li2

R0 = 1.125>1, The endemic equlibrium, P* = (4.49e6,4134,1033,3.44e6) is stable. [figure 5]

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The within-host dynamics of malaria infection with immune response.

  • Yilong Li
  • Shigui Ruan
  • Dongmei Xiao
Math Biosci Eng 2011; 8 (4): 999
Abstract
Malaria infection is one of the most serious global health problems of our time. In this article the blood-stage dynamics of malaria in an infected host are studied by incorporating red blood cells, malaria parasitemia and immune effectors into a mathematical model with nonlinear bounded Michaelis-Menten-Monod functions describing how immune cells interact with infected red blood cells and merozoites. By a theoretical analysis of this model, we show that there exists a threshold value R0, namely the basic reproduction number, for the malaria infection. The malaria-free equilibrium is global asymptotically stable if R0 < 1. If R0 > 1, there exist two kinds of infection equilibria: malaria infection equilibrium (without specific immune response) and positive equilibrium (with specific immune response). Conditions on the existence and stability of both infection equilibria are given. Moreover, it has been showed that the model can undergo Hopf bifurcation at the positive equilibrium and exhibit periodic oscillations. Numerical simulations are also provided to demonstrate these theoretical results.

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 0.0 1.0
Id Name Initial quantity Compartment Fixed
E Population of Immune effectors 0.0001 default
H Population of RBCs 5000000.0 default
I Population of iRBCs 0.0 default
M Population of malaria parasites 10000.0 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
v1 v1 ∅ = H

lambda
v10 v10 ∅ = E

k1 * I * E / (1 + beta * I)
v11 v11 ∅ = E

k2 * M * E / (1 + gamma * M)
v2 v2 H = ∅

d1 * H
v3 v3 H = I

alfa * H * M
v4 v4 I = ∅

delta * I
v5 v5 I = ∅

p1 * I * E / (1 + beta * I)
v6 v6 ∅ = M

r * I
v7 v7 M = ∅

mu * M
v8 v8 M = ∅

p2 * M * E / (1 + gamma * M)
v9 v9 E = ∅

d2 * E

Global parameters

Id Value
alfa 0.0000009
beta 0.0005
d1 0.0083
d2 0.04
delta 1.0
gamma 0.000667
k1 0.000025
k2 0.0000103
lambda 41500.0
mu 48.0
p1 0.00000001
p2 0.00000001
r 12.0

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Trigger Assignments