Mathematical model of the antibody response to hepatitis B vaccines: Implications for reduced schedules

Wilson, J. N.; Nokes, D. James; Medley, Graham F.

doi:10.1016/j.vaccine.2007.01.012

Cited by 19 publications

(25 citation statements)

References 27 publications

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“…When examining the maximum rate of antibody production, there was slight variability between patients, ranging from 0.57-1.93 year -1 . In studies using dynamic modeling, the highest rates of antibody production have been observed after vaccination among immunocompetent populations, with estimates around 0.94 per day [28]. These rates are much lower during clearance of acute infection at 0.96-1.32 per month, while the lower bounds of these estimates are strongly associated with low virus production [14].…”

Section: Discussionmentioning

confidence: 99%

Development of anti-hepatitis B surface (HBs) antibodies after HBs antigen loss in HIV-hepatitis B virus co-infected patients

Boyd

Canini

Gozlan

et al. 2017

Journal of Clinical Virology

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Section: Discussionmentioning

confidence: 99%

Development of anti-hepatitis B surface (HBs) antibodies after HBs antigen loss in HIV-hepatitis B virus co-infected patients

Boyd

Canini

Gozlan

et al. 2017

Journal of Clinical Virology

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“…Age-related development of schistosome infection and antibody responses were modelled using a set of differential equations, using a similar framework to earlier models of helminth immunity [11], [20], [40] and immune memory development [41], [42]. Two different structures for the immune response were explored: one with only plasma cells and the other including both plasma cell and memory B cell populations.…”

Section: Methodsmentioning

confidence: 99%

Explaining Observed Infection and Antibody Age-Profiles in Populations with Urogenital Schistosomiasis

et al. 2011

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Urogenital schistosomiasis is a tropical disease infecting more than 100 million people in sub-Saharan Africa. Individuals in endemic areas endure repeated infections with long-lived schistosome worms, and also encounter larval and egg stages of the life cycle. Protective immunity against infection develops slowly with age. Distinctive age-related patterns of infection and specific antibody responses are seen in endemic areas, including an infection ‘peak shift’ and a switch in the antibody types produced. Deterministic models describing changing levels of infection and antibody with age in homogeneously exposed populations were developed to identify the key mechanisms underlying the antibody switch, and to test two theories for the slow development of protective immunity: that (i) exposure to dying (long-lived) worms, or (ii) experience of a threshold level of antigen, is necessary to stimulate protective antibody. Different model structures were explored, including alternative stages of the life cycle as the main antigenic source and the principal target of protective antibody, different worm survival distributions, antigen thresholds and immune cross-regulation. Models were identified which could reproduce patterns of infection and antibody consistent with field data. Models with dying worms as the main source of protective antigen could reproduce all of these patterns, but so could some models with other continually-encountered life stages acting as the principal antigen source. An antigen threshold enhanced the ability of the model to replicate these patterns, but was not essential for it to do so. Models including either non-exponential worm survival or cross-regulation were more likely to be able to reproduce field patterns, but neither of these was absolutely required. The combination of life cycle stage stimulating, and targeted by, antibody was found to be critical in determining whether models could successfully reproduce patterns in the data, and a number of combinations were excluded as being inconsistent with field data.

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“…These and other animal models could be alternatives to chimpanzees for investigating the effects of candidates drugs and vaccines against HCV (Bukh, 2012; chimpanzees are endangered species and now cannot be used for animal experiments). On the other hand, mathematical modeling of the immune response against HBV in patients has estimated the contribution of the host response for viral clearance (Ciupe et al, 2007a,b), and the optimal vaccination schedule (Gesemann and Scheiermann, 1995; Wilson et al, 2007). Taken together, the combination of a small animal model and mathematical modeling can overcome the ethical and financial limitations of clinical trials and help develop new effective therapies against HBV and HCV.…”

Section: Quantification Of Virus Infection Dynamicsmentioning

confidence: 99%

Quantification of viral infection dynamics in animal experiments

Iwami¹,

Koizumi²,

Ikeda³

et al. 2013

Front. Microbiol.

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Analyzing the time-course of several viral infections using mathematical models based on experimental data can provide important quantitative insights regarding infection dynamics. Over the past decade, the importance and significance of mathematical modeling has been gaining recognition among virologists. In the near future, many animal models of human-specific infections and experimental data from high-throughput techniques will become available. This will provide us with the opportunity to develop new quantitative approaches, combining experimental and mathematical analyses. In this paper, we review the various quantitative analyses of viral infections and discuss their possible applications.

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Mathematical model of the antibody response to hepatitis B vaccines: Implications for reduced schedules

Cited by 19 publications

References 27 publications

Development of anti-hepatitis B surface (HBs) antibodies after HBs antigen loss in HIV-hepatitis B virus co-infected patients

Development of anti-hepatitis B surface (HBs) antibodies after HBs antigen loss in HIV-hepatitis B virus co-infected patients

Explaining Observed Infection and Antibody Age-Profiles in Populations with Urogenital Schistosomiasis

Quantification of viral infection dynamics in animal experiments

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