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Estimating the Distribution of the Incubation Periods of Human Avian Influenza A(H7N9) Virus Infections

Overview
Journal Am J Epidemiol
Specialty Public Health
Date 2015 Sep 27
PMID 26409239
Citations 19
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Abstract

A novel avian influenza virus, influenza A(H7N9), emerged in China in early 2013 and caused severe disease in humans, with infections occurring most frequently after recent exposure to live poultry. The distribution of A(H7N9) incubation periods is of interest to epidemiologists and public health officials, but estimation of the distribution is complicated by interval censoring of exposures. Imputation of the midpoint of intervals was used in some early studies, resulting in estimated mean incubation times of approximately 5 days. In this study, we estimated the incubation period distribution of human influenza A(H7N9) infections using exposure data available for 229 patients with laboratory-confirmed A(H7N9) infection from mainland China. A nonparametric model (Turnbull) and several parametric models accounting for the interval censoring in some exposures were fitted to the data. For the best-fitting parametric model (Weibull), the mean incubation period was 3.4 days (95% confidence interval: 3.0, 3.7) and the variance was 2.9 days; results were very similar for the nonparametric Turnbull estimate. Under the Weibull model, the 95th percentile of the incubation period distribution was 6.5 days (95% confidence interval: 5.9, 7.1). The midpoint approximation for interval-censored exposures led to overestimation of the mean incubation period. Public health observation of potentially exposed persons for 7 days after exposure would be appropriate.

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References
1.
Cowling B, Jin L, Lau E, Liao Q, Wu P, Jiang H . Comparative epidemiology of human infections with avian influenza A H7N9 and H5N1 viruses in China: a population-based study of laboratory-confirmed cases. Lancet. 2013; 382(9887):129-37. PMC: 3777567. DOI: 10.1016/S0140-6736(13)61171-X. View

2.
SARTWELL P . The distribution of incubation periods of infectious disease. Am J Hyg. 1950; 51(3):310-8. DOI: 10.1093/oxfordjournals.aje.a119397. View

3.
de Gruttola V, Lagakos S . Analysis of doubly-censored survival data, with application to AIDS. Biometrics. 1989; 45(1):1-11. View

4.
Gao R, Cao B, Hu Y, Feng Z, Wang D, Hu W . Human infection with a novel avian-origin influenza A (H7N9) virus. N Engl J Med. 2013; 368(20):1888-97. DOI: 10.1056/NEJMoa1304459. View

5.
Nishiura H . Early efforts in modeling the incubation period of infectious diseases with an acute course of illness. Emerg Themes Epidemiol. 2007; 4:2. PMC: 1884151. DOI: 10.1186/1742-7622-4-2. View