Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Quantitative Sciences, Flatiron Health, New York, NY, USA.
Eur J Epidemiol. 2020 Aug;35(8):727-729. doi: 10.1007/s10654-020-00661-0. Epub 2020 Jul 17.
Since the onset of the COVID-19 pandemic, countless disease prediction models have emerged, shaping the focus of news media, policymakers, and broader society. We reviewed the accuracy of forecasts made during prior twenty-first century epidemics, namely SARS, H1N1, and Ebola. We found that while disease prediction models were relatively nascent as a research focus during SARS and H1N1, for Ebola, numerous such forecasts were published. We found that forecasts of deaths for Ebola were often far from the eventual reality, with a strong tendency to over predict. Given the societal prominence of these models, it is crucial that their uncertainty be communicated. Otherwise, we will be unaware if we are being falsely lulled into complacency or unjustifiably shocked into action.
自 COVID-19 大流行以来，出现了无数疾病预测模型，这些模型成为了新闻媒体、政策制定者和更广泛的社会关注的焦点。我们回顾了 21 世纪之前发生的 SARS、H1N1 和埃博拉等疫情期间做出的预测的准确性。我们发现，虽然疾病预测模型在 SARS 和 H1N1 期间作为一个研究重点还相对较新，但在埃博拉疫情期间，已经发布了许多此类预测。我们发现，埃博拉死亡人数的预测往往与实际情况相去甚远，存在强烈的高估趋势。鉴于这些模型在社会上的重要性，必须要对其不确定性进行沟通。否则，我们将无法确定自己是否被错误地安抚而自满，或者是否被不合理地吓得采取行动。
