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International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 4 | Issue 9 | Year 2013 | Article Id. IJMTT-V4I9P2 | DOI : https://doi.org/10.14445/22315373/IJMTT-V4I9P2

Mathematical Modelling of Pulmonary and Extra-pulmonary Tuberculosis


Nita H. Shah, Jyoti Gupta
Abstract

The entire population is divided into five compartments viz. susceptible (S), exposed (E), infectious with pulmonary tuberculosis (I) and extra-pulmonary tuberculosis (X) and treated (T). Basic reproduction number R0 is defined and a relation is established for it. Steady state conditions are derived showing that when 0 R 1there is a disease free equilibrium which is locally asymptotically stable whereas for 0 R 1there exists an endemic equilibrium. Sensitivity of R0 to each parameter is analysed.

Keywords
Extra-pulmonary, Pulmonary, Tuberculosis, Stability analysis.
References

[1] H.S. Joshi and M.N. Bates, “Comparision of pulmonary and extrapulmonary tuberculosis in Nepal-a hospital-based retrospective study”. BMC infectious disease, 2008, 8:8. doi: 10.1186/1471-2334-8-8.
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[3] C. Coljin, T. Cohen and M. Murray, “Mathematical Models of Tuberculosis: Accomplishments and future challenges”. BIOMAT- 2006, International Symposium on Mathematical and Computational Biology, doi: 10.1142/9789812708779_0008.
[4] C.J.L. Murray and J. A. Salomon, “Using mathematical models to evaluate global tuberculosis control strategies”. Harward Centre for Population and Development Studies, Harvard University, Cambridge MA.
[5] C. Castillo-Chavez and Z. Feng, “To treat or not to treat: the case of tuberculosis”. Journal of Mathematical Biology, Springer-Verlag, 35: pp 629-656, 1997. [6] C. Coljin, T. Cohen and M. Murray, “Mathematical Models of Tuberculosis: Accomplishments and future challenges”. BIOMAT- 2006, International Symposium on Mathematical and Computational Biology, doi: 10.1142/9789812708779_0008.
[7] C.J.L. Murray and J. A. Salomon, “Using mathematical models to evaluate global tuberculosis control strategies”. Harward Centre for Population and Development Studies, Harvard University, Cambridge MA.
[8] O. Diekmann, J. A. P. Heesterbeek, Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation, Wiley, 1999.
[9] Sarah A. Al-Sheikh: “Modeling and analysis of an SEIR Epidemic Model with a Limited Resource for Treatment”. Global Journal of Sceience Frontier Research: Mathematics and Decision Sciences, vol 12, pp. 57 – 66, 2012.
[10] P. van den Driessche and J. Watmough.: “Reproduction numbers and subthreshold endemic equilibria for compartmental models of disease transmission”. Mathematics Biosciences, 180, pp. 29-48, 2002.
[11] S.A. Egbetade and M.O. Ibrahim,”Global Stability Result for a Tuberculosis Epidemic Model”. Research Journal of mathematics and Statistics, 4(1): pp. 14-20, 2012. [12] J. H. Jones: Notes on R0. Standford University, 2007.
[13] www.who.int/tb/data/ [14] www.tbcindia.nic.in/ [15] http://www.cdc.gov/

Citation :

Nita H. Shah, Jyoti Gupta, "Mathematical Modelling of Pulmonary and Extra-pulmonary Tuberculosis," International Journal of Mathematics Trends and Technology (IJMTT), vol. 4, no. 9, pp. 158-162, 2013. Crossref, https://doi.org/10.14445/22315373/IJMTT-V4I9P2

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