Open AccessMathematical Analysis of the TB Model with Treatment via Caputo-Type Fractional Derivative
Author(s) -
Xiaohong Zhang,
Aatif Ali,
Muhammad Altaf Khan,
Mohammad Y. Alshahrani,
Taseer Muhammad,
Saeed Islam
Publication year - 2021
Publication title -
discrete dynamics in nature and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 39
eISSN - 1607-887X
pISSN - 1026-0226
DOI - 10.1155/2021/9512371
Subject(s) - basic reproduction number , mathematics , fractional calculus , tuberculosis , lagrange polynomial , transmission (telecommunications) , type (biology) , order (exchange) , derivative (finance) , polynomial , mathematical optimization , computer science , mathematical analysis , medicine , biology , population , telecommunications , ecology , environmental health , finance , pathology , financial economics , economics
In this study, we formulate a noninteger-order mathematical model via the Caputo operator for the transmission dynamics of the bacterial disease tuberculosis (TB) in Khyber Pakhtunkhwa (KP), Pakistan. The number of confirmed cases from 2002 to 2017 is considered as incidence data for the estimation of parameters or to parameterize the model and analysis. The positivity and boundedness of the model solution are derived. For the dynamics of the tuberculosis model, we find the equilibrium points and the basic reproduction number. The proposed model is locally and globally stable at disease-free equilibrium, if the reproduction number ℛ 0 < 1 . Furthermore, to examine the behavior of the various parameters and different values of fractional-order derivative graphically, the most common iterative scheme based on fundamental theorem and Lagrange interpolation polynomial is implemented. From the numerical result, it is observed that the contact rate and treatment rate have a great impact on curtailing the tuberculosis disease. Furthermore, proper treatment is a key factor in reducing the TB transmission and prevalence. Also, the results are more precise for lower fractional order. The results from various numerical plots show that the fractional model gives more insights into the disease dynamics and on how to curtail the disease spread.