impreciseness, thereby developing a more generalized and accurate disease model.