Persistence of viral infections on the population level explained by an immunoepidemiological model

Kostova, Tanya

doi:10.1016/j.mbs.2005.08.003

Cited by 25 publications

(21 citation statements)

References 8 publications

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“…The dependence of the epidemiological reproduction number R 0 on within-host pathogen load and immune responses is of key interest as it explains how the within-host dynamics affects the population-level persistence of the disease [19,31,34,36,40,50,53]. Martcheva studied how the pathogen load affects the population-level prevalence of HIV and found that a medication-mediated decrease in viral load increases the population-level prevalence of HIV [43].…”

Section: Introductionmentioning

confidence: 99%

An immuno-eco-epidemiological model of competition

Bhattacharya

Martcheva

2016

Journal of Biological Dynamics

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This paper introduces a novel immuno-eco-epidemiological model of competition in which one of the species is affected by a pathogen. The infected individuals from species one are structured by timesince-infection and the within-host dynamics of the pathogen and the immune response is also modelled. A novel feature of the model is the impact of the species two numbers on the ability of species one to mount an immune response. The within-host model has three equilibria: an extinction equilibrium, pathogen-only equilibrium and pathogen and immune response equilibrium which exists if the immune response reproduction number R 0 > 1. The extinction equilibrium is always unstable, the pathogen-only equilibrium is stable if R 0 < 1, and the coexistence equilibrium is stable whenever it exists. The between-host competition model has six equilibria: an extinction equilibrium, three disease-free equilibria: species oneonly equilibrium, species two-only equilibrium and a disease-free species coexistence equilibrium. There are also two disease-present equilibria: species one-only disease equilibrium and disease coexistence equilibrium. The existence and stability of these equilibria are governed by six reproduction numbers. Results show that for a nonfatal disease, the disease coexistence equilibrium is stable whenever it exists. ARTICLE HISTORY

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Section: Introductionmentioning

confidence: 99%

An immuno-eco-epidemiological model of competition

Bhattacharya

Martcheva

2016

Journal of Biological Dynamics

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“…This framework allows one to explicitly determine parameters of the between-host model from the behaviour of the within-host model-and hence predict the transmission consequences of waning immunity. Previous studies have used nested models to link within-host and epidemiological characteristics to study the relationship between transmission and virulence (Sasaki & Iwasa 1991;Antia et al 1994;Ganusov et al 2002;Gilchrist & Sasaki 2002;André et al 2003;Krakauer & Komarova 2003;Alizon & Van Baalen 2005;Gilchrist & Coombs 2006;Read & Keeling 2006;Coombs et al 2007), while other studies have developed immunoepidemiological models, where the classes of hosts are delineated by immune or infection status (Kostova 2005;Vickers & Osgood 2007;Cornell et al 2008;Mitchell et al 2008). However, with the exception of a select few (e.g.…”

Section: Introductionmentioning

confidence: 99%

Implications of vaccination and waning immunity

Heffernan

Keeling

2009

Proc. R. Soc. B.

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For infectious diseases where immunization can offer lifelong protection, a variety of simple models can be used to explain the utility of vaccination as a control method. However, for many diseases, immunity wanes over time and is subsequently enhanced (boosted) by asymptomatic encounters with the infection. The study of this type of epidemiological process requires a model formulation that can capture both the withinhost dynamics of the pathogen and immune system as well as the associated population-level transmission dynamics. Here, we parametrize such a model for measles and show how vaccination can have a range of unexpected consequences as it reduces the natural boosting of immunity as well as reducing the number of naive susceptibles. In particular, we show that moderate waning times (40-80 years) and high levels of vaccination (greater than 70%) can induce large-scale oscillations with substantial numbers of symptomatic cases being generated at the peak. In addition, we predict that, after a long disease-free period, the introduction of infection will lead to far larger epidemics than that predicted by standard models. These results have clear implications for the long-term success of any vaccination campaign and highlight the need for a sound understanding of the immunological mechanisms of immunity and vaccination.

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“…This is exemplified by even early examples of these models, such as Kostova [34], which demonstrated population-level disease persistence even when individual immune responses are able to clear infection and result in immunity. A second example is the population level persistence of virus, even when the between host reproduction number is less than 1, as shown by Feng et al [22].…”

Section: Discussionmentioning

confidence: 97%

“…The models can show the impact of the individual immune dynamics on populationlevel transmission of disease. Tucknell [57] and Kostova [34] introduced some of the first immunoepidemiological models where the epidemiological component is a network. Kostova linked a network of n within-host models and showed that even if the immune response clears the infection in each individual when isolated, while these individuals are in a network, the pathogen persists in each one of them and on a "population level".…”

Section: A Network Epidemic Modelsmentioning

confidence: 99%

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Coupling Within-Host and Between-Host Infectious Diseases Models

Martcheva

Tuncer

Mary

2015

BIOMATH

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Abstract-Biological processes occur at distinct but interlinked scales of organization. Yet, mathematical models are often focused on a single scale. Recently, there has been a significant interest in creating and using models that link the within-host dynamics and population level dynamics of infectious diseases. These types of multi-scale models, called immuno-epidemiological models, fall in four categories, dependent on the type of the epidemiological component of the model: network or individual based models (IBM), "nested" agesince-infection structured models, ordinary differential equation (ODE) models, and "size-structured" models. Immuno-epidemiological multi-scale models have been used to address a variety of questions, including what is the impact of within-host dynamics on population-level quantities such as reproduction number and prevalence, as well as questions related to evolution of the pathogen or co-evolution of the pathogen and the host. Here we review the literature on immuno-epidemiological modeling as well as the main insights these models have created.

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Persistence of viral infections on the population level explained by an immunoepidemiological model

Cited by 25 publications

References 8 publications

An immuno-eco-epidemiological model of competition

An immuno-eco-epidemiological model of competition

Implications of vaccination and waning immunity

Coupling Within-Host and Between-Host Infectious Diseases Models

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