HEVnet: A one health, collaborative, interdisciplinary network and sequence data repository for enhanced hepatitis e virus molecular typing, characterisation and epidemiological investigations

Annemieke Christine Mulder, Annelies Kroneman, Eelco Franz, Harry Vennema, Anna D. Tulen, Johanna Takkinen, Agnetha Hofhuis*, Cornelia Adlhoch, Stephan Aberle, Lorenzo Subissi, Vanessa Suin, Sofie Midgley, Tatiana Kuznetsova, Jacques Izopet, Nicole Pavio, Christine Baechlein, Sally A. Baylisa, Victor M. Corman, Mirko Fabera, Reimar JohneChristel Kamp, Juergen J. Wenzel, Suzie Coughlan, Ilaria Di Bartolo, Roberto Bruni, Anna Rita Ciccaglionea, Anna Rosa Garbuglia, Elisabetta Suffredini, Ingeborg Boxman, Boris Hogema, Wim van der Poel, Hans Zaaijera, Rita de Sousaa, Branko Velebit, Ana Avellóna, Maria Buti, Rosina Girones, Josep Quer, Frederik Widén, Heléne Norder, Kristina Nyström, Claudia Bachofen, Roland Sahli, Samreen Ijaza, Samantha Treagus, Michael Kulka, Valentina Rizzi

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

60 Citations (Scopus)

Abstract

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide. In Europe, HEV is a zoonosis transmitted via contaminated pork meat or other pork food products. Genotype 3 is the most prevalent HEV type in the animal reservoir, as well as in humans. Despite an increased incidence of hepatitis E across Europe, much remains unknown about its spread, sources and transmission routes. A One Health approach is crucial to better understand the (molecular) epidemiology of HEV. HEVnet was established in April 2017 as a network and database for sharing sequences and accompanying metadata collected from human, animal, food and environmental sources. HEVnet members working in the public health, veterinary health, food, environmental and blood safety sectors have submitted 1,615 HEV sequences from nine countries as at January 2019. Most are from humans (89%), and sequences of animal (5%), food (6%) or environmental (0.3%) origin are rare. Metadata for human sequences capture mostly sex (93%), year of birth (92%) and sampling (100%); data on region of sampling (37%) and clinical information (hospitalisation 27%, symptoms 20% or mortality 8%) are limited. HEVnet aims to expand into a global network capable of performing cross-sectoral and supranational studies, with a joint repository of molecular and epidemiological data on HEV.

Original languageEnglish
Article number1800407
JournalEurosurveillance
Volume24
Issue number10
DOIs
Publication statusPublished - 7 Mar 2019

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