A major outbreak of gastroenteritis in Réunion Island in 2012: first identification of G12 rotavirus on the Island.

Between August and November 2012 a severe outbreak of gastroenteritis occurred on Réunion Island, affecting more than 50,000 cases, particularly young children. Virological analyses showed that the virus responsible for this epidemic was rotavirus. Genotyping of stool samples indicated circulation of rotavirus type G3P[8] but also G12P[8], highlighting the risk of global emergence of this genotype in the coming years.

Burden of infant bronchiolitis: data from a hospital network.

In France, surveillance of bronchiolitis is based on a pilot network of hospital emergency departments. The study was a 1-year observational study (2007-2008) carried out in a central region of metropolitan France. The hospitalization rate for bronchiolitis was 17.7/1000 children aged <1 year and the estimated prevalence of bronchiolitis ranged from 17.7% to 34.4% in children aged <1 year. Such a network constitutes a valuable tool to estimate the dynamic and the burden of infant bronchiolitis.

Syndromic surveillance based on emergency department activity and crude mortality: two examples.

Recent public health crises have shown the need for readily available information allowing proper management by decision-makers. One way of obtaining early information is to involve data providers who already record routine data for their own use. We describe here the results of a pilot network carried out by the InVS (Institut national de veille sanitaire) which gathered data available in real time from hospital emergency departments and register offices. Emergency departments data were registered from patients' computerized medical files. Mortality data were received from the national institute of statistics (Insee). Data were transmitted automatically on a daily basis. Influenza data from outbreaks in 2004/05 and 2005/06 were compared with data from the sentinel network for the same periods. Environmental health data were compared with meteorological temperatures recorded in Paris between June and August 2006. A mortality analysis was conducted on a weekly basis. Correlation between influenza data from emergency departments and data from Sentiweb (sentinel network) was significant (p<0.001) for both outbreaks. In 2005 and 2006, the outbreaks were described similarly by both sources with identification of the start of the outbreaks by both systems during the same weeks. As for data related to heat, a significant correlation was observed between some diagnoses and temperature increases. For both types of phenomena, mortality increased significantly with one to two weeks lag. To our knowledge, this is the first time that a study using real time morbidity and mortality data is conducted. These initial results show how these data complement each other and how their simultaneous analysis in real time makes it possible to quickly measure the impact of a phenomenon.

Syndromic surveillance based on emergency department activity and crude mortality: two examples.

Recent public health crises have shown the need for readily available information allowing proper management by decision-makers. One way of obtaining early information is to involve data providers who already record routine data for their own use. We describe here the results of a pilot network carried out by the InVS (Institut national de veille sanitaire) which gathered data available in real time from hospital emergency departments and register offices. Emergency departments data were registered from patients' computerised medical files. Mortality data were received from the national institute of statistics (Insee). Data were transmitted automatically on a daily basis. Influenza data from outbreaks in 2004/05 and 2005/06 were compared with data from the sentinel network for the same periods. Environmental health data were compared with meteorological temperatures recorded in Paris between June and August 2006. A mortality analysis was conducted on a weekly basis. Correlation between influenza data from emergency departments and data from Sentiweb (sentinel network) was significant (p<0.001) for both outbreaks. In 2005 and 2006, the outbreaks were described similarly by both sources with identification of the start of the outbreaks by both systems during the same weeks. As for data related to heat, a significant correlation was observed between some diagnoses and temperature increases. For both types of phenomena, mortality increased significantly with one to two weeks lag. To our knowledge, this is the first time that a study using real time morbidity and mortality data is conducted. These initial results show how these data complement each other and how their simultaneous analysis in real time makes it possible to quickly measure the impact of a phenomenon.