National Institute of Public Health and the Environment, Bilthoven, The Netherlands.
Proc Biol Sci. 2012 Feb 7;279(1728):444-50. doi: 10.1098/rspb.2011.0913. Epub 2011 Jul 6.
Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic, genetic data of the pathogen. We present a likelihood-based framework to integrate these two data types, estimating probabilities of infection by taking weighted averages over the set of possible transmission trees. We test the approach by applying it to temporal, geographical and genetic data on the 241 poultry farms infected in an epidemic of avian influenza A (H7N7) in The Netherlands in 2003. We show that the combined approach estimates the transmission tree with higher correctness and resolution than analyses based on genetic or epidemiological data alone. Furthermore, the estimated tree reveals the relative infectiousness of farms of different types and sizes.
有关传染病传播树的知识可以为疾病动态提供有价值的见解。可以通过分析详细的流行病学数据（例如接触追踪），或者如果病原体在传染病过程中积累了足够的遗传多样性，来重建传播树。我们提出了一个基于似然的框架来整合这两种数据类型，通过对可能的传播树集合进行加权平均来估计感染的概率。我们通过将该方法应用于 2003 年在荷兰爆发的禽流感 A（H7N7）疫情中 241 个受感染家禽养殖场的时间、地理和遗传数据来检验该方法。结果表明，与基于遗传或流行病学数据的分析相比，综合方法估计的传播树具有更高的正确性和分辨率。此外，估计的树揭示了不同类型和规模的农场的相对传染性。
