Article ID: CBB546389082

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

unapi

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
Simonutti, Luisa
Zizek, Slavoj
Alchon, Suzanne Austin
Armocida, Giuseppe
Bauer, Susanne
Bretelle-Establet, Florence
Journals
Laboratorio dell'ISPF
Centaurus: International Magazine of the History of Mathematics, Science, and Technology
Mefisto: Rivista di medicina, filosofia, storia
Medicina Historica
Journal of Global History
Medicina nei Secoli - Arte e Scienza
Publishers
Polity Press
Franco Angeli
Springer
University of California Press
University of New Mexico Press
Vanderbilt University Press
Concepts
Epidemics
Medicine and society
Coronavirus disease 2019 (COVID-19)
Public health
Medicine
Pandemics
People
Andrea Verga
Time Periods
21st century
20th century, late
19th century
20th century
16th century
Early modern
Places
Soviet Union
China
European Union
North America
South America
London (England)
Institutions
World Health Organization (WHO)
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