Germann Timothy C, Kadau Kai, Longini Ira M, Macken Catherine A
Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
Proc Natl Acad Sci U S A. 2006 Apr 11;103(15):5935-40. doi: 10.1073/pnas.0601266103. Epub 2006 Apr 3.
Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
近期,高致病性甲型流感病毒(H5N1)感染导致的人类死亡事件引发了人们对1917 - 1918年那样毁灭性大流行的担忧,倘若这种禽流感病毒进化到能够轻易在人际间传播的话。我们引入并使用了一个大规模随机模拟模型,来研究一种流感病毒大流行毒株在美国2.81亿人口中的传播情况,其中基本再生数R(0)取值范围为1.6至2.4。我们模拟了不同水平和组合的流感抗病毒药物、疫苗以及改变后的社会流动性(包括学校关闭和旅行限制)对疫情传播的时间和规模产生的影响。我们的模拟结果表明,在人口流动性高的情况下,在检测到疫情爆发后限制旅行可能只会略微延迟疫情的发展进程,而不会影响最终患病的人数。对于R(0) < 1.9,我们的模型表明,即使疫苗与流行毒株的匹配度不佳,但疫苗的快速生产和分发仍可显著减缓疾病传播,并将患病数量限制在人口的10%以内,特别是如果优先为儿童接种疫苗的话。或者,在有足够的接触者追踪和分发能力的情况下,在有针对性的预防策略中大规模部署数百万疗程的流感抗病毒药物,可能会控制住R(0)较低的新出现疫情。对于更高的R(0),我们预测需要综合多种策略(包括社会和医疗干预)才能对发病率实现类似的控制。