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

Research output: Contribution to journalArticle

Abstract / Description of output

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 languageEnglish
Article number20220179
Pages (from-to)1-5
Number of pages5
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume380
Issue number2233
Early online date15 Aug 2022
DOIs
Publication statusPublished - 3 Oct 2022

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