2015
DOI: 10.1007/82_2015_458
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Models of Viral Population Dynamics

Abstract: Models of viral population dynamics have contributed enormously to our understanding of the pathogenesis and transmission of several infectious diseases, the coevolutionary dynamics of viruses and their hosts, the mechanisms of action of drugs, and the effectiveness of interventions. In this chapter, we review major advances in the modeling of the population dynamics of the human immunodeficiency virus (HIV) and briefly discuss adaptations to other viruses.

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Cited by 9 publications
(9 citation statements)
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References 161 publications
(186 reference statements)
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“…We followed the practice of representing the within-host dynamics of viral infection with a system of ordinary differential equations [ 25 32 ]. Eqs ( 1 – 4 ) describe the model of viral infection and immune response in the absence of N-803 treatment.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We followed the practice of representing the within-host dynamics of viral infection with a system of ordinary differential equations [ 25 32 ]. Eqs ( 1 – 4 ) describe the model of viral infection and immune response in the absence of N-803 treatment.…”
Section: Methodsmentioning
confidence: 99%
“…Computational models are well-suited to quantify and deconvolute the effects of multiple interacting mechanisms in complex systems. Ordinary differential equation (ODE) models have been used to study HIV and its treatment (reviewed in [ 25 , 26 ]). ODE models have investigated the potential of various treatment strategies, including reactivating latent infections [ 27 , 28 ], cytotoxic cell stimulation [ 27 ], and cellular vaccines [ 29 ].…”
Section: Introductionmentioning
confidence: 99%
“…1,2 Modeling studies have since yielded key insights into the pathogenesis of HIV, including the evolution of drug resistance and immune escape, and guided strategies of intervention. 3,4 Much of this knowledge has been gleaned from studies on patients with HIV-1 subtype B (HIV-1B) infection. In the present context of the HIV epidemic, HIV-1 subtype C (HIV-1C) is the most prevalent subtype, particularly in low and middle-income countries (LMIC) like India, South Africa, and Ethiopia, and accounts for nearly 48% of all global infections.…”
Section: Introductionmentioning
confidence: 99%
“…The viral population within an infected individual comprises virions containing closely related but not identical viral genomes (Andino & Domingo, ; Padmanabhan & Dixit, ). V i denotes the viral subpopulation containing genomes of type i .…”
Section: Effector Functionmentioning
confidence: 99%
“…Variants of the model have captured the changes in viral load when this balance is perturbed using antiretroviral therapy (ART) and yielded estimates of the half‐lives of virions and infected cells in vivo (Ho et al, ; Nowak & May, ; Perelson, ; Perelson, Neumann, Markowitz, Leonard, & Ho, ; Wei et al, ). The models have also been extended to other viruses (Best et al, ; Dixit, Layden‐Almer, Layden, & Perelson, ; Neumann et al, ; Nowak et al, ; Padmanabhan & Dixit, ; Padmanabhan, Garaigorta, & Dixit, ). It has been of interest to estimate the contribution of effector CD8 + T cells in the observed loss of infected cells (Gadhamsetty, Beltman, & de Boer, ).…”
Section: Effector Functionmentioning
confidence: 99%