TY - JOUR
T1 - Analyzing left-truncated and right-censored infectious disease cohort data with interval-censored infection onset
AU - Pak, Daewoo
AU - Liu, Jun
AU - Ning, Jing
AU - Gómez, Guadalupe
AU - Shen, Yu
N1 - Funding Information:
This work was supported in part by grants CA016672 and CA193878 from the National Cancer Institute (NCI); by grant PID2019‐104830RB‐I00 from the Ministerio de Ciencia e Innovación (Spain); by grant MTM2015‐64465‐C2‐1‐R (MINECO/FEDER) from the Ministerio de Economía y Competitividad (Spain); and by grant 2017 SGR 622 (GRBIO) from the Departament d'Economia i Coneixement de la Generalitat de Catalunya(Spain).
PY - 2021/1/30
Y1 - 2021/1/30
N2 - 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.
AB - 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.
KW - generalized odd rate class of models
KW - incubation period of an infectious disease
KW - interval censoring
KW - left truncation
KW - uncertain initiating event
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U2 - 10.1002/sim.8774
DO - 10.1002/sim.8774
M3 - Article
C2 - 33086432
AN - SCOPUS:85092893515
VL - 40
SP - 287
EP - 298
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 2
ER -