Inverse problem for coefficient identification in SIR epidemic models

This work deals with the development of a numerical method for solving an inverse problem for identifying coefficients from over-posed data in an SIR mathematical model of infectious diseases spread through a population. The parameters are identified using a generalized Least Squares Method which is similar to the technique called Method of Variational Imbedding, where the original inverse problem is replaced by a minimization problem. A difference scheme and a numerical algorithm for solving the parameter identification problem are developed. The correctness of the embedded problem is discussed. Numerical results of the parameters, representing the solution to the inverse problem, are presented.