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The Statistical Challenges Of Modelling Covid-19

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  • Dolton, Peter

Abstract

In 2020–2021, the world has been gripped by a pandemic that no living person has ever known. The coronavirus pandemic is undoubtedly the greatest challenge the world has faced in over a generation. The imperative of statistical modelling is not only to manage the short-run crisis for the health services, but also to explain the pandemic’s course and establish the effectiveness of different policies, both non-pharmaceutical and with vaccines. This difficult task has been undertaken by the epidemiologists and others in the face of measurement data problems, behavioural complications and endogeneity issues. This paper proposes a simple taxonomy of the alternative different models and suggests how they may be used together to overcome limitations. This perspective may have important implications for how policy-makers cope with future waves or strains in the current pandemic, or future pandemics.

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  • Dolton, Peter, 2021. "The Statistical Challenges Of Modelling Covid-19," National Institute Economic Review, National Institute of Economic and Social Research, vol. 257, pages 46-82, August.
    • Handle: RePEc:cup:nierev:v:257:y:2021:i::p:46-82_5
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    Cited by:

    1. Carl Singleton & Alex Bryson & Peter Dolton & James Reade & Dominik Schreyer, 2022. "Economics lessons from sports during the COVID-19 pandemic," Chapters, in: Paul M. Pedersen (ed.), Research Handbook on Sport and COVID-19, chapter 2, pages 9-18, Edward Elgar Publishing.

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