Manheim David
David Manheim, PhD, is an independent researcher, Silver Spring, Maryland.
Health Secur. 2018 Nov/Dec;16(6):381-390. doi: 10.1089/hs.2018.0039. Epub 2018 Nov 29.
The central argument in this article is that the probability of very large natural pandemics is more uncertain than either previous analyses or the historical record suggest. In public health and health security analyses, global catastrophic biological risks (GCBRs) have the potential to cause "sudden, extraordinary, widespread disaster," with "tens to hundreds of millions of fatalities." Recent analyses focusing on extreme events presume that the most extreme natural events are less likely than artificial sources of GCBRs and should receive proportionately less attention. These earlier analyses relied on an informal Bayesian analysis of naturally occurring GCBRs in the historical record and conclude that the near absence of such events demonstrates that they are rare. This ignores key uncertainties about both selection biases inherent in historical data and underlying causes of the nonstationary risk. The uncertainty is addressed here by first reconsidering the assumptions in earlier Bayesian analyses, then outlining a more complete analysis accounting for several previously omitted factors. Finally, relationships are suggested between available evidence and the uncertain question at hand, allowing more rigorous future estimates.
本文的核心观点是,大规模自然疫情大流行的可能性比以往分析或历史记录所显示的更具不确定性。在公共卫生和卫生安全分析中,全球灾难性生物风险(GCBRs)有可能引发“突然、异常、广泛的灾难”,造成“数亿人死亡”。最近针对极端事件的分析假定,最极端的自然事件比人为造成的全球灾难性生物风险源可能性更小,因而应得到相对较少的关注。这些早期分析依赖于对历史记录中自然发生的全球灾难性生物风险进行非正式贝叶斯分析,并得出结论称,此类事件几乎不存在表明它们很罕见。这忽略了历史数据中固有选择偏差以及非平稳风险潜在原因的关键不确定性。本文通过首先重新审视早期贝叶斯分析中的假设来解决这一不确定性,然后概述一个更全面的分析,该分析考虑了几个先前被遗漏的因素。最后,提出了现有证据与手头不确定问题之间的关系,以便未来能进行更严谨的估计。