Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.18/1260
Título: Nowcasting influenza epidemics using non-homogeneous hidden Markov models
Autor: Nunes, Baltazar
Natário, Isabel
Carvalho, Maria Lucília
Palavras-chave: Estados de Saúde e de Doença
Hidden Markov Models
Nowcasting
Surveillance
Influenza
Data: 5-Nov-2012
Editora: John Wiley and Sons
Citação: Stat Med. 2012 Nov 5. doi: 10.1002/sim.5670. [Epub ahead of print]
Resumo: Timeliness of a public health surveillance system is one of its most important characteristics. The process of predicting the present situation using available incomplete information from surveillance systems has received the term nowcasting and has high public health interest. Generally in Europe, general practitioners’ sentinel networks support the epidemiological surveillance of influenza activity, and each week's epidemiological bulletins are usually issued between Wednesday and Friday of the following week. In this work, we have developed a non-homogeneous hidden Markov model (HMM) that, on a weekly basis, uses as covariates an early observation of influenza-like illness (ILI) incidence rate and the number of ILI cases tested positive to nowcast the current week ILI rate and the probability that the influenza activity is in an epidemic state. We use Bayesian inference to find estimates of the model parameters and nowcasted quantities. The results obtained with data provided by the Portuguese influenza surveillance system show the additional value of using a non-homogeneous HMM instead of a homogeneous one. The use of a non-homogeneous HMM improves the surveillance system timeliness in 2 weeks. Copyright © 2012 John Wiley & Sons, Ltd.
Peer review: yes
URI: http://hdl.handle.net/10400.18/1260
ISSN: 0277-6715
Versão do Editor: http://onlinelibrary.wiley.com/doi/10.1002/sim.5670/abstract;jsessionid=74C8018CFDA4464DD89CD2CAAEF9619B.d04t03
Aparece nas colecções:DEP - Artigos em revistas internacionais

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