v1
A = ∅
v10
∅ = V
v11
∅ = V
v2
∅ = T
v3
∅ = T
v4
T = Tstar
v5
T = ∅
v6
Tstar = ∅
v7
CC = ∅
v8
V = ∅
v9
Tstar = CC
Note that constraints are not enforced in simulations. It remains the responsibility of the user to verify that simulation results satisfy these constraints.
Modeling the effects of vaccination on chronically infected HIV-positive patients.
J. Acquir. Immune Defic. Syndr. 2002;
31
(4):
369-377
- PubMed: 12447006
- ISSN: 1525-4135
- URL: https://ncbi.nlm.nih.gov/pubmed/12447006
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.
The model reproduces some of the subplots in Figure 2 of the paper. The model is coded to represent patient number 3. The plots for patient 9 and 10 were also reproduced (in Figure 2).