title: Bayesian estimation of the effective reproduction number for pandemic influenza A H1N1 in Guangdong Province, China.
abstract: OBJECTIVE
  During the course of a pandemic, it is necessary to understand its transmissibility, which is often summarized by the effective reproduction number. Accurate estimation of the effective reproduction number (R) is of vital significance in real-time decision making for coping with pandemic influenza.
  
  
  METHODS
  We used daily case notification data in Guangdong Province, China, in conjunction with Bayesian inference of two different stochastic susceptible, infectious, recovered (SIR) models to estimate the effective reproduction number. The duration of infectiousness was taken from published literature, and the proportion of imported cases was obtained from individual-level data.
  
  
  RESULTS
  At the initial epidemic phase, 40% of the first 261 cases were not locally acquired. Explicitly accounting for imported cases and different infectious periods, the possible range of basic reproduction number was preliminarily estimated to be between 1.05 and 1.46. We showed how the daily case reports provided valuable information to estimate the effective reproduction number. We also found the potential delay in reporting had a relatively minor impact on estimating R.
  
  
  CONCLUSIONS
  Our proposed models and findings provide a relevant contribution towards establishing a basis for monitoring the evolution of emerging infectious diseases in real time and understanding the characteristics of pandemic influenza A H1N1 in Guangdong Province.
authors.affiliation: Disease Prevention and Control Institute, Center for Disease Control and Prevention of Guangdong Province, Guangzhou, P. R. China.
authors.forename: Fen
authors.initials: F
authors.lastname: Yang
authors.forename: Lingling
authors.initials: L
authors.lastname: Yuan
authors.forename: Xuhui
authors.initials: X
authors.lastname: Tan
authors.forename: Cunrui
authors.initials: C
authors.lastname: Huang
authors.forename: Jun
authors.initials: J
authors.lastname: Feng
mesh_terms: D000293:Adolescent; D050936:Basic Reproduction Number / Q000706:statistics & numerical data; D001499:Bayes Theorem; D002681:China / Q000453:epidemiology; D018563:Disease Notification; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology* / Q000635:transmission*; D008297:Male; D058873:Pandemics; D013269:Stochastic Processes