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Jointly Modelling Economics and Epidemiology to Support Public Policy Decisions for the COVID-19 Response: A Review of UK Studies


  • Ana Duarte

    (University of York)

  • Simon Walker

    (University of York)

  • Andrew Metry

    (University of Sheffield)

  • Ruth Wong

    (University of Sheffield)

  • Jasmina Panovska-Griffiths

    (University College London
    University of Oxford)

  • Mark Sculpher

    (University of York)


COVID-19 in the UK has had a profound impact on population health and other socially important outcomes, including on education and the economy. Although a range of evidence has guided policy, epidemiological models have been central. It is less clear whether models to support decision making have sought to integrate COVID-19 epidemiology with a consideration of broader health, wellbeing and economic implications. We report on a rapid review of studies seeking to integrate epidemiological and economic modelling to assess the impacts of alternative policies. Overall, our results suggest that few studies have explored broader impacts of different COVID-19 policies in the UK. Three studies looked only at health, capturing impacts on individuals with and without COVID-19, with various methods used to model the latter. Four models considered health and wider impacts on individuals’ economic outcomes, such as wages. However, these models made no attempt to consider the dynamic impacts on economic outcomes of others and the wider economy. The most complex analyses sought to link epidemiological and dynamic economic models. Studies compared a wide range of policies, although most were defined in general terms with minimal consideration of their granular specifications. There was minimal exploration of uncertainty, with no consideration in half the studies. Selecting appropriate models to inform decisions requires careful thought of factors relevant to the decision options under consideration such as the outcomes of interest, sectors likely to be impacted and causal pathways. In summary, better linking epidemiological and economic modelling would help to inform COVID-19 policy.

Suggested Citation

  • Ana Duarte & Simon Walker & Andrew Metry & Ruth Wong & Jasmina Panovska-Griffiths & Mark Sculpher, 2021. "Jointly Modelling Economics and Epidemiology to Support Public Policy Decisions for the COVID-19 Response: A Review of UK Studies," PharmacoEconomics, Springer, vol. 39(8), pages 879-887, August.
  • Handle: RePEc:spr:pharme:v:39:y:2021:i:8:d:10.1007_s40273-021-01045-2
    DOI: 10.1007/s40273-021-01045-2

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    References listed on IDEAS

    1. Simon Walker & Susan Griffin & Miqdad Asaria & Aki Tsuchiya & Mark Sculpher, 2019. "Striving for a Societal Perspective: A Framework for Economic Evaluations When Costs and Effects Fall on Multiple Sectors and Decision Makers," Applied Health Economics and Health Policy, Springer, vol. 17(5), pages 577-590, October.
    2. Cuñat, Alejandro & Zymek, Robert, 2022. "The (structural) gravity of epidemics," European Economic Review, Elsevier, vol. 144(C).
    3. Fabrizio Adriani, 2020. "Social distance, speed of containment, and crowding in/out in a network model of contagion," Discussion Papers 2020-10, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    4. Adriani, Fabrizio & Ladley, Dan, 2021. "Social distance, speed of containment and crowding in/out in a network model of contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 597-625.
    5. Rama Cont & Artur Kotlicki & Renyuan Xu, 2020. "Modelling COVID-19 contagion: risk assessment and targeted mitigation policies," Working Papers hal-02923033, HAL.
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