Technical challenges of modelling real-life epidemics and examples of overcoming these

J. Panovska-Griffiths; W. Waites; G. J. Ackland

doi:10.1098/rsta.2022.0179

Technical challenges of modelling real-life epidemics and examples of overcoming these

J. Panovska-Griffiths^*, W. Waites, G. J. Ackland

^*Corresponding author for this work

School of Physics and Astronomy

Research output: Contribution to journal › Article

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the importance of mathematical modelling in informing and advising policy decision-making. Effective practice of mathematical modelling has challenges. These can be around the technical modelling framework and how different techniques are combined, the appropriate use of mathematical formalisms or computational languages to accurately capture the intended mechanism or process being studied, in transparency and robustness of models and numerical code, in simulating the appropriate scenarios via explicitly identifying underlying assumptions about the process in nature and simplifying approximations to facilitate modelling, in correctly quantifying the uncertainty of the model parameters and projections, in taking into account the variable quality of data sources, and applying established software engineering practices to avoid duplication of effort and ensure reproducibility of numerical results. Via a collection of 16 technical papers, this special issue aims to address some of these challenges alongside showcasing the usefulness of modelling as applied in this pandemic.

Original language	English
Article number	20220179
Pages (from-to)	1-5
Number of pages	5
Journal	Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume	380
Issue number	2233
Early online date	15 Aug 2022
DOIs	https://doi.org/10.1098/rsta.2022.0179
Publication status	Published - 3 Oct 2022

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rsta.2022.0179Final published version, 346 KBLicence: Creative Commons: Attribution (CC-BY)

Rapid Assistance in Modelling the Pandemic (RAMP - Edinburgh central admin)
Ackland, G.
UK central government bodies/local authorities, health and hospital authorities
1/06/20 → 30/11/21
Project: Research

Cite this

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abstract = "The coronavirus disease 2019 (COVID-19) pandemic has highlighted the importance of mathematical modelling in informing and advising policy decision-making. Effective practice of mathematical modelling has challenges. These can be around the technical modelling framework and how different techniques are combined, the appropriate use of mathematical formalisms or computational languages to accurately capture the intended mechanism or process being studied, in transparency and robustness of models and numerical code, in simulating the appropriate scenarios via explicitly identifying underlying assumptions about the process in nature and simplifying approximations to facilitate modelling, in correctly quantifying the uncertainty of the model parameters and projections, in taking into account the variable quality of data sources, and applying established software engineering practices to avoid duplication of effort and ensure reproducibility of numerical results. Via a collection of 16 technical papers, this special issue aims to address some of these challenges alongside showcasing the usefulness of modelling as applied in this pandemic.",

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Technical challenges of modelling real-life epidemics and examples of overcoming these

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Rapid Assistance in Modelling the Pandemic (RAMP - Edinburgh central admin)

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