Potter Gail E, Hens Niel
California Polytechnic State University, San Luis Obispo, CA, U.S.A., Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center, Seattle, WA, U.S.A.
J R Stat Soc Ser C Appl Stat. 2013 Aug 1;62(4):629-648. doi: 10.1111/rssc.12011.
Acute infectious diseases are transmitted over networks of social contacts. Epidemic models are used to predict the spread of emergent pathogens and compare intervention strategies. Many of these models assume equal probability of contact within mixing groups (homes, schools, etc.), but little work has inferred the actual contact network, which may influence epidemic estimates. We develop a penalized likelihood method to infer contact networks within households, a key area for disease transmission. Using egocentric surveys of contact behavior in Belgium, we estimate within-household contact networks for six different age compositions. Our estimates show dependency in contact behavior and vary substantively by age composition, with fewer contacts occurring in older households. Our results are relevant for epidemic models used to make policy recommendations.
急性传染病通过社会接触网络传播。流行病模型用于预测新出现病原体的传播并比较干预策略。这些模型中的许多都假设在混合群体（家庭、学校等）内接触的概率相等，但很少有研究推断实际的接触网络，而这可能会影响疫情估计。我们开发了一种惩罚似然方法来推断家庭内部的接触网络，这是疾病传播的一个关键领域。利用对比利时接触行为的自我中心调查，我们估计了六种不同年龄构成家庭内部的接触网络。我们的估计结果显示了接触行为中的依赖性，并且因年龄构成而有很大差异，老年家庭中的接触较少。我们的结果对于用于制定政策建议的流行病模型具有参考价值。
