Sensitivity Analysis of Mathematical Modelling of Tuberculosis Disease With Resistance to Drug Treatments

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Date
2021-02-16
Authors
Mufutau, R.A
Akinpelu, F.
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Mathematical Sciences and Optimization: Theory and Applications
Abstract
Drug resistance to the line of treatment is also of concerns in the control of Tuberculosis disease in the world [11], an individual with drug resistance will still retain the disease even after several treatment. In this study, we consider a mathematical model of a tuberculosis disease with resistance to the first line of treatment, taking into consideration population of children and adults. We considered six different compartment (S1S2EIRHR), an extension of SEIR model by introducing two different susceptible classes (S1S2) and drug resistance(RH) to the first line of treatment. The system was described by an ordinary differential equation, which was solved algebraically to obtained the equilibrium point (disease free and endemic equilibrium point). The next generation matrix was employed to evaluate the basic reproduction number and column reduction matrix to get the local stability of the systems. It was observed that the age group had bigger effect on the control of TB. The drug resistance had a little effect on the total control of the disease. At the end, three effective measure were found,that would help reach the major goal of the World Health Organization(WHO)which includes: to reduce the exposed rate of the disease especially in the adults, increase the recovery rate and reduce the transmission rate of the adults.
Description
Scholarly articles
Keywords
Tuberculosis , Resistance to Drug , Basic Reproduction number , Equilibrium , Stability , Sensitivity Analysis , Research Subject Categories::MATHEMATICS
Citation
Mufutau, R. A. & Akinpelu, F. (2020). Sensitivity Analysis of Mathematical Modelling of Tuberculosis Disease With Resistance to Drug Treatments. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 6(2), 940-955