Eurosurveillance - Volume 19, Issue 46, 20 November 2014

We provide the first scientific report of influenza A virus involvement in a mass mortality event among harbour seals (Phoca vitulina) off the west coast of Sweden. Avian influenza A (H10N7) virus was detected in the lungs of two affected animals. This subtype has not been reported in seals to date, nor has influenza A-associated mortality been reported in seals in Europe. Circulation of avian influenza viruses in mammals may have implications for public health.

Emerging infections are a potential risk during mass gathering events due to the congregation of large numbers of international travellers. To mitigate this risk for the London 2012 Olympic and Paralympic Games, a sentinel surveillance system was developed to identify clusters of emerging infections presenting as undiagnosed serious infectious illness (USII) in intensive care units (ICUs). Following a six month pilot period, which had begun in January 2011, the surveillance was operational for a further 18 months spanning the Games. The surveillance system and reported USII cases were reviewed and evaluated after this 18 month operational period including assessment of positive predictive value (PPV), timeliness, acceptability and sensitivity of the system. Surveillance records were used to review reported cases and calculate the PPV and median reporting times of USII surveillance. Sensitivity was assessed through comparison with the pilot period. Participating clinicians completed a five-point Likert scale questionnaire about the acceptability of surveillance. Between 11 July 2011 and 10 January 2013, 34 cases were reported. Of these, 22 remained classified as USII at the time of the evaluation, none of which were still hospitalised. No clusters were identified. The 22 USII cases had no association with the Games, suggesting that they represented the background level of USII in the area covered by the surveillance. This corresponded to an annualised rate of 0.39 cases/100,000 population and a PPV of 65%. Clinicians involved in the surveillance reported high acceptability levels. The USII surveillance model could be a useful public health tool in other countries and during mass gathering events for identifying potential clusters of emerging infections.

Enteroviruses (EV) and human parechoviruses (HPeV) are endemic worldwide. These infections are a constant cause of hospitalisation and severe disease, predominantly in young children and infants. Coordinated monitoring and surveillance are crucial to control these infections. We have monitored EV and HPeV epidemiology in Amsterdam from 2007 to 2011 with real-time RT-PCR and direct genotyping, facilitating highly sensitive surveillance. Moreover, we conducted a literature survey of existing surveillance data for comparison. Only 14 studies were identified. While HPeV1 was most frequently detected in Amsterdam, EV-B viruses dominated nationally and internationally. Furthermore, the top 10 strains detected differed yearly and per study. However, detection and typing methods were too varied to allow direct comparison and comprehension of the worldwide distribution and circulation patterns of the different genotypes. This limited a direct response to anticipate peaks. Uniform European monitoring programmes are essential to aid prediction of outbreaks and disease management.

Syndromic data sources have been sought to improve the timely detection of increased influenza transmission. This study set out to examine the prospective performance of telenursing chief complaints in predicting influenza activity. Data from two influenza seasons (2007/08 and 2008/09) were collected in a Swedish county (population 427,000) to retrospectively determine which grouping of telenursing chief complaints had the largest correlation with influenza case rates. This grouping was prospectively evaluated in the three subsequent seasons. The best performing telenursing complaint grouping in the retrospective algorithm calibration was fever (child, adult) and syncope (r=0.66; p<0.001). In the prospective evaluation, the performance of 14-day predictions was acceptable for the part of the evaluation period including the 2009 influenza pandemic (area under the curve (AUC)=0.84; positive predictive value (PPV)=0.58), while it was strong (AUC=0.89; PPV=0.93) for the remaining evaluation period including only influenza winter seasons. We recommend the use of telenursing complaints for predicting winter influenza seasons. The method requires adjustments when used during pandemics.

The genetic diversity of 89 clinical Legionella isolates, collected between 1987 and 2012, in 22 hospitals from the five regions of Portugal, was analysed in this study using monoclonal antibodies (MAbs) of the Dresden panel and the sequence-based typing (SBT) protocol. The eBURST algorithm was used to infer levels of relatedness between isolates. All isolates collected were Legionella pneumophila, which were further characterised into four subgroups by MAbs, and 30 sequence types (STs) by SBT. Twelve of the STs were unique to Portugal; one of them (ST100) was represented by 32 epidemiologically related isolates. The ST44 was the profile with the highest number of epidemiologically unrelated isolates. The eBURST analyses indicate that, within the group formed by the 30 STs identified in this study, 17 STs were genetically close to at least another ST in the group. The comparison between the eBURST diagrams obtained with the STs from this study and the entire SBT database of the European Working Group for Legionella, showed that 24 (seven of them unique to Portugal) of our 30 STs were related with STs identified in others countries. These results suggest that the population of L. pneumophila clinical strains in Portugal includes both worldwide and local strains.