A statistical method to estimate the basic reproduction number subject to under-reporting: A case study for the 2009 influenza A pandemic in Mexico
The basic reproduction number (Ro), which is defined as the average number of secondary infections produced by a typical infectious individual in a wholly susceptible population, is a key parameter of disease transmission and it is of great interest to most researchers and policy-makers during the initial outbreak of an epidemic. In practice, the Ro estimation from surveillance data is subject to the time delay until the first disease confirmation and also to the non-reporting rate. So, in this paper we suggested a Markov Chain Monte Carlo (MCMC) method to estimate the Ro subject to the abovementioned problems through a traditional SIR epidemic model. Methods: We adopted a simple stochastic SIR model to describe the disease dynamic. The model divided the population into three compartments: susceptible; infectious; and recovered, at each time point. In relating the model to the data, we employed the MCMC method because of its powerful ability to augment data. The method was tested by a series of simulations. We also applied the method to the 2009 influenza A (H1N1) pandemic in Mexico and adopted the surveillance data from the Ministry of Health of Mexico, which data covered most of the first wave of the epidemic.
Ka Chun Chong Benny Chung Ying Zee
Division of Biostatistics,School of Public Health and Primary Care,The Chinese University of Hong Kong,Hong Kong SAR,China
国际会议
Second Joint Biostatistics Symposium(第二届生物统计国际研讨会2012)
北京
英文
349-370
2012-07-08（万方平台首次上网日期，不代表论文的发表时间）