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Comparative Study
. 2021 Aug 25;43(3):104.
doi: 10.1007/s40656-021-00457-9.

Epidemiological models and COVID-19: a comparative view

Affiliations
Comparative Study

Epidemiological models and COVID-19: a comparative view

Valeriano Iranzo et al. Hist Philos Life Sci. .

Abstract

Epidemiological models have played a central role in the COVID-19 pandemic, particularly when urgent decisions were required and available evidence was sparse. They have been used to predict the evolution of the disease and to inform policy-making. In this paper, we address two kinds of epidemiological models widely used in the pandemic, namely, compartmental models and agent-based models. After describing their essentials-some real examples are invoked-we discuss their main strengths and weaknesses. Then, on the basis of this analysis, we make a comparison between their respective merits concerning three different goals: prediction, explanation, and intervention. We argue that there are general considerations which could favour any of those sorts of models for obtaining the aforementioned goals. We conclude, however, that preference for particular models must be grounded case-by-case since additional contextual factors, as the peculiarities of the target population and the aims and expectations of policy-makers, cannot be overlooked.

Keywords: Agent-based models; COVID-19; Compartmental models; Decision-making; Epidemiology; Prediction.

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Conflict of interest statement

The authors have no conflict of interest or competing interests to declare.

References

    1. Adam D. Special report: The simulations driving the world’s response to COVID-19. Nature. 2020;580(7803):316–318. doi: 10.1038/d41586-020-01003-6. - DOI - PubMed
    1. Alagoz O, Sethi AK, Patterson BW, Churpek M, Safdar N. Effect of timing of and adherence to social distancing measures on COVID-19 Burden in the United States. Annals of Internal Medicine. 2020;174(1):50–57. doi: 10.7326/M20-4096. - DOI - PMC - PubMed
    1. Anderson RM, May RM. Directly transmitted infectious diseases: Control by vaccination. Science. 1982;215(4536):1053–1060. doi: 10.1126/science.7063839. - DOI - PubMed
    1. Auchincloss AH, Diez Roux AV. A new tool for epidemiology: The usefulness of dynamic-agent models in understanding place effects on health. American Journal of Epidemiology. 2008;168(1):1–8. doi: 10.1093/aje/kwn118. - DOI - PubMed
    1. Bansal S, Grenfell BT, Meyers LA. When individual behaviour matters: Homogeneous and network models in epidemiology. Journal of the Royal Society Interface. 2007;4(16):879–891. doi: 10.1098/rsif.2007.1100. - DOI - PMC - PubMed

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