Predicting influenza-like illness-related emergency department visits by modelling spatio-temporal syndromic surveillance data.
Epidemiol Infect
; 147: e312, 2019 12 02.
Article
em En
| MEDLINE
| ID: mdl-31787127
ABSTRACT
Predicting the magnitude of the annual seasonal peak in influenza-like illness (ILI)-related emergency department (ED) visit volumes can inform the decision to open influenza care clinics (ICCs), which can mitigate pressure at the ED. Using ILI-related ED visit data from the Alberta Real Time Syndromic Surveillance Net for Edmonton, Alberta, Canada, we developed (training data, 1 August 2004-31 July 2008) and tested (testing data, 1 August 2008-19 February 2014) spatio-temporal statistical prediction models of daily ILI-related ED visits to estimate high visit volumes 3 days in advance. Our Main Model, based on a generalised linear mixed model with random intercept, incorporated prediction residuals over 14 days and captured increases in observed volume ahead of peaks. During seasonal influenza periods, our Main Model predicted volumes within ±30% of observed volumes for 67%-82% of high-volume days and within 0.3%-21% of observed seasonal peak volumes. Model predictions were not as successful during the 2009 H1N1 pandemic. Our model can provide early warning of increases in ILI-related ED visit volumes during seasonal influenza periods of differing intensities. These predictions may be used to support public health decisions, such as if and when to open ICCs, during seasonal influenza epidemics.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Serviço Hospitalar de Emergência
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Influenza Humana
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Vírus da Influenza A Subtipo H1N1
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Vigilância em Saúde Pública
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Análise Espaço-Temporal
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Utilização de Instalações e Serviços
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Modelos Biológicos
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Adolescent
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Adult
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Aged
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Aged80
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Child
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Child, preschool
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Humans
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Infant
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Middle aged
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Newborn
País/Região como assunto:
America do norte
Idioma:
En
Revista:
Epidemiol Infect
Assunto da revista:
DOENCAS TRANSMISSIVEIS
/
EPIDEMIOLOGIA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Canadá