Literature DB >> 20369961

Influence of backward bifurcation on interpretation of r(0) in a model of epidemic tuberculosis with reinfection.

Benjamin H Singer1, Denise E Kirschner.   

Abstract

the extent to which reinfection of latently infected individuals contributes to the dynamics of tuberculosis (TB) epidemics. In this study we present an epidemiological model of Mycobacterium tuberculosis infection that includes the process of reinfection. Using analysis and numerical simulations, we observe the effect that varying levels of reinfection has on the qualitative dynamics of the TB epidemic. We examine cases of the model both with and without treatment of actively infected individuals. Next, we consider a variation of the model describing a heterogeneous population, stratified by susceptibility to TB infection. Results show that a threshold level of reinfection exists in all cases of the model. Beyond this threshold, the dynamics of the model are described by a backward bifurcation. Uncertainty analysis of the parameters shows that this threshold is too high to be attained in a realistic epidemic. However, we show that even for sub-threshold levels of reinfection, including reinfection in the model changes dynamic behavior of the model. In particular, when reinfection is present the basic reproductive number, R(0), does not accurately describe the severity of an epidemic.

Entities:  

Year:  2004        PMID: 20369961     DOI: 10.3934/mbe.2004.1.81

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  6 in total

1.  Modeling the joint epidemics of TB and HIV in a South African township.

Authors:  Nicolas Bacaër; Rachid Ouifki; Carel Pretorius; Robin Wood; Brian Williams
Journal:  J Math Biol       Date:  2008-04-15       Impact factor: 2.259

2.  A population model capturing dynamics of tuberculosis granulomas predicts host infection outcomes.

Authors:  Chang Gong; Jennifer J Linderman; Denise Kirschner
Journal:  Math Biosci Eng       Date:  2015-06       Impact factor: 2.080

3.  Emergent heterogeneity in declining tuberculosis epidemics.

Authors:  Caroline Colijn; Ted Cohen; Megan Murray
Journal:  J Theor Biol       Date:  2007-04-27       Impact factor: 2.691

4.  Modeling the impact of early therapy for latent tuberculosis patients and its optimal control analysis.

Authors:  S Mushayabasa; C P Bhunu
Journal:  J Biol Phys       Date:  2013-08-23       Impact factor: 1.365

5.  Assessing the effects of multiple infections and long latency in the dynamics of tuberculosis.

Authors:  Hyun M Yang; Silvia M Raimundo
Journal:  Theor Biol Med Model       Date:  2010-11-08       Impact factor: 2.432

6.  Quantifying TB transmission: a systematic review of reproduction number and serial interval estimates for tuberculosis.

Authors:  Y Ma; C R Horsburgh; L F White; H E Jenkins
Journal:  Epidemiol Infect       Date:  2018-07-04       Impact factor: 4.434

  6 in total

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