Journal article
Compositional modelling of immune response and virus transmission dynamics
- 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’.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 4.6MB, Terms of use)
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- Publisher copy:
- 10.1098/rsta.2021.0307
Authors
+ Medical Research Council
More from this funder
- Funder identifier:
- https://ror.org/03x94j517
- Grant:
- MR/V027956/1
- Publisher:
- The Royal Society
- Journal:
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences More from this journal
- Volume:
- 380
- Issue:
- 2233
- Pages:
- 20210307
- Article number:
- 20210307
- Publication date:
- 2022-08-15
- Acceptance date:
- 2022-03-16
- DOI:
- EISSN:
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1471-2962
- ISSN:
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1364503X, 1364-503X
- Language:
-
English
- Keywords:
- Pubs id:
-
1276198
- Local pid:
-
pubs:1276198
- Source identifiers:
-
3805706
- Deposit date:
-
2026-02-27
- ARK identifier:
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Terms of use
- Copyright date:
- 2022
- Licence:
- CC Attribution (CC BY)
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