Literature DB >> 11965261

Vaccination strategies and backward bifurcation in an age-since-infection structured model.

Christopher M Kribs-Zaleta1, Maia Martcheva.   

Abstract

We consider models for a disease with acute and chronic infective stages, and variable infectivity and recovery rates, within the context of a vaccination campaign. Models for SIRS and SIS disease cycles exhibit backward bifurcations under certain conditions, which complicate the criteria for success of the vaccination campaign by making it possible to have stable endemic states when R(0)<1. We also show the extent to which the forms of the infectivity and recovery functions affect the possibility of backward bifurcations. SIR and SI models examined do not exhibit this behavior.

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Year:  2002        PMID: 11965261     DOI: 10.1016/s0025-5564(01)00099-2

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  6 in total

1.  The minimum effort required to eradicate infections in models with backward bifurcation.

Authors:  Muntaser Safan; Hans Heesterbeek; Klaus Dietz
Journal:  J Math Biol       Date:  2006-08-05       Impact factor: 2.259

2.  An age-structured epidemic model of rotavirus with vaccination.

Authors:  E Shim; Z Feng; M Martcheva; C Castillo-Chavez
Journal:  J Math Biol       Date:  2006-08-17       Impact factor: 2.259

3.  Vaccination based control of infections in SIRS models with reinfection: special reference to pertussis.

Authors:  Muntaser Safan; Mirjam Kretzschmar; Karl P Hadeler
Journal:  J Math Biol       Date:  2012-09-05       Impact factor: 2.259

4.  Modelling the effect of a booster vaccination on disease epidemiology.

Authors:  M E Alexander; S M Moghadas; P Rohani; A R Summers
Journal:  J Math Biol       Date:  2005-11-10       Impact factor: 2.164

5.  The impact of vaccination on the modeling of COVID-19 dynamics: a fractional order model.

Authors:  Aatif Ali; Saif Ullah; Muhammad Altaf Khan
Journal:  Nonlinear Dyn       Date:  2022-08-28       Impact factor: 5.741

6.  Mathematical epidemiology is not an oxymoron.

Authors:  Fred Brauer
Journal:  BMC Public Health       Date:  2009-11-18       Impact factor: 3.295

  6 in total

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