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家庭社区中的繁殖数、疫情传播与控制

Reproductive numbers, epidemic spread and control in a community of households.

作者信息

Goldstein E, Paur K, Fraser C, Kenah E, Wallinga J, Lipsitch M

机构信息

Harvard School of Public Health, Boston, MA 02115, USA.

出版信息

Math Biosci. 2009 Sep;221(1):11-25. doi: 10.1016/j.mbs.2009.06.002. Epub 2009 Jun 25.

Abstract

Many of the studies on emerging epidemics (such as SARS and pandemic flu) use mass action models to estimate reproductive numbers and the needed control measures. In reality, transmission patterns are more complex due to the presence of various social networks. One level of complexity can be accommodated by considering a community of households. Our study of transmission dynamics in a community of households emphasizes five types of reproductive numbers for the epidemic spread: household-to-household reproductive number, leaky vaccine-associated reproductive numbers, perfect vaccine reproductive number, growth rate reproductive number, and the individual reproductive number. Each of those carries different information about the transmission dynamics and the required control measures, and often some of those can be estimated from the data while others cannot. Simulations have shown that under certain scenarios there is an ordering for those reproductive numbers. We have proven a number of ordering inequalities under general assumptions about the individual infectiousness profiles. Those inequalities allow, for instance, to estimate the needed vaccine coverage and other control measures without knowing the various transmission parameters in the models. Along the way, we have also shown that in choosing between increasing vaccine efficacy and increasing coverage levels by the same factor, preference should go to efficacy.

摘要

许多关于新发流行病(如非典和大流行性流感)的研究使用群体作用模型来估计繁殖数和所需的控制措施。实际上,由于存在各种社会网络,传播模式更为复杂。考虑家庭群落可以解决一定程度的复杂性问题。我们对家庭群落中传播动态的研究强调了流行病传播的五种繁殖数类型:家庭间繁殖数、与泄漏疫苗相关的繁殖数、完美疫苗繁殖数、增长率繁殖数和个体繁殖数。每一种都携带了关于传播动态和所需控制措施的不同信息,并且通常其中一些可以从数据中估计出来,而另一些则无法估计。模拟表明,在某些情况下,这些繁殖数存在一种排序。我们在关于个体传染性特征的一般假设下证明了一些排序不等式。例如,这些不等式使得在不知道模型中各种传播参数的情况下,能够估计所需的疫苗覆盖率和其他控制措施。在此过程中,我们还表明,在以相同因子提高疫苗效力和提高覆盖率之间进行选择时,应优先选择效力。

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