In an infectious disease cohort study, individuals who have been infected with a pathogen are often recruited for follow up. The period between infection and the onset of symptomatic disease, referred to as the incubation period, is of interest because of its importance on disease surveillance and control. However, the incubation period is often difficult to ascertain due to the uncertainty associated with asymptomatic infection onset time. An additional complication is that the observed infected subjects are likely to have longer incubation periods due to the prevalent sampling. In this article, we demonstrate how to estimate the distribution of the incubation period with the uncertain infection onset, subject to left‐truncation and right‐censoring. We employ a family of sufficiently general parametric models, the generalized odds‐rate class of regression models, for the underlying incubation period and its correlation with covariates. In simulation studies, we assess the finite sample performance of the model fitting and hazard function estimation. The proposed method is illustrated on data from the HIV/AIDS study on injection drug users admitted to a detoxification program in Badalona, Spain.

中文翻译：

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分析具有间隔删失感染发作的左截断和右删失传染病队列数据

在一项传染病队列研究中，经常招募已感染病原体的个体进行随访。从感染到出现有症状的疾病之间的时期（称为潜伏期）是令人感兴趣的，因为它对疾病监测和控制很重要。然而，由于与无症状感染发作时间相关的不确定性，潜伏期通常难以确定。另一个复杂情况是，观察到的受感染对象可能由于普遍采样而具有更长的潜伏期。在本文中，我们展示了如何估计感染发作不确定的潜伏期分布，受左截断和右删失的影响。我们采用了一系列足够通用的参数模型，回归模型的广义赔率类，用于潜在的潜伏期及其与协变量的相关性。在模拟研究中，我们评估模型拟合和危险函数估计的有限样本性能。所提出的方法以来自西班牙巴达洛纳接受戒毒计划的注射吸毒者的艾滋病毒/艾滋病研究数据进行说明。