Inference for Epidemics with Three Levels of Mixing: Methodology and Application to a Measles Outbreak
Inference for Epidemics with Three Levels of Mixing: Methodology and Application to a Measles Outbreak
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DOI：
10.1111/j.1467-9469.2010.00726.x
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发表时间：
2011-09-01
影响因子：
1
通讯作者：
O'Neill, Philip D.
中科院分区：
文献类型：
--
作者：
Britton, Tom;Kypraios, Theodore;O'Neill, Philip D.
定义了一个随机流行病模型，其中每个人都属于一个家庭，一个次级群体（通常是学校或工作场所），也是整个社区。此外，这三种环境中的传染性接触发生率可能不同。对于这个模型，我们考虑如何使用不同类型的数据来估计感染率参数，以了解什么可以和不能推断。除其他事项外，我们发现，时间数据可以是相当大的推论的好处相比，最终大小的数据，在数据的异质性程度可以有相当大的影响，推断非家庭传输，推断可以是实质性的不同，从一个模型中获得的只有两个层次的混合。我们通过分析德国Hagelloch麻疹暴发的高度详细的数据集来说明我们的研究结果。
A stochastic epidemic model is defined in which each individual belongs to a household, a secondary grouping (typically school or workplace) and also the community as a whole. Moreover, infectious contacts take place in these three settings according to potentially different rates. For this model, we consider how different kinds of data can be used to estimate the infection rate parameters with a view to understanding what can and cannot be inferred. Among other things we find that temporal data can be of considerable inferential benefit compared with final size data, that the degree of heterogeneity in the data can have a considerable effect on inference for non-household transmission, and that inferences can be materially different from those obtained from a model with only two levels of mixing. We illustrate our findings by analysing a highly detailed dataset concerning a measles outbreak in Hagelloch, Germany.