Optimal Perturbations of Systems with Delayed Independent Variables for Control of Dynamics of Infectious Diseases Based on Multicomponent Actions

In this paper, we apply optimal perturbations to control mathematical models of infectious diseases expressed as systems of nonlinear differential equations with delayed independent variables. We develop the method for calculation of perturbations of the initial state of a dynamical system with delayed independent variable producing maximal amplification in the given local norm taking into account weights of perturbation components. For the model of experimental virus infection, we construct optimal perturbation for two types of stationary states, with low or high viral load, corresponding to different variants of chronic virus infection flow.

[1]  Richard Bellman,et al.  Differential-Difference Equations , 1967 .

[2]  Guriĭ Ivanovich Marchuk,et al.  Mathematical Modelling of Immune Response in Infectious Diseases , 1997 .

[3]  D. Gurdasani,et al.  A systematic review of definitions of extreme phenotypes of HIV control and progression , 2013, AIDS.

[4]  P. Klenerman,et al.  Low level viral persistence after infection with LCMV: a quantitative insight through numerical bifurcation analysis. , 2001, Mathematical biosciences.

[5]  Miloud Sadkane,et al.  A Low-Rank Approximation for Computing the Matrix Exponential Norm , 2011, SIAM J. Matrix Anal. Appl..

[6]  E. Reshotko Transient growth: A factor in bypass transition , 2001 .

[7]  Eric Walter,et al.  Solving Ordinary Differential Equations , 2019, Programming for Computations - Python.

[8]  Y. Nechepurenko,et al.  Computing the maximum amplification of the solution norm of differential-algebraic systems , 2012 .

[9]  J. Doyle,et al.  Reverse Engineering of Biological Complexity , 2002, Science.

[10]  Rolf M. Zinkernagel,et al.  Virus persistence in acutely infected immunocompetent mice by exhaustion of antiviral cytotoxic effector T cells , 1993, Nature.

[11]  Dan S. Henningson,et al.  On the role of linear mechanisms in transition to turbulence , 1994 .

[12]  G. Bocharov,et al.  Maximum response perturbation-based control of virus infection model with time-delays , 2017 .

[13]  Y. Nechepurenko,et al.  Fast computation of optimal disturbances for duct flows with a given accuracy , 2010 .

[14]  Miloud Sadkane,et al.  Computing humps of the matrix exponential , 2017, J. Comput. Appl. Math..

[15]  Hiroaki Kitano,et al.  Biological robustness in complex host-pathogen systems. , 2007, Progress in drug research. Fortschritte der Arzneimittelforschung. Progres des recherches pharmaceutiques.

[16]  H. Weyl The Classical Groups , 1940 .

[17]  B. Mothé,et al.  Pathogenesis and Treatment of HIV Infection: The Cellular, the Immune System and the Neuroendocrine Systems Perspective , 2013, International reviews of immunology.

[18]  Y. Takeuchi,et al.  The stability of generalized Volterra equations , 1978 .

[19]  Hiroaki Kitano,et al.  Biological robustness , 2008, Nature Reviews Genetics.

[20]  E John Wherry,et al.  Molecular and transcriptional basis of CD4⁺ T cell dysfunction during chronic infection. , 2014, Immunity.

[21]  Martin Meier-Schellersheim,et al.  Systems biology in immunology: a computational modeling perspective. , 2011, Annual review of immunology.

[22]  P. Klenerman,et al.  Persistence of lymphocytic choriomeningitis virus at very low levels in immune mice. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[23]  James Sharpe,et al.  A global “imaging’’ view on systems approaches in immunology , 2012, European journal of immunology.

[24]  G. I. Marchuk,et al.  Numerical solution by LMMs of stiff delay differential systems modelling an immune response , 1996 .

[25]  Nicholas J. Higham,et al.  The Scaling and Squaring Method for the Matrix Exponential Revisited , 2005, SIAM J. Matrix Anal. Appl..

[26]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[27]  G. Bocharov,et al.  Modelling the dynamics of LCMV infection in mice: conventional and exhaustive CTL responses. , 1998, Journal of theoretical biology.

[28]  S. Lewin,et al.  The search for an HIV cure: tackling latent infection. , 2013, The Lancet. Infectious diseases.