The impact of mass gatherings and holiday traveling on the course of an influenza pandemic: a computational model.
The impact of mass gatherings and holiday traveling on the course of an influenza pandemic: a computational model.
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DOI：
10.1186/1471-2458-10-778
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发表时间：
2010-12-21
影响因子：
4.5
通讯作者：
Lee BY
中科院分区：
文献类型：
--
作者：
Shi P;Keskinocak P;Swann JL;Lee BY
在2009年H1N1流感大流行期间，人们对大规模公众集会和旅行对大流行的潜在负面影响表示关切。更好地了解社会混合模式的时间变化的潜在影响，可以帮助政府官员确定是否以及何时取消大型公共集会，或在流行病期间实施区域旅行限制、强制措施或监测。我们使用来自格鲁吉亚州的详细数据开发了一个计算机模拟模型，以探索社会混合和接触模式的各种变化，代表大规模集会和假日旅行，可能会影响流感大流行的过程。探讨了各种情景与不同的组合的长度的大规模集会或旅行期间（范围：0.5至5天），人口的比例参加的大规模集会活动或旅行（范围：1%至50%），和初始繁殖数R0（1.3，1.5，1.8）。在疫情高峰前10天内发生的群众聚集，可导致高峰流行率和总发病率相对增加高达10%，对当地社区和旅客家庭的影响可能更严重。假日旅游在某些情况下可能导致第二次疫情高峰。相反，大规模旅行或聚会在流行高峰期之前或之后发生时可能影响不大，例如，当初始R0 = 1.5时，比峰值早40天或晚20天以上。我们的研究结果表明，监测，推迟或取消大型公共集会可能是有道理的接近流行高峰，但不是在流行期间的早期或后期。流感活动也应密切监测，如果发生在流行率高的假期旅行时，可能会出现第二个高峰。
During the 2009 H1N1 influenza pandemic, concerns arose about the potential negative effects of mass public gatherings and travel on the course of the pandemic. Better understanding the potential effects of temporal changes in social mixing patterns could help public officials determine if and when to cancel large public gatherings or enforce regional travel restrictions, advisories, or surveillance during an epidemic. We develop a computer simulation model using detailed data from the state of Georgia to explore how various changes in social mixing and contact patterns, representing mass gatherings and holiday traveling, may affect the course of an influenza pandemic. Various scenarios with different combinations of the length of the mass gatherings or traveling period (range: 0.5 to 5 days), the proportion of the population attending the mass gathering events or on travel (range: 1% to 50%), and the initial reproduction numbers R0 (1.3, 1.5, 1.8) are explored. Mass gatherings that occur within 10 days before the epidemic peak can result in as high as a 10% relative increase in the peak prevalence and the total attack rate, and may have even worse impacts on local communities and travelers' families. Holiday traveling can lead to a second epidemic peak under certain scenarios. Conversely, mass traveling or gatherings may have little effect when occurring much earlier or later than the epidemic peak, e.g., more than 40 days earlier or 20 days later than the peak when the initial R0 = 1.5. Our results suggest that monitoring, postponing, or cancelling large public gatherings may be warranted close to the epidemic peak but not earlier or later during the epidemic. Influenza activity should also be closely monitored for a potential second peak if holiday traveling occurs when prevalence is high.
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影响因子：
4.3
作者：
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通讯作者：
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DOI：
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发表时间：
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影响因子：
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DOI：
10.1073/pnas.0601266103
发表时间：
2006-04-11
影响因子：
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DOI：
10.1073/pnas.0610941104
发表时间：
2007-05-01
影响因子：
11.1
作者：
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通讯作者：
Lipsitch, Marc