Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method

Vega, Tomás; Lozano, José; Meerhoff, T J; Snacken, René; Mott, Joshua A.; Lejarazu, Raúl Ortíz de; Nunes, Baltazar

doi:10.1111/j.1750-2659.2012.00422.x

Cited by 171 publications

(249 citation statements)

References 35 publications

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“…The MEM approach uses historical data to calculate the typical timing and duration of an influenza epidemic by determining the minimum number of weeks with the maximum cumulative rate [12]. By matching weeks of each season according to their relative location in the modelled epidemic period, the typical epidemic period curve was calculated.…”

Section: Mem Approachmentioning

confidence: 99%

Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes

et al. 2014

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SUMMARYGeneral Practitioner consultation rates for influenza-like illness (ILI) are monitored through several geographically distinct schemes in the UK, providing early warning to government and health services of community circulation and intensity of activity each winter. Following on from the 2009 pandemic, there has been a harmonization initiative to allow comparison across the distinct existing surveillance schemes each season. The moving epidemic method (MEM), proposed by the European Centre for Disease Prevention and Control for standardizing reporting of ILI rates, was piloted in 2011/12 and 2012/13 along with the previously proposed UK method of empirical percentiles. The MEM resulted in thresholds that were lower than traditional thresholds but more appropriate as indicators of the start of influenza virus circulation. The intensity of the influenza season assessed with the MEM was similar to that reported through the percentile approach. The MEM pre-epidemic threshold has now been adopted for reporting by each country of the UK. Further work will continue to assess intensity of activity and apply standardized methods to other influenza-related data sources.

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Section: Mem Approachmentioning

confidence: 99%

Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes

et al. 2014

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“…Therefore, we consider the limits used for evaluating detection and the peak-timing predictions in this study to be at least as strict as those in the CDC challenge. Regarding the prediction of peak intensity, we considered a forecast to be accurate if it predicted the peak intensity to be the correct peak-intensity category as defined by Vega et al ( 8 ), who calculated the thresholds for each of these categories for every winter influenza season by applying the moving epidemic method ( 21 ) on 5–10 previously occurring seasons. Hence, we consider these categories to be reliable.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Nowcasting for Detecting and Predicting Local Influenza Epidemics, Sweden, 2009–2014

Spreco¹,

Eriksson²,

Dahlström³

et al. 2018

Emerg. Infect. Dis.

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The growing availability of big data in healthcare and public health opens possibilities for infectious disease control in local settings. We prospectively evaluated a method for integrated local detection and prediction (nowcasting) of influenza epidemics over 5 years, using the total population in Östergötland County, Sweden. We used routine health information system data on influenza-diagnosis cases and syndromic telenursing data for July 2009–June 2014 to evaluate epidemic detection, peak-timing prediction, and peak-intensity prediction. Detection performance was satisfactory throughout the period, except for the 2011–12 influenza A(H3N2) season, which followed a season with influenza B and pandemic influenza A(H1N1)pdm09 virus activity. Peak-timing prediction performance was satisfactory for the 4 influenza seasons but not the pandemic. Peak-intensity levels were correctly categorized for the pandemic and 2 of 4 influenza seasons. We recommend using versions of this method modified with regard to local use context for further evaluations using standard methods.

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“…Finally, several countries have been using an influenza epidemic threshold for years [23,24], yet the best data source and the best outbreak detection method to use are still a matter of discussion [25]. We shall continue to look for the combination of data sources and methods that produces the most relevant results for our needs.…”

Section: Limitations and Perspectivesmentioning

confidence: 99%

Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France

et al. 2017

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The 2014/15 influenza epidemic caused a work overload for healthcare facilities in France. The French national public health agency announced the start of the epidemic – based on indicators aggregated at the national level – too late for many hospitals to prepare. It was therefore decided to improve the influenza alert procedure through (i) the introduction of a pre-epidemic alert level to better anticipate future outbreaks, (ii) the regionalisation of surveillance so that healthcare structures can be informed of the arrival of epidemics in their region, (iii) the standardised use of data sources and statistical methods across regions. A web application was developed to deliver statistical results of three outbreak detection methods applied to three surveillance data sources: emergency departments, emergency general practitioners and sentinel general practitioners. This application was used throughout the 2015/16 influenza season by the epidemiologists of the headquarters and regional units of the French national public health agency. It allowed them to signal the first influenza epidemic alert in week 2016-W03, in Brittany, with 11 other regions in pre-epidemic alert. This application received positive feedback from users and was pivotal for coordinating surveillance across the agency’s regional units.

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Influenza surveillance in Europe: establishing epidemic thresholds by the Moving Epidemic Method

Cited by 171 publications

References 35 publications

Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes

Harmonizing influenza primary-care surveillance in the United Kingdom: piloting two methods to assess the timing and intensity of the seasonal epidemic across several general practice-based surveillance schemes

Evaluation of Nowcasting for Detecting and Predicting Local Influenza Epidemics, Sweden, 2009–2014

Improving regional influenza surveillance through a combination of automated outbreak detection methods: the 2015/16 season in France

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