Learning transmission dynamics modelling of COVID-19 using comomodels
Solveig A. van der Vegt, Liangti Dai, Ioana Bouros, Hui Jia Farm, Richard Creswell, Oscar Dimdore‐Miles, Idil Cazimoglu, Sumali Bajaj, Lyle Hopkins, David Seiferth, Fergus Cooper, Chon Lok Lei, David J. Gavaghan, Ben Lambert
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.