Accounting for uncertainty during a pandemic

Jon Zelner; Julien Riou; Ruth Etzioni; Andrew Gelman

doi:10.1016/j.patter.2021.100310

Accounting for uncertainty during a pandemic

Patterns (N Y). 2021 Aug 13;2(8):100310. doi: 10.1016/j.patter.2021.100310.

Authors

Jon Zelner¹, Julien Riou², Ruth Etzioni³, Andrew Gelman⁴

Affiliations

¹ Department of Epidemiology, Center of Social Epidemiology & Population Health, University of Michigan School of Public Health, Ann Arbor, MI, USA.
² Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
³ Fred Hutchinson Cancer Research Center, University of Washington, Seattle, WA, USA.
⁴ Department of Statistics and Department of Political Science, Columbia University, New York, NY, USA.

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.

Publication types

Review

Abstract

Publication types

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