Literature DB >> 11909117

Simple model of epidemics with pathogen mutation.

Michelle Girvan1, Duncan S Callaway, M E J Newman, Steven H Strogatz.   

Abstract

We study how the interplay between the memory immune response and pathogen mutation affects epidemic dynamics in two related models. The first explicitly models pathogen mutation and individual memory immune responses, with contacted individuals becoming infected only if they are exposed to strains that are significantly different from other strains in their memory repertoire. The second model is a reduction of the first to a system of difference equations. In this case, individuals spend a fixed amount of time in a generalized immune class. In both models, we observe four fundamentally different types of behavior, depending on parameters: (1) pathogen extinction due to lack of contact between individuals; (2) endemic infection; (3) periodic epidemic outbreaks; and (4) one or more outbreaks followed by extinction of the epidemic due to extremely low minima in the oscillations. We analyze both models to determine the location of each transition. Our main result is that pathogens in highly connected populations must mutate rapidly in order to remain viable.

Entities:  

Mesh:

Year:  2002        PMID: 11909117     DOI: 10.1103/PhysRevE.65.031915

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  19 in total

1.  A two-tiered model for simulating the ecological and evolutionary dynamics of rapidly evolving viruses, with an application to influenza.

Authors:  Katia Koelle; Priya Khatri; Meredith Kamradt; Thomas B Kepler
Journal:  J R Soc Interface       Date:  2010-03-24       Impact factor: 4.118

2.  Epidemic dynamics and antigenic evolution in a single season of influenza A.

Authors:  Maciej F Boni; Julia R Gog; Viggo Andreasen; Marcus W Feldman
Journal:  Proc Biol Sci       Date:  2006-06-07       Impact factor: 5.349

3.  The reinfection threshold regulates pathogen diversity: the case of influenza.

Authors:  Dinis Gökaydin; José B Oliveira-Martins; Isabel Gordo; M Gabriela M Gomes
Journal:  J R Soc Interface       Date:  2007-02-22       Impact factor: 4.118

4.  Spatio-temporal waves and targeted vaccination in recurrent epidemic network models.

Authors:  Anna Litvak-Hinenzon; Lewi Stone
Journal:  J R Soc Interface       Date:  2008-10-28       Impact factor: 4.118

5.  Effects of network topology, transmission delays, and refractoriness on the response of coupled excitable systems to a stochastic stimulus.

Authors:  Daniel B Larremore; Woodrow L Shew; Edward Ott; Juan G Restrepo
Journal:  Chaos       Date:  2011-06       Impact factor: 3.642

Review 6.  Capturing the dynamics of pathogens with many strains.

Authors:  Adam J Kucharski; Viggo Andreasen; Julia R Gog
Journal:  J Math Biol       Date:  2015-03-24       Impact factor: 2.259

7.  Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission.

Authors:  Benjamin Roche; Jean-François Guégan; François Bousquet
Journal:  BMC Bioinformatics       Date:  2008-10-15       Impact factor: 3.169

8.  Towards multiscale modeling of influenza infection.

Authors:  Lisa N Murillo; Michael S Murillo; Alan S Perelson
Journal:  J Theor Biol       Date:  2013-04-19       Impact factor: 2.691

9.  Influenza A gradual and epochal evolution: insights from simple models.

Authors:  Sébastien Ballesteros; Elisabeta Vergu; Bernard Cazelles
Journal:  PLoS One       Date:  2009-10-20       Impact factor: 3.240

10.  Incorporating demographic stochasticity into multi-strain epidemic models: application to influenza A.

Authors:  Pavlo Minayev; Neil Ferguson
Journal:  J R Soc Interface       Date:  2009-01-21       Impact factor: 4.118

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