Literature DB >> 12387922

Comparing epidemic tuberculosis in demographically distinct heterogeneous populations.

Brian M Murphy1, Benjamin H Singer, Shoana Anderson, Denise Kirschner.   

Abstract

There is wide variation in endemic tuberculosis (TB) levels between countries and we seek to identify possible causes of these differences. In this study we present an epidemiological model of Mycobacterium tuberculosis infection to investigate the effects of host genetics and demographic factors on epidemic TB. We discuss the general framework for this approach and present analytical results to identify important parameters affecting steady-state prevalence and incidence rates of TB disease. We then use numerical simulations of our model to observe the effects of a genetically susceptible subpopulation on TB disease dynamics at the population level. Finally, we simulate infection within a genetically heterogeneous population in two demographic settings: India (a typical population with high TB prevalence) and the USA (a typical population with low TB prevalence). Results show that changes in transmission parameters, the fraction of the population genetically susceptible to infection, and demographic factors strongly affect TB prevalence and incidence rates.

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Year:  2002        PMID: 12387922     DOI: 10.1016/s0025-5564(02)00133-5

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


  13 in total

Review 1.  Perspectives on the basic reproductive ratio.

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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

Review 3.  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

4.  Population decline induced by gonorrhoea and tuberculosis transmission: Micronesia during the Japanese occupation, 1919-45.

Authors:  Susan Cassels; Burton H Singer
Journal:  J Popul Res (Canberra)       Date:  2010-12-01

Review 5.  A multifaceted approach to modeling the immune response in tuberculosis.

Authors:  Simeone Marino; Jennifer J Linderman; Denise E Kirschner
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010-12-31

6.  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

Review 7.  Data needs for evidence-based decisions: a tuberculosis modeler's 'wish list'.

Authors:  D W Dowdy; C Dye; T Cohen
Journal:  Int J Tuberc Lung Dis       Date:  2013-07       Impact factor: 2.373

8.  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

9.  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

10.  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

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