The impact of prior information on estimates of disease transmissibility using Bayesian tools

PLoS One. 2015 Mar 20;10(3):e0118762. doi: 10.1371/journal.pone.0118762. eCollection 2015.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Bayes Theorem
  • Computer Simulation
  • Confidence Intervals
  • Contact Tracing
  • Disease Outbreaks / statistics & numerical data
  • Hong Kong / epidemiology
  • Humans
  • Influenza A Virus, H1N1 Subtype
  • Influenza, Human / epidemiology*
  • Influenza, Human / transmission*
  • Influenza, Human / virology
  • Severe Acute Respiratory Syndrome / epidemiology
  • Singapore / epidemiology
  • South Africa / epidemiology