PRESTO, Japan Science and Technology Agency, Saitama, Japan.
J Theor Biol. 2011 Mar 7;272(1):123-30. doi: 10.1016/j.jtbi.2010.12.017. Epub 2010 Dec 17.
Empirical estimates of the incubation period of influenza A (H1N1-2009) have been limited. We estimated the incubation period among confirmed imported cases who traveled to Japan from Hawaii during the early phase of the 2009 pandemic (n=72). We addressed censoring and employed an infection-age structured argument to explicitly model the daily frequency of illness onset after departure. We assumed uniform and exponential distributions for the frequency of exposure in Hawaii, and the hazard rate of infection for the latter assumption was retrieved, in Hawaii, from local outbreak data. The maximum likelihood estimates of the median incubation period range from 1.43 to 1.64 days according to different modeling assumptions, consistent with a published estimate based on a New York school outbreak. The likelihood values of the different modeling assumptions do not differ greatly from each other, although models with the exponential assumption yield slightly shorter incubation periods than those with the uniform exposure assumption. Differences between our proposed approach and a published method for doubly interval-censored analysis highlight the importance of accounting for the dependence of the frequency of exposure on the survival function of incubating individuals among imported cases. A truncation of the density function of the incubation period due to an absence of illness onset during the exposure period also needs to be considered. When the data generating process is similar to that among imported cases, and when the incubation period is close to or shorter than the length of exposure, accounting for these aspects is critical for long exposure times.
甲型流感(H1N1-2009)的潜伏期的经验估计值有限。我们对在 2009 年大流行早期从夏威夷前往日本的确诊输入病例(n=72)的潜伏期进行了估计。我们解决了删失问题,并采用感染年龄结构论证来明确建立离开后的每日发病频率模型。我们假设在夏威夷的暴露频率服从均匀分布和指数分布,对于后一种假设,从当地暴发数据中获取了夏威夷的感染危险率。根据不同的建模假设,中位潜伏期的最大似然估计值范围在 1.43 至 1.64 天之间,与基于纽约学校暴发的一项已发表估计值一致。不同建模假设的似然值彼此之间差异不大,尽管假设暴露呈指数分布的模型比假设暴露均匀分布的模型产生的潜伏期略短。我们提出的方法与双区间删失分析的已发表方法之间的差异突出了在输入病例中,考虑到暴露频率对潜伏期个体生存函数的依赖性的重要性。由于在暴露期间未出现发病,也需要考虑潜伏期密度函数的截断。当数据生成过程类似于输入病例时,并且潜伏期接近或短于暴露时间时,在长时间暴露的情况下,考虑这些方面至关重要。