Estimación Bayesiana de los parámetros de la eficacia del Interferón en una infección viral In Vitro.

Abstract

In virology, mathematical models based on differential equations have been used to describe the dynamics of viral infections either with or without antiviral therapy and, based on this, are used as a tool to monitor replication inhibition viral and leading to cure of the infection or to keep the viral load below a threshold. In this work, Bayesian statistics are used to estimate the parameters of cell dynamics, viral dynamics, the efficacy of interferón (IFN), the basic reproductive number and other important parameters in viral infection models, from cell culture data. infected with Human Immunodeficiency Virus type 1 (HIV-1). Bayesian estimates of cell growth models and viral dynamics with or without interferon are presented, and the selection of the best model is made for each data set. The results obtained indicate that the inhibiting effects of interferon on viral replication and the production of new infections have the same efficacy. In addition, that interferon treatment significantly reduces the basic reproductive number and therefore the spread of the infection.