Passivity-Based Inverse Optimal Impulsive Control for Influenza Treatment in the Host

Abstract

Influenza A virus infections are causes of severe illness resulting in high levels of mortality. Neuraminidase inhibitors such as zanamivir and oseltamivir are used to treat influenza; however, treatment recommendations remain debatable. In this paper, a discrete-time inverse optimal impulsive control scheme based on passivation is proposed to address the antiviral treatment scheduling problem. We adapt results regarding stability, passivity, and optimality for the impulsive action. The study is founded on mathematical models whose parameters are adjusted to data from clinical trials where participants were experimentally infected with influenza H1N1 and treated with either zanamivir or oseltamivir. Simulation results show that control-based techniques can reduce the amount of medication while simultaneously reach the efficacy levels of the treatment schedules by the Food and Drug Administration. Monte Carlo simulations disclose the robustness of the proposed control-based techniques.