Summary 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. The bigger picture Just as war makes every citizen into an amateur geographer and tactician, a pandemic makes epidemiologists of us all. Instead of maps with colored pins, we have charts of exposure and death counts; people on the street argue about infection fatality rates and herd immunity the way they might have debated wartime strategies and alliances in the past. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has brought statistics and uncertainty assessment into public discourse to an extent rarely seen except in election season and the occasional billion-dollar lottery jackpot. In this paper, we reflect on our role as statisticians and epidemiologists and lay out some of the challenges that arise in measuring and communicating our uncertainty about the behavior of a never-before-seen infectious disease. We look at the problem from multiple directions, including the challenges of estimating the case fatality rate (i.e., proportion of individuals who will die from the disease), the rate of transmission from person to person, and even the number of cases circulating in the population at any time. We advocate for an approach that is more transparent about the limitations of statistical and mathematical models as representations of reality and suggest some ways to ensure better representation and communication of uncertainty in future public health emergencies. Characterizing and communicating uncertainty has been a signal challenge of the COVID-19 pandemic. This uncertainty has touched every aspect of the pandemic, from our understanding of case fatality rates, geographic patterns of infection, and variation in the rate of transmission between people and over time. In this paper, we discuss issues of statistical design, data collection, analysis, communication, and decision-making that have arisen in recent and ongoing studies of SARS-CoV-2, focusing on tools for assessment and propagation of uncertainty.
【초록키워드】 public health, SARS-CoV-2, coronavirus, pandemic, Immunity, COVID-19 pandemic, Variation, Infection, Transmission, Infectious disease, Research, death, Analysis, case fatality rates, acute respiratory syndrome, individual, Fatality rate, statistician, limitation, circulating, epidemiologist, approach, statistical, example, proportion, the disease, mathematical, 【제목키워드】 pandemic, accounting,