A numerical algorithm of parameter estimation for dynamic model for HIV infection of CD4+ t cells

Abstract

The problem of approximation the values of 6 coefficients of a HIV infection basic model by knowing how viremia and target cells blood concentrations change as time goes on is considered. Above inverse problem for HIV dynamic model is reduced to the problem of minimization a least squares misfit function. A 6-dimensional Nelder-Mead algorithm is implemented to approximate this minimum. For a narrow interval to mean values of unknown coefficients (about 33% of the total bandwidth between experimental extreme coefficients values), proposed algorithm demonstrates a good convergence, with a probability of 17% for the Nelder-Mead algorithm. Results of numerical experiment are demonstrated and discussed.