Analyzing left-truncated and right-censored infectious disease cohort data with interval-censored infection onset

Daewoo Pak, Jun Liu, Jing Ning, Guadalupe Gómez, Yu Shen

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)287-298
Number of pages12
JournalStatistics in Medicine
Volume40
Issue number2
DOIs
StatePublished - Jan 30 2021

Keywords

  • generalized odd rate class of models
  • incubation period of an infectious disease
  • interval censoring
  • left truncation
  • uncertain initiating event

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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