Accounting for uncertainty during a pandemic

Jon Zelner, Julien Riou, Ruth Etzioni, Andrew Gelman

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

We discuss several issues of statistical design, data collection, analysis, communication, and decision-making that have arisen in recent and ongoing coronavirus studies, focusing on tools for assessment and propagation of uncertainty. This paper does not purport to be a comprehensive survey of the research literature; rather, we use examples to illustrate statistical points that we think are important.

Original languageEnglish (US)
Article number100310
JournalPatterns
Volume2
Issue number8
DOIs
StatePublished - Aug 13 2021
Externally publishedYes

Keywords

  • DSML 2: Proof-of-Concept: Data science output has been formulated, implemented, and tested for one domain/problem

ASJC Scopus subject areas

  • Decision Sciences(all)

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