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2
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3
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Health Secur. 2017 Jul/Aug;15(4):329-330. doi: 10.1089/hs.2017.0049. Epub 2017 Jul 26.
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If a Global Catastrophic Biological Risk Materializes, at What Stage Will We Recognize It?如果全球灾难性生物风险成为现实,我们将在哪个阶段认识到它?
Health Secur. 2017 Jul/Aug;15(4):331-334. doi: 10.1089/hs.2017.0037. Epub 2017 Jul 26.
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Human Agency and Global Catastrophic Biorisks.人类行为与全球灾难性生物风险
Health Secur. 2017 Jul/Aug;15(4):335-336. doi: 10.1089/hs.2017.0044. Epub 2017 Jul 26.
6
The Pathogenic Potential of a Microbe.微生物的致病潜力
mSphere. 2017 Feb 22;2(1). doi: 10.1128/mSphere.00015-17. eCollection 2017 Jan-Feb.
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Toward Integrated DoD Biosurveillance: Assessment and Opportunities.迈向国防部综合生物监测:评估与机遇
Rand Health Q. 2014 Dec 1;3(4):9. eCollection 2014 Winter.
8
Evolution of Bacterial Pathogens Within the Human Host.人类宿主内细菌病原体的演变
Microbiol Spectr. 2016 Feb;4(1). doi: 10.1128/microbiolspec.VMBF-0017-2015.
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Planning for the Next Global Pandemic.为下一次全球大流行做准备。
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Existential risks: exploring a robust risk reduction strategy.存在性风险:探索一种稳健的风险降低策略。
Sci Eng Ethics. 2015 Jun;21(3):541-54. doi: 10.1007/s11948-014-9559-3. Epub 2014 Jun 3.

质疑自然大流行风险的评估。

Questioning Estimates of Natural Pandemic Risk.

作者信息

Manheim David

机构信息

David Manheim, PhD, is an independent researcher, Silver Spring, Maryland.

出版信息

Health Secur. 2018 Nov/Dec;16(6):381-390. doi: 10.1089/hs.2018.0039. Epub 2018 Nov 29.

DOI:10.1089/hs.2018.0039
PMID:30489178
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6306648/
Abstract

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.

摘要

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。