1. Learning transmission dynamics modelling of COVID-19 using comomodels.
- Author
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van der Vegt SA, Dai L, Bouros I, Farm HJ, Creswell R, Dimdore-Miles O, Cazimoglu I, Bajaj S, Hopkins L, Seiferth D, Cooper F, Lei CL, Gavaghan D, and Lambert B
- Subjects
- Humans, Learning, Models, Theoretical, COVID-19, Epidemics
- Abstract
The COVID-19 epidemic continues to rage in many parts of the world. In the UK alone, an array of mathematical models have played a prominent role in guiding policymaking. Whilst considerable pedagogical material exists for understanding the basics of transmission dynamics modelling, there is a substantial gap between the relatively simple models used for exposition of the theory and those used in practice to model the transmission dynamics of COVID-19. Understanding these models requires considerable prerequisite knowledge and presents challenges to those new to the field of epidemiological modelling. In this paper, we introduce an open-source R package, comomodels, which can be used to understand the complexities of modelling the transmission dynamics of COVID-19 through a series of differential equation models. Alongside the base package, we describe a host of learning resources, including detailed tutorials and an interactive web-based interface allowing dynamic investigation of the model properties. We then use comomodels to illustrate three key lessons in the transmission of COVID-19 within R Markdown vignettes., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)
- Published
- 2022
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