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Rabies is a lethal and notifiable zoonotic disease for which diagnostics have to meet the highest standards. In recent years, an evolution was especially seen in molecular diagnostics with a wide variety of different detection methods published. Therefore, a first international ring trial specifically designed on the use of reverse transcription polymerase chain reaction (RT-PCR) for detection of lyssavirus genomic RNA was organized. The trial focussed on assessment and comparison of the performance of conventional and real-time assays. In total, 16 European laboratories participated. All participants were asked to investigate a panel of defined lyssavirus RNAs, consisting of Rabies virus (RABV) and European bat lyssavirus 1 and 2 (EBLV-1 and -2) RNA samples, with systems available in their laboratory. The ring trial allowed the important conclusion that conventional RT-PCR assays were really robust assays tested with a high concordance between different laboratories and assays. The real-time RT-PCR system by Wakeley et al. (2005) in combination with an intercalating dye, and the combined version by Hoffmann and co-workers (2010) showed good sensitivity for the detection of all RABV samples included in this test panel. Furthermore, all used EBLV-specific assays, real-time RT-PCRs as well as conventional RT-PCR systems, were shown to be suitable for a reliable detection of EBLVs. It has to be mentioned that differences were seen in the performance between both the individual RT-PCR systems and the laboratories. Laboratories which used more than one molecular assay for testing the sample panel always concluded a correct sample result. Due to the markedly high genetic diversity of lyssaviruses, the application of different assays in diagnostics is needed to achieve a maximum of diagnostic accuracy. To improve the knowledge about the diagnostic performance proficiency testing at an international level is recommended before using lyssavirus molecular diagnostics e.g. for

Les virus influenza A porcins circulant actuellement en Belgique sont les sous-types H1N1, H3N2 et H1N2. Ces virus zoonotiques peuvent être transmis entre le porc et l’homme par contact direct ou par voie aérogène. Le virus pandémique influenza A/H1N1 (2009) est une nouvelle souche de virus influenza A/H1N1 humain, résultant d’un réassortiment entre deux virus porcins. Sa transmission est principalement interhumaine, avec cependant plusieurs cas indépendants et isolés dans le monde de transmission de l’homme au porc. La présence de ce virus n’a pas encore été détectée en Belgique dans les élevages porcins. En cas d’introduction du virus dans la population porcine belge, le risque qu’il puisse y circuler serait réel, du fait de sa capacité de transmission aérogène et de la haute densité de la population porcine en Belgique, particulièrement dans le Nord du pays. Cependant, vu la faible pathogénicité de cette souche, l’impact économique serait faible pour le secteur porcin. L’infection des porcs par le virus pandémique influenza A/H1N1 pourrait par contre augmenter le risque de réassortiment avec d’autres souches de virus influenza A, ce qui pourrait avoir des conséquences négatives pour la santé publique. Afin de permettre une détection précoce et limiter le risque de diffusion du virus pandémique Influenza A/H1N1 (2009) dans la population porcine, l’instauration d’une surveillance virologique ciblée sur la présence de signes respiratoires aigus chez le porc est recommandée. Dans les conditions actuelles, la vaccination des porcs contre le virus influenza A/H1N1 (2009) ne semble pas nécessaire. Celle-ci pourrait être recommandée en cas de circulation intense du virus chez le porc et chez l’homme, afin de limiter le risque de réassortiment et de protéger la santé publique.

Background. Computerized morbidity registration networks might serve as early warning systems in a time where natural epidemics such as the H 1N1flu can easily spread from one region to another. Methods. In this contribution we examine whether general practice based broad-spectrum computerized morbidity registration networks have the potential to act as a valid surveillance instrument of frequently occurring diseases. We compare general practice based computerized data assessing the frequency of influenza-like illness (ILI) and acute respiratory infections (ARI) with data from a well established case-specific sentinel network, the European Influenza Surveillance Scheme (EISS). The overall frequency and trends of weekly ILI and ARI data are compared using both networks. Results. Detection of influenza-like illness and acute respiratory illness occurs equally fast in EISS and the computerized network. The overall frequency data for ARI are the same for both networks, the overall trends are similar, but the increases and decreases in frequency do not occur in exactly the same weeks. For ILI, the overall rate was slightly higher for the computerized network population, especially before the increase of ILI, the overall trend was almost identical and the increases and decreases occur in the same weeks for both networks. Conclusions. Computerized morbidity registration networks are a valid tool for monitoring frequent occurring respiratory diseases and the detection of sudden outbreaks.

Background: Computerized morbidity registration networks might serve as early warning systems in a time where natural epidemics such as the H1N1 flu can easily spread from one region to another. Methods: In this contribution we examine whether general practice based broad-spectrum computerized morbidity registration networks have the potential to act as a valid surveillance instrument of frequently occurring diseases. We compare general practice based computerized data assessing the frequency of influenza-like illness (ILI) and acute respiratory infections (ARI) with data from a well established case-specific sentinel network, the European Influenza Surveillance Scheme (EISS). The overall frequency and trends of weekly ILI and ARI data are compared using both networks. Results: Detection of influenza-like illness and acute respiratory illness occurs equally fast in EISS and the computerized network. The overall frequency data for ARI are the same for both networks, the overall trends are similar, but the increases and decreases in frequency do not occur in exactly the same weeks. For ILI, the overall rate was slightly higher for the computerized network population, especially before the increase of ILI, the overall trend was almost identical and the increases and decreases occur in the same weeks for both networks. Conclusions: Computerized morbidity registration networks are a valid tool for monitoring frequent occurring respiratory diseases and the detection of sudden outbreaks.

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