Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data

摘要: Quantifying the attack ratio of disease is key to epidemiological inference and Public Health planning. For multi-serotype pathogens, however, different levels serotype-specific immunity make it difficult assess population at risk. In this paper we propose a Bayesian method for estimation an epidemic initial fraction susceptibles using aggregated incidence data. We derive probability distribution effective reproductive number, R t , use MCMC obtain posterior distributions parameters single-strain SIR transmission model with time-varying force infection. Our showcased in data set consisting 18 years dengue city Rio de Janeiro, Brazil. demonstrate that possible learn about even absence serotype specific On other hand, information provided by approach limited, stressing need detailed serological surveys characterise population.