Identifying International Foodborne Norovirus Outbreak Events: A Combined Epidemiological and Molecular Approach

Norovirussen zijn een van de belangrijkste veroorzakers van uitbraken en sporadische gevallen van gastro-enteritis in Nederland, maar ook wereldwijd. De symptomen bestaan meestal uit projectiel braken en/of waterdunne diarree, waarvan men na enkele dagen hersteld is. Een norovirusinfectie kan echter een ernstiger verloop hebben in kwetsbare personen, zoals ouderen en immuun-gecompromitteerden. Persoon-op-persoon transmissie komt het meeste voor. Toch wordt norovirus vaker via voedsel overgedragen dan enkele jaren geleden werd gedacht. Na introductie van het virus via besmet voedsel, kan persoon-op-persoon transmissie zorgen voor verdere verspreiding. Een voedselgerelateerde uitbraak kan daarnaast niet alleen een lokaal, maar ook een internat

An Integrated Approach to Identifying International Foodborne Norovirus Outbreaks1

Surveillance gaps can be bridged through analysis of combined molecular and epidemiologic data

Money Follows the Person: Transitioning Nursing Home Residents into the Community

Introduction. Research has shown that admission to nursing homes (NH) is associated with decline in several measures of well-being; transitioning out of a NH into the community is a positive predictor for quality of life. Currently, the State of Vermont offers several housing options for Medicaid eligible NH residents; however, there are very few opportunities to fully integrate into the communityhttps://scholarworks.uvm.edu/comphp_gallery/1090/thumbnail.jp

Use of Norovirus Genotype Profiles to Differentiate Origins of Foodborne Outbreaks

Detection should enable containment of viral foodborne infections

Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection

BackgroundHAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. Aim: We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbreak detection. Methods: A descriptive analysis was performed on the timeliness, completeness, epidemiological data and geographic coverage of the dataset. Length and genomic region of the sequences were reviewed as well as the numerical and geographical distribution of the genotypes. The geographical signal in the sequences was assessed based on a short common nt stretch using a 100% identity analysis. Results: The 9,211 reports were heterogeneous for completeness and timeliness, and for length and genomic region of the sequences. Some parts of the world were not represented by the sequences. Geographical differences in prevalence of HAV genotypes described previously could be confirmed with this dataset and for a third (1,075/3,124) of the included sequences, 100% identity of the short common sequence coincided with an identical country of origin. Conclusion: Analysis of a subset of short, shared sequences indicates that a geographical annotation on the level of individual countries is possible with the HAVNet data. If the current incompleteness and heterogeneity of the data can be improved on, HAVNet could become very useful as a worldwide reference set for geographical annotation and for backtracing and outbreak detection

Selection of a phylogenetically informative region of the norovirus genome for outbreak linkage

The recognition of a common source norovirus outbreak is supported by finding identical norovirus sequences in patients. Norovirus sequencing has been established in many (national) public health laboratories and academic centers, but often partial and different genome sequences are used. Therefore, agreement on a target sequence of sufficient diversity to resolve links between outbreaks is crucial. Although harmonization of laboratory methods is one of the keystone activities of networks that have the aim to identify common source norovirus outbreaks, this has proven difficult to accomplish, particularly in the international context. Here, we aimed at providing a method enabling identification of the genomic region informative of a common source norovirus outbreak by bio-informatic tools. The data set of 502 unique full length capsid gene sequences available from the public domain, combined with epidemiological data including linkage information was used to build over 3,000 maximum likelihood (ML) trees for different sequence lengths and regions. All ML trees were evaluated for robustness and specificity of clustering of known linked norovirus outbreaks against the background diversity of strains. Great differences were seen in the robustness of commonly used PCR targets for cluster detection. The capsid gene region spanning nucleotides 900–1,400 was identified as the region optimally substituting for the full length capsid region. Reliability of this approach depends on the quality of the background data set, and we recommend periodic reassessment of this growing data set. The approach may be applicable to multiple sequence-based data sets of other pathogens

Underdiagnosis of foodborne hepatitis a, the Netherlands, 2008-2010

Outbreaks of foodborne hepatitis A are rarely recognized as such. Detection of these infections is challenging because of the infection's long incubation period and patients' recall bias. Nevertheless, the complex food market might lead to reemergence of hepatitis A virus outside of disease-endemic areas. To assess the role of food as a source of infection, we combined routine surveillance with real-time strain sequencing in the Netherlands during 2008-2010. Virus RNA from serum of 248 (59%) of 421 reported case-patients could be sequenced. Without typing, foodborne transmission was suspected for only 4% of reported case-patients. With typing, foodborne transmission increased to being the most probable source of infection for 16%. We recommend routine implementation of an enhanced surveillance system that includes prompt forwarding and typing of hepatitis A virus RNA isolated from serum, standard use of questionnaires, data sharing, and centralized interpretation of data

Laboratory-based surveillance in the molecular era: The typened model, a joint data-sharing platform for clinical and public health laboratories

Laboratory-based surveillance, one of the pillars of monitoring infectious disease trends, relies on data produced in clinical and/or public health laboratories. Currently, diagnostic laboratories worldwide submit strains or samples to a relatively small number of reference laboratories for characterisation and typing. However, with the introduction of molecular diagnostic methods and sequencing in most of the larger diagnostic and university hospital centres in high-income countries, the distinction between diagnostic and reference/public health laboratory functions has become less clear-cut. Given these developments, new ways of networking and data sharing are needed. Assuming that clinical and public health laboratories may be able to use the same data for their own purposes when sequence-based testing and typing are used, we explored ways to develop a collaborative approach and a jointly owned database (TYPENED) in the Netherlands. The rationale was that sequence data - whether produced to support clinical care or for surveillance -can be aggregated to meet both needs. Here we describe the development of the TYPENED approach and supporting infrastructure, and the implementation of a pilot laboratory network sharing enterovirus sequences and metadata