The spread of awareness and its impact on epidemic outbreaks

The spread of awareness and its impact on epidemic outbreaks
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DOI:
10.1073/pnas.0810762106
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发表时间:
2009-04-21
影响因子:
11.1
通讯作者:
Jansen, Vincent A. A.
Jansen, Vincent A. A.
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Funk, Sebastian;Gilad, Erez;Jansen, Vincent A. A.

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当一种疾病在人群中爆发时,应对爆发的行为变化可能会改变传染源的进展。特别是,人们意识到在他们附近的疾病可以采取措施,以减少他们的易感性。即使没有提供关于疾病存在的集中信息,也可以通过第一手观察和口头传播来提高这种认识。为了了解这可能对疾病传播的影响,我们制定并分析了一个数学模型,用于在宿主人群中传播意识,然后将其与流行病学模型联系起来,让更多知情的宿主降低其易感性。我们发现,在一个混合良好的人群中,这可能会导致较低的爆发规模,但不影响流行阈值。然而,如果行为反应被视为在爆发附近产生的局部效应,它可以完全阻止疾病的传播,尽管只有在感染率低于阈值的情况下。我们发现,如果潜在感染事件的社会网络和个人交流的网络重叠,特别是如果网络具有高水平的聚类,则局部传播意识的影响会被放大。这些研究结果表明,在解释疾病参数以及预测未来疫情的命运方面都需要谨慎。
When a disease breaks out in a human population, changes in behavior in response to the outbreak can alter the progression of the infectious agent. In particular, people aware of a disease in their proximity can take measures to reduce their susceptibility. Even if no centralized information is provided about the presence of a disease, such awareness can arise through first-hand observation and word of mouth. To understand the effects this can have on the spread of a disease, we formulate and analyze a mathematical model for the spread of awareness in a host population, and then link this to an epidemiological model by having more informed hosts reduce their susceptibility. We find that, in a well-mixed population, this can result in a lower size of the outbreak, but does not affect the epidemic threshold. If, however, the behavioral response is treated as a local effect arising in the proximity of an outbreak, it can completely stop a disease from spreading, although only if the infection rate is below a threshold. We show that the impact of locally spreading awareness is amplified if the social network of potential infection events and the network over which individuals communicate overlap, especially so if the networks have a high level of clustering. These findings suggest that care needs to be taken both in the interpretation of disease parameters, as well as in the prediction of the fate of future outbreaks.