Article ID: CBB546389082

Non-epistemic factors in epidemiological models. The case of mortality data (2021)


The COVID-19 pandemic has made it especially visible that mortality data are a key component of epidemiological models, being a single indicator that provides information about various health aspects, such as disease prevalence and effectiveness of interventions, and thus enabling predictions on many fronts. In this paper, we illustrate the interrelation between facts and values in death statistics, by analyzing the rules for death certification issued by the World Health Organization. We show how the notion of the underlying cause of death can change in view of public health goals. This brings us to a general point about how non-epistemic factors, such as values and goals, are reflected in the choice of different measures in epidemiological models. We finally argue that this analysis is not only relevant from a theoretical point of view but also has important practical consequences.

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Authors & Contributors
Worboys, Michael
Condrau, Flurin
Noymer, Andrew Jonathan
Jarosz, Beth
Farquhar, Fiona
Linden, Stefanie Caroline
Centaurus: International Magazine of the History of Mathematics, Science, and Technology
Social History of Medicine
Medicina Historica
Mefisto: Rivista di medicina, filosofia, storia
History of Psychiatry
Journal of Global History
Vanderbilt University Press
University of California, Davis
University of California Press
University of New Mexico Press
Medicine and society
Coronavirus disease 2019 (COVID-19)
Public health
Time Periods
21st century
20th century, late
19th century
20th century
16th century
20th century, early
Great Britain
New England (U.S.)
Soviet Union
Georgia (Republic)
Sierra Leone
World Health Organization (WHO)

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