Department of Pure Mathematics and Mathematical Statistics, Winton Centre for Risk and Evidence Communication, University of Cambridge, Cambridge, United Kingdom.
PLoS One. 2021 May 5;16(5):e0250935. doi: 10.1371/journal.pone.0250935. eCollection 2021.
Throughout the COVID-19 pandemic, social and traditional media have disseminated predictions from experts and nonexperts about its expected magnitude. How accurate were the predictions of 'experts'-individuals holding occupations or roles in subject-relevant fields, such as epidemiologists and statisticians-compared with those of the public? We conducted a survey in April 2020 of 140 UK experts and 2,086 UK laypersons; all were asked to make four quantitative predictions about the impact of COVID-19 by 31 Dec 2020. In addition to soliciting point estimates, we asked participants for lower and higher bounds of a range that they felt had a 75% chance of containing the true answer. Experts exhibited greater accuracy and calibration than laypersons, even when restricting the comparison to a subset of laypersons who scored in the top quartile on a numeracy test. Even so, experts substantially underestimated the ultimate extent of the pandemic, and the mean number of predictions for which the expert intervals contained the actual outcome was only 1.8 (out of 4), suggesting that experts should consider broadening the range of scenarios they consider plausible. Predictions of the public were even more inaccurate and poorly calibrated, suggesting that an important role remains for expert predictions as long as experts acknowledge their uncertainty.
在整个 COVID-19 大流行期间，社交和传统媒体传播了专家和非专家对其预期规模的预测。与公众相比，专家——在相关领域拥有职业或角色的个人，如流行病学家和统计学家——的预测有多准确？我们在 2020 年 4 月对 140 名英国专家和 2086 名英国非专业人士进行了调查；所有受访者都被要求在 2020 年 12 月 31 日前对 COVID-19 的影响做出四项定量预测。除了征求点估计值外，我们还要求参与者提供他们认为有 75%的可能性包含真实答案的范围的下限和上限。专家的准确性和校准度都高于非专业人士，即使将比较范围限制在在一项计算能力测试中得分在前四分之一的非专业人士的子集中也是如此。即便如此，专家们还是大大低估了大流行的最终程度，而专家区间包含实际结果的预测平均值仅为 1.8（4 项预测中的 1.8），这表明专家们应该考虑拓宽他们认为合理的情景范围。公众的预测甚至更不准确，校准度也更差，这表明只要专家承认自己的不确定性，公众的预测仍然很重要。
