Strategies for mitigating an influenza pandemic.

Strategies for mitigating an influenza pandemic.
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减轻流感大流行的策略。

DOI:
10.1038/nature04795
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发表时间:
2006-07-27
期刊:
影响因子:
64.8
通讯作者:
Burke DS
Burke DS
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Ferguson NM;Cummings DA;Fraser C;Cajka JC;Cooley PC;Burke DS

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潜在流感大流行的流行病学数值模型表明,没有单一的灵丹妙药可以控制疫情的爆发,但多种方法的结合可以减少传播并挽救许多生命。边境限制不太可能产生太大影响,在一个国家内限制旅行对流行病在该国蔓延的影响微乎其微。这些模型预测,英国的大流行将在第一例出现后的两到三个月内达到顶峰,并在4个月内结束。它还表明,疫苗需要在大流行开始后两个月内提供,才能在降低感染率方面产生重大影响。这意味着疫苗需要提前储存才能有效。本文的在线版本(doi:10.1038/nature04795)包含补充材料,可供授权用户使用。制定减轻新流感大流行严重程度的战略现在是全球公共卫生的首要优先事项。流感预防和遏制战略可根据抗病毒、疫苗和非药物(病例隔离、家庭隔离、学校或工作场所关闭、旅行限制)措施等大类加以考虑。数学模型是探索干预策略的复杂图景和量化不同选择的潜在成本和收益的有力工具。本文以英国和美国为例,采用大规模流行病模拟来研究在对新型流感爆发的初步控制失败时的干预方案。我们发现,除非有效性超过99%,否则边境限制和/或国内旅行限制不太可能将传播延迟2-3周以上。在大流行高峰期关闭学校可将峰值发病率降低高达40%,但对总体发病率影响不大,而如果可行,病例隔离或家庭隔离可能会产生重大影响。治疗临床病例可以减少传播,但前提是在出现症状的一天内给予抗病毒药物。如果为50%的人口提供足够的药物,以家庭为基础的预防加上被动关闭学校,可将临床发病率降低40-50%。更广泛的预防将在后勤上更具挑战性,但可能会将发病率降低75%以上。在大流行之前储存疫苗,即使效力较低,也可以显著降低发病率。如果未来大流行毒株的特征与过去大流行中看到的特征有很大不同,对政策有效性的估计就会改变。本文的在线版本(doi:10.1038/nature04795)包含补充材料,可供授权用户使用。
Numerical models of the epidemiology of a potential flu pandemic show there is no single magic bullet which can control the outbreak, but that a combination of approaches could reduce transmission and save many lives. Border restrictions are unlikely to have much effect and travel restrictions within one country would make very little difference to the spread of a pandemic within that country. The models predict that a pandemic in the United Kingdom would peak within two to three months of the first case, and be over within 4 months. It also shows that vaccines need to be available within two months of the start of a pandemic to have a big effect in reducing infection rates. That means that vaccines would need to be stockpiled in advance to be effective. The online version of this article (doi:10.1038/nature04795) contains supplementary material, which is available to authorized users. Development of strategies for mitigating the severity of a new influenza pandemic is now a top global public health priority. Influenza prevention and containment strategies can be considered under the broad categories of antiviral, vaccine and non-pharmaceutical (case isolation, household quarantine, school or workplace closure, restrictions on travel) measures. Mathematical models are powerful tools for exploring this complex landscape of intervention strategies and quantifying the potential costs and benefits of different options. Here we use a large-scale epidemic simulation to examine intervention options should initial containment of a novel influenza outbreak fail, using Great Britain and the United States as examples. We find that border restrictions and/or internal travel restrictions are unlikely to delay spread by more than 2–3 weeks unless more than 99% effective. School closure during the peak of a pandemic can reduce peak attack rates by up to 40%, but has little impact on overall attack rates, whereas case isolation or household quarantine could have a significant impact, if feasible. Treatment of clinical cases can reduce transmission, but only if antivirals are given within a day of symptoms starting. Given enough drugs for 50% of the population, household-based prophylaxis coupled with reactive school closure could reduce clinical attack rates by 40–50%. More widespread prophylaxis would be even more logistically challenging but might reduce attack rates by over 75%. Vaccine stockpiled in advance of a pandemic could significantly reduce attack rates even if of low efficacy. Estimates of policy effectiveness will change if the characteristics of a future pandemic strain differ substantially from those seen in past pandemics. The online version of this article (doi:10.1038/nature04795) contains supplementary material, which is available to authorized users.
DOI: 10.1002/sim.1912
发表时间: 2004-11-30
影响因子: 2
作者:
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DOI: 10.1126/science.1086616
发表时间: 2003-06-20
期刊: SCIENCE
影响因子: 56.9
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DOI: 10.3201/eid1011.040729
发表时间: 2004-11
影响因子: 11.8
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通讯作者: World Health Organization Working Group on International and Community Transmission of SARS
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发表时间: 2004-10-19
影响因子: 11.1
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通讯作者: Geisel, T
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发表时间: 2001-10-26
期刊: SCIENCE
影响因子: 56.9
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