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jones1

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Modeling the effects of vaccination on chronically infected HIV-positive patients.

  • Laura E Jones
  • Alan S Perelson
J. Acquir. Immune Defic. Syndr. 2002; 31 (4): 369-377
Abstract
T-cell activation plays a critical role in the initiation and propagation of HIV-1 infection and yet transient activation of the immune system is a normal response to immunization. While it is now considered wise to vaccinate HIV-1-positive patients, it is crucial to anticipate any lasting effects of vaccination on plasma HIV-1 RNA levels and on infected T-cell populations. We extend a simple dynamic model of HIV infection to include T-cell activation by vaccination. We show that the model can reproduce many but not all of the features of the post-tetanus immunization rise in viral load observed and reported on by Stanley et al. in 1966 ( 334:1222-1230). Amplitudes and approximate timing of postimmunization peak viral loads were matched in 10 of 12 cases; in patients with double postimmunization peaks of nearly equal amplitude the later peaks were matched. Furthermore, our simulations suggest that productively infected cell populations track postvaccination increases in plasma viral load, rising and falling in concert over a period of about 4 weeks, whereas chronically infected cells peak later and remain elevated over baseline levels for up to 6 weeks postvaccination.

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
A 1.0 default
CC 18800.0 default
T 323000.0 default
Tstar 7800.0 default
V 120000.0 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 A = ∅

gamma * A * T
v10 ∅ = V

delta * NN * Tstar
v11 ∅ = V

mu * NC * CC
v2 ∅ = T

lambda
v3 ∅ = T

a * A * T / (KK + A)
v4 T = Tstar

k * T * V
v5 T = ∅

d * T
v6 Tstar = ∅

delta * Tstar
v7 CC = ∅

mu * CC
v8 V = ∅

c * V
v9 Tstar = CC

alpha * k * T * V

Global parameters

Id Value
KK 3.36
NC 4.11
NN 285.0
a 1.6
alpha 0.195
c 13.0
d 0.01
delta 0.7
gamma 0.0000017475
k 0.00000017437
lambda 10000.0
mu 0.07

Local parameters

Id Value Reaction

Assignment rules

Definition

Rate rules

Definition

Algebraic rules

Definition
Definition
Trigger Assignments