Literature DB >> 32920726

Traveling Waves and Estimation of Minimal Wave Speed for a Diffusive Influenza Model with Multiple Strains.

Guoting Chen1, Xinchu Fu2, Mengfeng Sun3,4.   

Abstract

Antiviral treatment remains one of the key pharmacological interventions against influenza pandemic. However, widespread use of antiviral drugs brings with it the danger of drug resistance evolution. To assess the risk of the emergence and diffusion of resistance, in this paper, we develop a diffusive influenza model where influenza infection involves both drug-sensitive and drug-resistant strains. We first analyze its corresponding reaction model, whose reproduction numbers and equilibria are derived. The results show that the sensitive strains can be eliminated by treatment. Then, we establish the existence of the three kinds of traveling waves starting from the disease-free equilibrium, i.e., semi-traveling waves, strong traveling waves and persistent traveling waves, from which we can get some useful information (such as whether influenza will spread, asymptotic speed of propagation, the final state of the wavefront). On the other hand, we discuss three situations in which semi-traveling waves do not exist. When the control reproduction number [Formula: see text] is larger than 1, the conditions for the existence and nonexistence of traveling waves are determined completely by the reproduction numbers [Formula: see text], [Formula: see text] and the wave speed c. Meanwhile, we give an interval estimation of minimal wave speed for influenza transmission, which has important guiding significance for the control of influenza in reality. Our findings demonstrate that the control of influenza depends not only on the rates of resistance emergence and transmission during treatment, but also on the diffusion rates of influenza strains, which have been overlooked in previous modeling studies. This suggests that antiviral treatment should be implemented appropriately, and infected individuals (especially with the resistant strain) should be tested and controlled effectively. Finally, we outline some future directions that deserve further investigation.

Entities:  

Keywords:  Antiviral treatment; Diffusive influenza model; Minimal wave speed; Multiple strains; Reproduction numbers; Traveling waves

Year:  2020        PMID: 32920726      PMCID: PMC7487074          DOI: 10.1007/s11538-020-00799-8

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  21 in total

1.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.

Authors:  P van den Driessche; James Watmough
Journal:  Math Biosci       Date:  2002 Nov-Dec       Impact factor: 2.144

2.  Emergence of drug-resistant influenza virus: population dynamical considerations.

Authors:  Roland R Regoes; Sebastian Bonhoeffer
Journal:  Science       Date:  2006-04-21       Impact factor: 47.728

3.  Strategies for containing an emerging influenza pandemic in Southeast Asia.

Authors:  Neil M Ferguson; Derek A T Cummings; Simon Cauchemez; Christophe Fraser; Steven Riley; Aronrag Meeyai; Sopon Iamsirithaworn; Donald S Burke
Journal:  Nature       Date:  2005-08-03       Impact factor: 49.962

4.  Resistance to anti-infective drugs and the threat to public health.

Authors:  David L Heymann
Journal:  Cell       Date:  2006-02-24       Impact factor: 41.582

5.  Modeling targeted layered containment of an influenza pandemic in the United States.

Authors:  M Elizabeth Halloran; Neil M Ferguson; Stephen Eubank; Ira M Longini; Derek A T Cummings; Bryan Lewis; Shufu Xu; Christophe Fraser; Anil Vullikanti; Timothy C Germann; Diane Wagener; Richard Beckman; Kai Kadau; Chris Barrett; Catherine A Macken; Donald S Burke; Philip Cooley
Journal:  Proc Natl Acad Sci U S A       Date:  2008-03-10       Impact factor: 11.205

6.  Seasonal dynamics of recurrent epidemics.

Authors:  Lewi Stone; Ronen Olinky; Amit Huppert
Journal:  Nature       Date:  2007-03-29       Impact factor: 49.962

7.  Influenza A pandemics of the 20th century with special reference to 1918: virology, pathology and epidemiology.

Authors:  J S Oxford
Journal:  Rev Med Virol       Date:  2000 Mar-Apr       Impact factor: 6.989

8.  Risk factors of influenza transmission in households.

Authors:  Cécile Viboud; Pierre-Yves Boëlle; Simon Cauchemez; Audrey Lavenu; Alain-Jacques Valleron; Antoine Flahault; Fabrice Carrat
Journal:  Br J Gen Pract       Date:  2004-09       Impact factor: 5.386

9.  Antigenic and genetic characteristics of swine-origin 2009 A(H1N1) influenza viruses circulating in humans.

Authors:  Rebecca J Garten; C Todd Davis; Colin A Russell; Bo Shu; Stephen Lindstrom; Amanda Balish; Wendy M Sessions; Xiyan Xu; Eugene Skepner; Varough Deyde; Margaret Okomo-Adhiambo; Larisa Gubareva; John Barnes; Catherine B Smith; Shannon L Emery; Michael J Hillman; Pierre Rivailler; James Smagala; Miranda de Graaf; David F Burke; Ron A M Fouchier; Claudia Pappas; Celia M Alpuche-Aranda; Hugo López-Gatell; Hiram Olivera; Irma López; Christopher A Myers; Dennis Faix; Patrick J Blair; Cindy Yu; Kimberly M Keene; P David Dotson; David Boxrud; Anthony R Sambol; Syed H Abid; Kirsten St George; Tammy Bannerman; Amanda L Moore; David J Stringer; Patricia Blevins; Gail J Demmler-Harrison; Michele Ginsberg; Paula Kriner; Steve Waterman; Sandra Smole; Hugo F Guevara; Edward A Belongia; Patricia A Clark; Sara T Beatrice; Ruben Donis; Jacqueline Katz; Lyn Finelli; Carolyn B Bridges; Michael Shaw; Daniel B Jernigan; Timothy M Uyeki; Derek J Smith; Alexander I Klimov; Nancy J Cox
Journal:  Science       Date:  2009-05-22       Impact factor: 47.728

10.  Emergence and spread of drug resistant influenza: A two-population game theoretical model.

Authors:  Kamal Jnawali; Bryce Morsky; Keith Poore; Chris T Bauch
Journal:  Infect Dis Model       Date:  2016-09-02
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