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Detecting the start of an influenza outbreak using exponentially weighted moving average charts

BACKGROUND: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to pro...

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Detalles Bibliográficos
Autores principales: Steiner, Stefan H, Grant, Kristina, Coory, Michael, Kelly, Heath A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909986/
https://www.ncbi.nlm.nih.gov/pubmed/20587013
http://dx.doi.org/10.1186/1472-6947-10-37
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author Steiner, Stefan H
Grant, Kristina
Coory, Michael
Kelly, Heath A
author_facet Steiner, Stefan H
Grant, Kristina
Coory, Michael
Kelly, Heath A
author_sort Steiner, Stefan H
collection PubMed
description BACKGROUND: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to promote public health measures. METHODS: We propose the use of an exponentially weighted moving average (EWMA) control chart of laboratory confirmed influenza counts to detect the start and end of influenza outbreaks. RESULTS: The chart is shown to provide timely signals in an example application with seven years of data from Victoria, Australia. CONCLUSIONS: The EWMA control chart could be applied in other applications to quickly detect influenza outbreaks.
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spelling pubmed-29099862010-07-27 Detecting the start of an influenza outbreak using exponentially weighted moving average charts Steiner, Stefan H Grant, Kristina Coory, Michael Kelly, Heath A BMC Med Inform Decis Mak Research Article BACKGROUND: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to promote public health measures. METHODS: We propose the use of an exponentially weighted moving average (EWMA) control chart of laboratory confirmed influenza counts to detect the start and end of influenza outbreaks. RESULTS: The chart is shown to provide timely signals in an example application with seven years of data from Victoria, Australia. CONCLUSIONS: The EWMA control chart could be applied in other applications to quickly detect influenza outbreaks. BioMed Central 2010-06-29 /pmc/articles/PMC2909986/ /pubmed/20587013 http://dx.doi.org/10.1186/1472-6947-10-37 Text en Copyright ©2010 Steiner et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Steiner, Stefan H
Grant, Kristina
Coory, Michael
Kelly, Heath A
Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title_full Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title_fullStr Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title_full_unstemmed Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title_short Detecting the start of an influenza outbreak using exponentially weighted moving average charts
title_sort detecting the start of an influenza outbreak using exponentially weighted moving average charts
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2909986/
https://www.ncbi.nlm.nih.gov/pubmed/20587013
http://dx.doi.org/10.1186/1472-6947-10-37
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