Accounting for uncertainty during a pandemic.
Accounting for uncertainty during a pandemic.
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DOI：
10.1016/j.patter.2021.100310
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发表时间：
2021-08-13
期刊：
影响因子：
--
通讯作者：
Gelman A
中科院分区：
文献类型：
--
作者：
Zelner J;Riou J;Etzioni R;Gelman A
我们讨论了最近和正在进行的冠状病毒研究中出现的统计设计、数据收集、分析、交流和决策的几个问题，重点是评估和传播不确定性的工具。这篇论文并不是对研究文献的全面综述；相反，我们用例子来说明我们认为重要的统计点。正如战争使每个公民成为业余地理学家和战术家一样，流行病使我们所有人都成为流行病学家。我们用的不是带有彩色图钉的地图，而是暴露和死亡人数的图表；街上的人们争论感染死亡率和群体免疫力，就像他们过去可能辩论战时战略和联盟的方式一样。严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的大流行将统计数据和不确定性评估带入了公共话语，除了选举季节和偶尔出现的数十亿美元彩票大奖之外，这种程度是罕见的。在这篇文章中，我们反思了我们作为统计学家和流行病学家的角色，并列出了在衡量和传达我们对一种前所未见的传染病行为的不确定性时出现的一些挑战。我们从多个方向看待这一问题，包括估计病死率(即将死于该疾病的个人的比例)、人与人之间的传播率、甚至任何时候在人群中传播的病例数量的挑战。我们主张采取一种更透明的方法，让统计和数学模型作为现实的代表的局限性更加透明，并提出一些方法，以确保在未来的公共卫生突发事件中更好地表达和沟通不确定性。表征和传达不确定性一直是新冠肺炎大流行的一个信号挑战。这种不确定性触及了大流行的方方面面，从我们对病死率、感染的地理模式以及人与人之间的传播率随时间的变化的了解。在这篇文章中，我们讨论了在最近和正在进行的SARS-CoV-2研究中出现的统计设计、数据收集、分析、沟通和决策问题，重点是评估和传播不确定性的工具。
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. 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.
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影响因子：
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作者：
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DOI：
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发表时间：
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DOI：
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发表时间：
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期刊：
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER
影响因子：
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作者：
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通讯作者：
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