title: A Bayesian inferential approach to quantify the transmission intensity of disease outbreak.
abstract: BACKGROUND
  Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns.
  
  
  METHODS
  We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R0), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R0 from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase.
  
  
  RESULTS
  The estimated R0 with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of R0.
  
  
  CONCLUSIONS
  Basic reproduction number R0 provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth.
authors.affiliation: Department of Studies in Statistics, Karnatak University, Dharwad 580003, India.
authors.forename: Adiveppa S
authors.initials: AS
authors.lastname: Kadi
authors.affiliation: Department of Studies in Statistics, Karnatak University, Dharwad 580003, India.
authors.forename: Shivakumari R
authors.initials: SR
authors.lastname: Avaradi
mesh_terms: D000465:Algorithms; D050936:Basic Reproduction Number; D001499:Bayes Theorem; D004196:Disease Outbreaks; D006801:Humans; D007194:India; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human / Q000453:epidemiology* / Q000635:transmission*; D015233:Models, Statistical; D011336:Probability; D012984:Software