Analyzing left-truncated and right-censored infectious disease cohort data with interval-censored infection onset
n an infectious disease cohort study, individuals who have been infected with apathogenare 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 cont...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/345511 |
| Acceso en línea: | https://hdl.handle.net/2117/345511 https://dx.doi.org/10.1002/sim.8774 |
| Access Level: | acceso abierto |
| Palabra clave: | Generalized odd rate class of models Incubation period of an infectious disease Interval censoring Left truncation Uncertain initiating event Classificació AMS::90 Operations research, mathematical programming Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa |
| Sumario: | n an infectious disease cohort study, individuals who have been infected with apathogenare 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 sub-jects are likely to have longer incubation periods due to the prevalent sampling. In this paper, 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 |
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