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Incorporating Social Determinants of Health into Modelling of COVID-19 and other Infectious Diseases: A Baseline Socio-economic Compartmental Model

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  • Galanis, Giorgos
  • Hanieh, Adam

Abstract

The role of socio-economic conditions has been largely implicit in mathematical epidemiological models. However, measures to address the current pandemic, specifically the relevant interventions proposing physical distancing, have highlighted how social determinants affect contagion and mortality dynamics of COVID-19. For the most part, these social determinants are not present in either policy discussions or in epidemiological models. We argue for the importance of incorporating social determinants of health into the modelling dynamics of COVID-19, and show how global variation of these conditions may be integrated into relevant models. In doing so, we also highlight a key political economy aspect of reproduction dynamics in epidemics.

Suggested Citation

  • Galanis, Giorgos & Hanieh, Adam, 2021. "Incorporating Social Determinants of Health into Modelling of COVID-19 and other Infectious Diseases: A Baseline Socio-economic Compartmental Model," Social Science & Medicine, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:socmed:v:274:y:2021:i:c:s027795362100126x
    DOI: 10.1016/j.socscimed.2021.113794
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    Cited by:

    1. Becchetti, Leonardo & Candio, Paolo & Salustri, Francesco, 2021. "Vaccine uptake and constrained decision making: The case of Covid-19," Social Science & Medicine, Elsevier, vol. 289(C).
    2. Fiske, Amelia & Galasso, Ilaria & Eichinger, Johanna & McLennan, Stuart & Radhuber, Isabella & Zimmermann, Bettina & Prainsack, Barbara, 2022. "The second pandemic: Examining structural inequality through reverberations of COVID-19 in Europe," Social Science & Medicine, Elsevier, vol. 292(C).
    3. Samad Noeiaghdam & Sanda Micula & Juan J. Nieto, 2021. "A Novel Technique to Control the Accuracy of a Nonlinear Fractional Order Model of COVID-19: Application of the CESTAC Method and the CADNA Library," Mathematics, MDPI, vol. 9(12), pages 1-26, June.
    4. Michele Tizzoni & Elaine O. Nsoesie & Laetitia Gauvin & Márton Karsai & Nicola Perra & Shweta Bansal, 2022. "Addressing the socioeconomic divide in computational modeling for infectious diseases," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    5. Galanis, Giorgos & Georgiadis, Andreas, 2024. "Socioeconomic conditions and contagion dynamics of the COVID-19 pandemic with and without mitigation measures: Evidence from 185 countries," World Development, Elsevier, vol. 175(C).

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