naresh1

None

None

None

None

None

None

Title

Modelling and analysis of HIV TB co infection in a variable size population

Authors

R. Naresh (a) and A. Tripathi (b)

Affiliations

a) Department of Mathematics, Harcourt Butler Technological Institute, Kanpur, Uttar Pradesh, 208002, India E-mail: b) Department of Mathematics, Harcourt Butler Technological Institute, Kanpur, Uttar Pradesh, 208002, India

Abstract

In this paper, a nonlinear mathematical model is proposed for the transmission dynamics of HIV and a curable TB pathogen within a population of varying size. In the model, we have divided the population into four sub classes of susceptibles, TB infectives, HIV infectives and that of AIDS patients. The model exhibits four equillibria namely, a disease free, HIV free, TB free and a co‐infection equilibrium. The model has been studied qualitatively using stability theory of nonlinear differential equations. It is shown that the positive co‐infection equilibrium is always locally stable but it may become globally stable under certain conditions showing that the disease becomes endemic due to constant migration of the population into the habitat. A numerical study of the model is also performed to investigate the influence of certain key parameters on the spread of the disease.

Journal

Mathematical Modelling and Analysis. Volume 10, Issue 3, 2005.

Unit definitions have no effect on the numerical analysis of the model. It remains the responsibility of the modeler to ensure the internal numerical consistency of the model. If units are provided, however, the consistency of the model units will be checked.

Name Definition
Id Name Spatial dimensions Size
default 1.0
Id Name Initial quantity Compartment Fixed
A AIDS 500.0 default
EXT EXT 1.0 default
I1 TB infected 2000.0 default
I2 HIV infected 3000.0 default
N Total population 20000.0 default

Initial assignments are expressions that are evaluated at time=0. It is not recommended to create initial assignments for all model entities. Restrict the use of initial assignments to cases where a value is expressed in terms of values or sizes of other model entities. Note that it is not permitted to have both an initial assignment and an assignment rule for a single model entity.

Definition
Id Name Objective coefficient Reaction Equation and Kinetic Law Flux bounds
v_1 EXT = N

Q0
v_10 I2 = EXT

d*I2
v_11 A = EXT

alpha*A
v_12 A = EXT

d*A
v_2 N = EXT

d*N
v_3 N = EXT

alpha*A
v_4 EXT = I1

beta1*(N-I1-I2-A)*I1/N
v_5 I1 = I2

beta3*I1*I2/N
v_6 I1 = EXT

lambda*I1
v_7 I1 = EXT

d*I1
v_8 EXT = I2

beta2*(N-I1-I2-A)*I2/N
v_9 I2 = A

delta*I2

Global parameters

Id Value
Q0 2000.0
alpha 1.0
beta1 0.925
beta2 0.365
beta3 1.15
d 0.02
delta 0.2
lambda 0.3

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments