The impact of prior information on estimates of disease transmissibility using Bayesian tools.
Título
The impact of prior information on estimates of disease transmissibility using Bayesian tools.
Autor
Carlee B Moser, Mayetri Gupta, Brett N. Archer, Laura F. White
Descripción
The basic reproductive number (R₀) and the distribution of the serial interval (SI) are often used to quantify transmission during an infectious disease outbreak. In this paper, we present estimates of R₀ and SI from the 2003 SARS outbreak in Hong Kong and Singapore, and the 2009 pandemic influenza A(H1N1) outbreak in South Africa using methods that expand upon an existing Bayesian framework. This expanded framework allows for the incorporation of additional information, such as contact tracing or household data, through prior distributions. The results for the R₀ and the SI from the influenza outbreak in South Africa were similar regardless of the prior information (R0 = 1.36-1.46, μ = 2.0-2.7, μ = mean of the SI). The estimates of R₀ and μ for the SARS outbreak ranged from 2.0-4.4 and 7.4-11.3, respectively, and were shown to vary depending on the use of contact tracing data. The impact of the contact tracing data was likely due to the small number of SARS cases relative to the size of the contact tracing sample.
Fecha
2015
Identificador
DOI: 10.1371/journal.pone.0118762
Fuente
PLoS ONE
Editor
Public Library of Science (PLoS)
Cobertura
Science, Medicine
Idioma
EN
Colección
Citación
Carlee B Moser, Mayetri Gupta, Brett N. Archer, Laura F. White, “The impact of prior information on estimates of disease transmissibility using Bayesian tools.,” SOCICT Open, consulta 18 de abril de 2026, https://www.socictopen.socict.org/items/show/1382.
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