Asten, L. van

Unspecified gastroenteritis illness and deaths in the elderly associated with norovirus epidemics (Article)

2011-05-01T00:00:00Z

Background: New variant strains of norovirus have emerged worldwide in recent years, evolving by mutation much like influenza viruses. These strains have been associated with a notable increase in the number of annual norovirus outbreaks. However, the impact of such increased norovirus activity on morbidity and mortality is not clear because norovirus infection is rarely specifically registered. Methods: We studied trends of gastroenteritis with unspecified cause in medical registrations (ie, general practitioner [GP] visits, hospitalizations, and deaths) and their association with known temporal trends in norovirus outbreaks in the Netherlands. Using weekly counts in the elderly (aged 65+ years) from 1999 through 2006, we applied Poisson regression analyses adjusted for additional pathogens and seasonal trends (linear, sine, and cosine terms). Results: In the elderly, each notified norovirus outbreak was associated with an estimated 26 unspecified gastroenteritis GP visits (95% confidence interval = 17-34), 2.2 unspecified gastroenteritis hospitalizations (1.6-2.7), and 0.14 unspecified gastroenteritis deaths (0.08-0.21). For the heaviest norovirus season (2004-2005), these models attributed up to 3804 unspecified gastroenteritis GP visits, 318 unspecified gastroenteritis hospitalizations, and 21 unspecified gastroenteritis deaths to norovirus outbreaks among a total elderly population of 2.3 million. DISCUSSION:: The recent increase in norovirus outbreak activity is associated with increases of unspecified gastroenteritis morbidity and even deaths in the elderly. Norovirus should not be regarded as an infection with trivial health risks. Copyright

In search of hidden Q-fever outbreaks: Linking syndromic hospital clusters to infected goat farms (Article)

2011-01-01T00:00:00Z

Large Q-fever outbreaks were reported in The Netherlands from May 2007 to 2009, with dairy-goat farms as the putative source. Since Q-fever outbreaks at such farms were first reported in 2005, we explored whether there was evidence of human outbreaks before May 2007. Space-time scan statistics were used to look for clusters of lower-respiratory infections (LRIs), hepatitis, and/or endocarditis in hospitalizations, 2005-2007. We assessed whether these were plausibly caused by Q fever, using patients' age, discharge diagnoses, indications for other causes, and overlap with reported Q fever in goats/humans. For seven detected LRI clusters and one hepatitis cluster, we considered Q fever a plausible cause. One of these clusters reflected the recognized May 2007 outbreak. Real-time syndromic surveillance would have detected four of the other clusters in 2007, one in 2006 and two in 2005, which might have resulted in detection of Q-fever outbreaks up to 2 years earlier.

Syndromic surveillance for local outbreaks of lower-respiratory infections: Would it work? (Article)

2010-09-14T00:00:00Z

Background: Although syndromic surveillance is increasingly used to detect unusual illness, there is a debate whether it is useful for detecting local outbreaks. We evaluated whether syndromic surveillance detects local outbreaks of lower-respiratory infections (LRIs) without swamping true signals by false alarms. Methods and Findings: Using retrospective hospitalization data, we simulated prospective surveillance for LRI-elevations. Between 1999-2006, a total of 290762 LRIs were included by date of hospitalization and patients place of residence (>80% coverage, 16 million population). Two large outbreaks of Legionnaires disease in the Netherlands were used as positive controls to test whether these outbreaks could have been detected as local LRI elevations. We used a space-time permutation scan statistic to detect LRI clusters. We evaluated how many LRI-clusters were detected in 1999-2006 and assessed likely causes for the cluster-signals by looking for significantly higher proportions of specific hospital discharge diagnoses (e.g. Legionnaires disease) and overlap with regional influenza elevations. We also evaluated whether the number of space-time signals can be reduced by restricting the scan statistic in space or time. In 1999-2006 the scan-statistic detected 35 local LRI clusters, representing on average 5 clusters per year. The known Legionnaires' disease outbreaks in 1999 and 2006 were detected as LRI-clusters, since cluster-signals were generated with an increased proportion of Legionnaires disease patients (p:<0.0001). 21 other clusters coincided with local influenza and/or respiratory syncytial virus activity, and 1 cluster appeared to be a data artifact. For 11 clusters no likely cause was defined, some possibly representing as yet undetected LRI-outbreaks. With restrictions on time and spatial windows the scan statistic still detected the Legionnaires' disease outbreaks, without loss of timeliness and with less signals generated in time (up to 42% decline). Conclusions: To our knowledge this is the first study that systematically evaluates the performance of space-time syndromic surveillance with nationwide high coverage data over a longer period. The results show that syndromic surveillance can detect local LRI-outbreaks in a timely manner, independent of laboratory-based outbreak detection. Furthermore, since comparatively few new clusters per year were observed that would prompt investigation, syndromic hospital-surveillance could be a valuable tool for detection of local LRI-outbreaks.

Corrigendum to "Strengthening the diagnostic capacity to detect Bio Safety Level 3 organisms in unusual respiratory viral outbreaks" [J. Clin. Virol. 45 (2009) 185-190] (DOI:10.1016/j.jcv.2009.05.024) (Article)

2010-02-01T00:00:00Z

Strengthening the diagnostic capacity to detect Bio Safety Level 3 organisms in unusual respiratory viral outbreaks (Article)

2009-07-01T00:00:00Z

Background: Experience with a highly pathogenic avian influenza outbreak in the Netherlands (2003) illustrated that the diagnostic demand for respiratory viruses at different biosafety levels (including BSL3), can increase unexpectedly and dramatically. Objectives: We describe the measures taken since, aimed at strengthening national laboratory surge capacity and improving preparedness for dealing with diagnostic demand during outbreaks of (emerging) respiratory virus infections, including pandemic influenza virus. Study design: Academic and peripheral medical-microbiological laboratories collaborated to determine minimal laboratory requirements for the identification of viruses in the early stages of a pandemic or a large outbreak of avian influenza virus. Next, an enhanced collaborative national network of outbreak assistance laboratories (OAL) was set up. An inventory was made of the maximum diagnostic throughput that this network can deliver in a period of intensified demand. For an estimate of the potential magnitude of this surge demand, historical counts were calculated from hospital- and physician-based registries of patients presenting with respiratory symptoms. Results: Number of respiratory physician-visits ranged from 140,000 to 615,000 per month and hospitalizations ranged from 3000 to 11,500 per month. The established OAL-network provides rapid diagnostic response with agreed quality requirements and a maximum throughput capacity of 1275 samples/day (38,000 per month), assuming other routine diagnostic work needs to be maintained. Conclusions: Thus surge demand for diagnostics for hospitalized cases (if not distinguishable from other respiratory illness) could be handled by the OAL network. Assessing etiology of community acquired acute respiratory infection however, may rapidly exceed the capacity of the network. Therefore algorithms are needed for triaging for laboratory diagnostics; currently this is not addressed in pandemic preparedness plans.