Abstract：
:The resurgence of tuberculosis in the 1990s and the emergence of drug-resistant tuberculosis in the first decade of the 21st century increased the importance of epidemiological models for the disease. Due to slow progression of tuberculosis, the transmission dynamics and its long-term effects can often be better observed and predicted using simulations of epidemiological models. This study provides a review of earlier study on modeling different aspects of tuberculosis dynamics. The models simulate tuberculosis transmission dynamics, treatment, drug resistance, control strategies for increasing compliance to treatment, HIV/TB co-infection, and patient groups. The models are based on various mathematical systems, such as systems of ordinary differential equations, simulation models, and Markov Chain Monte Carlo methods. The inferences from the models are justified by case studies and statistical analysis of TB patient datasets.
journal_name
Math Bioscijournal_title
Mathematical biosciencesauthors
Ozcaglar C,Shabbeer A,Vandenberg SL,Yener B,Bennett KPdoi
10.1016/j.mbs.2012.02.003subject
Has Abstractpub_date
2012-04-01 00:00:00pages
77-96issue
2eissn
0025-5564issn
1879-3134pii
S0025-5564(12)00019-3journal_volume
236pub_type
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