Influenza surveillance in Europe: comparing intensity levels calculated using the moving epidemic method

Abstract

ObjectivesAlthough influenza-like illnesses (ILI) and acute respiratory illnesses (ARI) surveillance are well established in Europe, the comparability of intensity among countries and seasons remains an unresolved challenge. The objective is to compare the intensity of ILI and ARI in some European countries.Design and settingWeekly ILI and ARI incidence rates and proportion of primary care consultations were modeled in 28 countries for the 1996/1997–2013/2014 seasons using the moving epidemic method (MEM). We calculated the epidemic threshold and three intensity thresholds, which delimit five intensity levels: baseline, low, medium, high, and very high. The intensity of 2013/2014 season is described and compared by country.ResultsThe lowest ILI epidemic thresholds appeared in Sweden and Estonia (below 10 cases per 100 000) and the highest in Belgium, Denmark, Hungary, Poland, Serbia, and Slovakia (above 100 per 100 000). The 2009/2010 season was the most intense, with 35% of the countries showing high or very high intensity levels. The European epidemic period in season 2013/2014 started in January 2014 in Spain, Poland, and Greece. The intensity was between low and medium and only Greece reached the high intensity level, in weeks 7 to 9/2014. Some countries remained at the baseline level throughout the entire surveillance period.ConclusionsEpidemic and intensity thresholds varied by country. Influenza-like illnesses and ARI levels normalized by MEM in 2013/2014 showed that the intensity of the season in Europe was between low and medium in most of the countries. Comparing intensity among seasons or countries is essential for understanding patterns in seasonal epidemics. An automated standardized model for comparison should be implemented at national and international levels.

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

“…A recent comparison of influenza intensity levels in Europe estimated a similar definition (6.4 influenza-diagnosis cases/wk/100,000 population) for the 2008–09 winter influenza season in Sweden ( 8 ). Peak timing was defined as the date when the highest number of influenza-diagnosis cases were documented in the countywide electronic patient record.…”

Epidemiological and statistical basis for detection and prediction of influenza epidemics

“…This limit was determined by inspecting the epidemic curves of previous local influenza epidemics in the learning dataset. In a recent comparison of influenza intensity levels in Europe (Vega et al 2015), a similar definition (6.4 influenza-diagnosis cases/week/100,000) was estimated for the 2008-09 winter influenza season in Sweden. The definition of when an epidemic ends was set to the inter-epidemic (i.e., the period between two epidemics) influenza-diagnosis case level for the setting where the nowcasting method is applied.…”

“…To evaluate the performance of the peak intensity function, the epidemic threshold and intensity level categories (nonepidemic, low, medium, high, and very high) were used ( Table 2). These categories and their limits were determined in a recent comparison of influenza intensity levels in 28 European countries, including Sweden (Vega et al 2015). A prediction was considered successful if the predicted peak intensity fell into the same category as the actual peak intensity, otherwise the prediction was considered unsuccessful.…”

“…In the development phase, timeliness was used to evaluate the peak timing prediction, whereas slightly different metrics were used to evaluate the peak intensity predictions in the retrospective and in the prospective settings. For logical reasons, in the first, an exact metric (the relative difference between the predicted peak intensity and the actual peak intensity) was used, whereas in the latter, the predicted peak intensity was compared with the correct peak intensity category defined by Vega et al (2015).…”

“…These limits are therefore considered to be at least as strict and accurate as those used in the CDC challenge. With regard to the prediction of the peak intensity, a forecast was considered to be accurate if it predicted the peak intensity to the correct peak intensity category defined by Vega et al (2015). In that study, the thresholds for each of these categories were calculated for every winter influenza season by applying the moving epidemic method (Vega et al 2013) to five to ten previous influenza seasons.…”