In this paper, an estimation of model parameters is performed by using the Alternative Regression (AR) approach on an experimental data set of Herpes Simplex Virus type-1 (HSV-1) infection with innate immune response. Throughout the specified course of time, the measurements of monocytes, neutrophils, and viral load were obtained from the corneas of infected mice. C57BL/6 (B6) mice were used at Oakland University, Department of Biological Sciences, and the outcome measurements were divided into training and testing data sets. The HSV-1 nonlinear dynamic model is proposed based on the observed data patterns and biological system information. The simulation results of the proposed model showed that they consistently fit the experimental data set. In addition, the sensitivity test and model validation diagnostics are considered to determine the most significant key parameters that affect the dynamics of the HSV-1 system.
Keywords: Alternative regression method; Biochemical system theory; HSV-1 experimental data set; HSV-1 parameter estimation; Nonlinear HSV-1 model; Smoothing algorithm.