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arXiv 1502.01236q-bio.PEstat.AP
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基于聚集通报数据的时变传染力下登革热疫情发病率估计

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

Flavio Coelho, Luiz Max Carvalho

摘要:

疾病发病率的量化是流行病学推断和公共卫生规划的关键。然而,对于多血清型病原体,不同类型特异性免疫水平使得难以评估处于风险中的人群。在本文中,我们提出了一个贝叶斯方法估计的攻击率的流行病和初始分数的易感人群使用聚集发病率数据。我们推导出有效再生数R t的概率分布,并使用MCMC获得具有时变感染力的单株SIR传播模型参数的后验分布。我们的方法展示在一个数据集,包括18年的登革热发病率在巴西里约热内卢市。我们证明,它是可能的,以了解初始分数的易感性和攻击率,即使在没有血清型的具体数据。另一方面,这一方法提供的信息有限,强调需要进行详细的血清学调查,以确定人群中特定型免疫力的分布。

英文摘要:

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

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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