Accounting for Uncertainty During a Pandemic

TL;DR

This paper highlights the importance of accounting for uncertainty in statistical methods during a pandemic, emphasizing tools for assessment and communication to improve decision-making.

Contribution

It introduces practical statistical approaches for managing and propagating uncertainty in pandemic-related data analysis and decision processes.

Findings

Emphasizes the need for uncertainty quantification in pandemic data analysis

Provides examples illustrating statistical issues in coronavirus studies

Highlights tools for assessing and communicating uncertainty

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.