Literature DB >> 12875819

On treatment of tuberculosis in heterogeneous populations.

Brian M Murphy1, Benjamin H Singer, Denise Kirschner.   

Abstract

Global eradication of tuberculosis (TB) is an international agenda. Thus understanding effects of treatment of TB in different settings is crucial. In previous work, we introduced the framework for a mathematical model of epidemic TB in demographically distinct, heterogeneous populations. Simulations showed the importance of genetic susceptibility in determining endemic prevalence levels. In the work presented here, we include treatment and investigate different strategies for treatment of latent and active TB disease in heterogeneous populations. We illustrate how the presence of a genetically susceptible subpopulation dramatically alters effects of treatment in the same way a core population does in the setting of sexually transmitted diseases. In addition, we evaluate treatment strategies that focus specifically on this subpopulation, and our results indicate that genetically susceptible subpopulations should be accounted for when designing treatment strategies to achieve the greatest reduction in disease prevalence.

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Year:  2003        PMID: 12875819     DOI: 10.1016/s0022-5193(03)00038-9

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  9 in total

1.  How do pathogen evolution and host heterogeneity interact in disease emergence?

Authors:  Andrew Yates; Rustom Antia; Roland R Regoes
Journal:  Proc Biol Sci       Date:  2006-12-22       Impact factor: 5.349

2.  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

3.  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

Review 4.  Epidemiological models of Mycobacterium tuberculosis complex infections.

Authors:  Cagri Ozcaglar; Amina Shabbeer; Scott L Vandenberg; Bülent Yener; Kristin P Bennett
Journal:  Math Biosci       Date:  2012-03-01       Impact factor: 2.144

5.  Epidemiological benefits of more-effective tuberculosis vaccines, drugs, and diagnostics.

Authors:  Laith J Abu-Raddad; Lorenzo Sabatelli; Jerusha T Achterberg; Jonathan D Sugimoto; Ira M Longini; Christopher Dye; M Elizabeth Halloran
Journal:  Proc Natl Acad Sci U S A       Date:  2009-08-03       Impact factor: 11.205

6.  Modeling socio-demography to capture tuberculosis transmission dynamics in a low burden setting.

Authors:  Giorgio Guzzetta; Marco Ajelli; Zhenhua Yang; Stefano Merler; Cesare Furlanello; Denise Kirschner
Journal:  J Theor Biol       Date:  2011-09-03       Impact factor: 2.691

7.  Parameter identification in a tuberculosis model for Cameroon.

Authors:  Dany Pascal Moualeu-Ngangue; Susanna Röblitz; Rainald Ehrig; Peter Deuflhard
Journal:  PLoS One       Date:  2015-04-13       Impact factor: 3.240

8.  Backward bifurcation and hysteresis in models of recurrent tuberculosis.

Authors:  Isaac Mwangi Wangari; Lewi Stone
Journal:  PLoS One       Date:  2018-03-22       Impact factor: 3.240

9.  Interpreting measures of tuberculosis transmission: a case study on the Portuguese population.

Authors:  Joao Sollari Lopes; Paula Rodrigues; Suani T R Pinho; Roberto F S Andrade; Raquel Duarte; M Gabriela M Gomes
Journal:  BMC Infect Dis       Date:  2014-06-18       Impact factor: 3.090

  9 in total

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