ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2022
Compositional modelling of immune response and virus transmission dynamics.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- A rule-based multiscale model of hepatic stellate cell plasticity: Critical role of the inactivation loop in fibrosis progression.PLoS computational biology · 2024Article
- Quantification of heterogeneity in human CD8Frontiers in immunology · 2024Article
- Modulating Immune Response in Viral Infection for Quantitative Forecasts of Drug Efficacy.Pharmaceutics · 2023Review
- The Royal Society RAMP modelling initiative.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- Technical challenges of modelling real-life epidemics and examples of overcoming these.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- Modelling herd immunity requirements in Queensland: impact of vaccination effectiveness, hesitancy and variants of SARS-CoV-2.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
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Registered trials
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