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Simple mathematical models do not accurately predict early SIV dynamics
Journal article   Open access   Peer reviewed

Simple mathematical models do not accurately predict early SIV dynamics

Cecilia Noecker, Krista Schaefer, Kelly Zaccheo, Yiding Yang, Judy Day, Vitaly V Ganusov and Yonghong F Yang
Viruses, v 7(3), pp 1189-1217
13 Mar 2015
DOI: https://doi.org/10.3390/v7031189
PMID: 25781919
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.3390/v7031189View
Published, Version of Record (VoR)CC BY V4.0,  Open

Abstract

Animals Blood - virology Macaca mulatta Models, Theoretical Simian Acquired Immunodeficiency Syndrome - virology Simian Immunodeficiency Virus - isolation & purification Viral Load
Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1-2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the "standard" mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available.

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17 citations in Web of Science
18 citations in Scopus

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UN Sustainable Development Goals (SDGs)

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#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Virology
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