title: Large Variations in HIV-1 Viral Load Explained by Shifting-Mosaic Metapopulation Dynamics.
abstract: The viral population of HIV-1, like many pathogens that cause systemic infection, is structured and differentiated within the body. The dynamics of cellular immune trafficking through the blood and within compartments of the body has also received wide attention. Despite these advances, mathematical models, which are widely used to interpret and predict viral and immune dynamics in infection, typically treat the infected host as a well-mixed homogeneous environment. Here, we present mathematical, analytical, and computational results that demonstrate that consideration of the spatial structure of the viral population within the host radically alters predictions of previous models. We study the dynamics of virus replication and cytotoxic T lymphocytes (CTLs) within a metapopulation of spatially segregated patches, representing T cell areas connected by circulating blood and lymph. The dynamics of the system depend critically on the interaction between CTLs and infected cells at the within-patch level. We show that for a wide range of parameters, the system admits an unexpected outcome called the shifting-mosaic steady state. In this state, the whole body's viral population is stable over time, but the equilibrium results from an underlying, highly dynamic process of local infection and clearance within T-cell centers. Notably, and in contrast to previous models, this new model can explain the large differences in set-point viral load (SPVL) observed between patients and their distribution, as well as the relatively low proportion of cells infected at any one time, and alters the predicted determinants of viral load variation.
authors.affiliation: Department of Zoology, Tinbergen Building, University of Oxford, Oxford, United Kingdom.|Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St. Mary's Campus, London, United Kingdom.
authors.forename: Katrina A
authors.initials: KA
authors.lastname: Lythgoe
authors.affiliation: Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St. Mary's Campus, London, United Kingdom.
authors.forename: François
authors.initials: F
authors.lastname: Blanquart
authors.affiliation: Mathematics Institute, Zeeman Building, University of Warwick, Coventry, United Kingdom.
authors.forename: Lorenzo
authors.identifier: http://orcid.org/0000-0002-3436-6487
authors.initials: L
authors.lastname: Pellis
authors.affiliation: Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, St. Mary's Campus, London, United Kingdom.|Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
authors.forename: Christophe
authors.identifier: http://orcid.org/0000-0003-2399-9657
authors.initials: C
authors.lastname: Fraser
mesh_terms: D015497:HIV-1 / Q000235:genetics / Q000302:isolation & purification* / Q000502:physiology; D006801:Humans; D008962:Models, Theoretical; D009030:Mosaicism; D013602:T-Lymphocytes, Cytotoxic / Q000276:immunology; D019562:Viral Load; D014774:Virulence; D014779:Virus Replication