Learning transmission dynamics modelling of COVID-19 using comomodels
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:349 |
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| Enthalten in: |
Mathematical biosciences - 349(2022) vom: 15. Juli, Seite 108824 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
van der Vegt, Solveig A [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 15.06.2022 Date Revised 11.01.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.mbs.2022.108824 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a 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 | ||
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| 650 | 4 | |a Pedagogy | |
| 650 | 4 | |a Population dynamics | |
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| 700 | 1 | |a Creswell, Richard |e verfasserin |4 aut | |
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| 700 | 1 | |a Lei, Chon Lok |e verfasserin |4 aut | |
| 700 | 1 | |a Gavaghan, David |e verfasserin |4 aut | |
| 700 | 1 | |a Lambert, Ben |e verfasserin |4 aut | |
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