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

Steiner SH, Grant K, Coory M, Kelly HA - BMC Med Inform Decis Mak (2010)

Bottom Line: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates.The chart is shown to provide timely signals in an example application with seven years of data from Victoria, Australia.The EWMA control chart could be applied in other applications to quickly detect influenza outbreaks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dept. of Statistics, University of Waterloo, Ontario, Canada. shsteine@math.uwaterloo.ca

ABSTRACT

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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Related in: MedlinePlus

Plot of the Baseline Average Run Length (ARL) by the threshold h.
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Figure 4: Plot of the Baseline Average Run Length (ARL) by the threshold h.

Mentions: We use a Markov chain to approximate the steady state baseline ARLs with different thresholds [20]. The results are given in Figure 4. With the previously selected threshold of 6.5, we obtain a (cyclical) steady state [18] average run length of 556 weeks. This means that using the proposed EWMA, we expect, on average, just one out-of-season false alarm roughly every 25 years if the influenza activity remains at the baseline level (recall there are only 5 out-of-season months every year).


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

Steiner SH, Grant K, Coory M, Kelly HA - BMC Med Inform Decis Mak (2010)

Plot of the Baseline Average Run Length (ARL) by the threshold h.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2909986&req=5

Figure 4: Plot of the Baseline Average Run Length (ARL) by the threshold h.
Mentions: We use a Markov chain to approximate the steady state baseline ARLs with different thresholds [20]. The results are given in Figure 4. With the previously selected threshold of 6.5, we obtain a (cyclical) steady state [18] average run length of 556 weeks. This means that using the proposed EWMA, we expect, on average, just one out-of-season false alarm roughly every 25 years if the influenza activity remains at the baseline level (recall there are only 5 out-of-season months every year).

Bottom Line: Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates.The chart is shown to provide timely signals in an example application with seven years of data from Victoria, Australia.The EWMA control chart could be applied in other applications to quickly detect influenza outbreaks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dept. of Statistics, University of Waterloo, Ontario, Canada. shsteine@math.uwaterloo.ca

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus