A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak

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. Method. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R (0)), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R (0) from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. Result. The estimated R (0) 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 R (0). Conclusion. Basic reproduction number R (0) 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.