All models are wrong, but some are useful

Mathematical models at the time of Covid-19

Bibliographic Data

ID19576844
AuthorsRoberta Buiani (0000-0002-8589-2911, corresponding author)
Year2021
Volume07
Issue01
Pages115-130
Publication date2021-01-01
Open AccessYes
TypeARTICLE
VenuePunctum International Journal of Semiotics (JOURNAL)
Journal identifiersISSN: 2459-2943 • E-ISSN: 2459-2943
PublisherHellenic Semiotic Society (PUBLISHER • GR)
DOI10.18680/hss.2021.0007
OpenAlexW3209609104
LanguageEN
Citations received1
References cited4

Epidemiological models have been crucial tools throughout all stages of the 2020-21 Coronavirus pandemic: using promptly available or historical data, they have studied and tried to anticipate its progression, providing valuable guidelines for public health officials, policymakers, and other medical and non-medical audiences. While useful, models are not designed to be infallible, and for this reason, they have been frequently subject to criticism. There is a discrepancy between what models do and how they are presented and perceived. Several juxtaposing factors, including current beliefs about scientific reliability, the role of quantification, and the epistemic values grounding the field, are at the core of this discrepancy. While scientific literacy may play a role in addressing this discrepancy, analyzing and becoming better aware of these factors may suggest long-term strategies to address, acknowledge, and communicate the pandemic’s inherent complexity and stochastic qualities

2019-20 coronavirus outbreak · Criticism · Data science · Economics · Epistemology · Management science · Pandemic · Political science · Positive economics · Public health · Computer Science · COVID-19 epidemiological studies · Law · Mathematics · Medicine · Psychology · Viral Infections and Outbreaks Research · Zoonotic diseases and public health

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