聚合人类判断：2019年冠状病毒病传播、负担及预防措施的概率预测
Aggregating Human Judgment Probabilistic Predictions of Coronavirus Disease 2019 Transmission, Burden, and Preventive Measures.
作者信息
Codi Allison, Luk Damon, Braun David, Cambeiro Juan, Besiroglu Tamay, Chen Eva, de Cesaris Luis Enrique Urtubey, Bocchini Paolo, McAndrew Thomas
机构信息
College of Health, Lehigh University, Bethlehem, Pennsylvania, USA.
Department of Psychology, College of Arts and Sciences, Lehigh University, Bethlehem, Pennsylvania, USA.
出版信息
Open Forum Infect Dis. 2022 Jul 25;9(8):ofac354. doi: 10.1093/ofid/ofac354. eCollection 2022 Aug.
Aggregated human judgment forecasts for coronavirus disease 2019 (COVID-19) targets of public health importance are accurate, often outperforming computational models. Our work shows that aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as a tool to aid public health decision making during outbreaks.
针对具有公共卫生重要性的2019冠状病毒病（COVID-19）目标的汇总人类判断预测是准确的，通常优于计算模型。我们的研究表明，针对传染源的汇总人类判断预测及时、准确且具有适应性，可作为疫情期间辅助公共卫生决策的工具。
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