swMATH ID: 42919
Software Authors: van der Vegt, Solveig A.; Dai, Liangti; Bouros, Ioana; Farm, Hui Jia; Creswell, Richard; Dimdore-Miles, Oscar; Cazimoglu, Idil; Bajaj, Sumali; Hopkins, Lyle; Seiferth, David; Cooper, Fergus; Lei, Chon Lok; Gavaghan, David; Lambert, Ben
Description: Learning transmission dynamics modelling of COVID-19 using comomodels. 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 extsf{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 extsf{R} Markdown vignettes.
Homepage: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9077823/
Source Code:  https://github.com/Como-DTC-Collaboration/como-models
Dependencies: R
Keywords: epidemiology; COVID-19; population dynamics; pedagogy; compartmental models; infectious disease modelling
Related Software: Plotly; R Markdown; ggplot2; R
Cited in: 1 Document

Cited in 1 Serial

1 Mathematical Biosciences

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