Compositional modelling of immune response and virus transmission dynamics
Waites, William and Cavaliere, Matteo and Danos, Vincent and Datta, Ruchira and Eggo, Rosalind M. and Hallett, Timothy B. and Manheim, David and Panovska-Griffiths, Jasmina and Russell, Timothy W. and Zarnitsyna, Veronika I. (2021) Compositional modelling of immune response and virus transmission dynamics. Other. arXiv.org, Ithaca, N.Y.. (https://arxiv.org/abs/2111.02510v1)
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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 don't 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.
ORCID iDs
Waites, William ORCID: https://orcid.org/0000-0002-7759-6805, Cavaliere, Matteo, Danos, Vincent, Datta, Ruchira, Eggo, Rosalind M., Hallett, Timothy B., Manheim, David, Panovska-Griffiths, Jasmina, Russell, Timothy W. and Zarnitsyna, Veronika I.;-
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Item type: Monograph(Other) ID code: 79584 Dates: DateEvent3 November 2021Published3 November 2021SubmittedSubjects: Medicine > Public aspects of medicine > Public health. Hygiene. Preventive Medicine
Science > Microbiology > Virology
Science > MathematicsDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 14 Feb 2022 12:25 Last modified: 11 Nov 2024 16:06 URI: https://strathprints.strath.ac.uk/id/eprint/79584