Switching Logistic Maps to Design Cycling Approaches Against Antimicrobial Resistance
Abstract
Antimicrobial resistance is a major threat to global health, in particular, new SARS-CoV-2 variants during the COVID-19 pandemic. Scheduling cycling therapies by targeting phenotypic states associated with specific mutations can help us to eradicate pathogenic variants. In this paper, we introduce a logistic switching model to abstract mutation networks of collateral resistance. We found conditions for which the unstable zero-equilibrium of the logistic maps can be stabilized through a switching signal. That is, persistent populations can be eradicated through tailored switching regimes. Starting from an optimal-control formulation, the switching policies show their potential in the stabilization of the zeroequilibrium for dynamics governed by logistic maps. Simulation results show the applicability of Parrondo's Paradox to design cycling therapies against drug resistance.
Domains
Engineering Sciences [physics]
Origin : Files produced by the author(s)