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http://dx.doi.org/10.7465/jkdi.2017.28.1.153

A study on MERS-CoV outbreak in Korea using Bayesian negative binomial branching processes  

Park, Yuha (Department of Statistics, Chonnam University)
Choi, Ilsu (Department of Statistics, Chonnam University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.1, 2017 , pp. 153-161 More about this Journal
Abstract
Branching processes which is used for epidemic dispersion as stochastic process model have advantages to estimate parameters by real data. We have to estimate both mean and dispersion parameter in order to use the negative binomial distribution as an offspring distribution on branching processes. In existing studies on biology and epidemiology, it is estimated using maximum-likelihood methods. However, for most of epidemic data, it is hard to get the best precision of maximum-likelihood estimator. We suggest a Bayesian inference that have good properties of statistics for small-sample. After estimating dispersion parameter we modelled the posterior distribution for 2015 Korea MERS cases. As the result, we found that the estimated dispersion parameter is relatively stable no matter how we assume prior distribution. We also computed extinction probabilities on branching processes using estimated dispersion parameters.
Keywords
Bayesian inference; branching processes; dispersion parameter; epidemic emergence; mathematical modeling; negative binomial distribution;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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