Non-Epistemic Factors in Epidemiological Models. The Case of Mortality Data

Mefisto 1 (5):65-78 (2021)
  Copy   BIBTEX

Abstract

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.

Other Versions

No versions found

Links

PhilArchive

External links

  • This entry has no external links. Add one.
Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

Analytics

Added to PP
2021-07-27

Downloads
417 (#68,491)

6 months
94 (#66,549)

Historical graph of downloads
How can I increase my downloads?

Author Profiles

Elisabetta Lalumera
University of Bologna
M. Cristina Amoretti
Università degli Studi di Genova

Citations of this work

No citations found.

Add more citations

References found in this work

No references found.

Add more references