Eurosurveillance - Volume 23, Issue 37, 13 September 2018

Understanding enterovirus D68 (EV-D68) circulation patterns as well as risk factors for severe respiratory and neurological illness is important for developing preventive strategies. Methods: Between 2010 and 2016, 11,132 respiratory specimens from hospitalised patients in Lyon, France, were screened for EV-D68 by PCR. Phylogenetic relationships of the viral-protein-1 sequences were reconstructed using maximum-likelihood and Bayesian-Markov-Chain-Monte-Carlo approaches. Results: Overall, 171 infections with a biennial pattern were detected, including seven, one, 55, none, 42, one and 65 cases annually during 2010–16. Children (< 16 years-old; n = 150) were mostly affected and 71% (n = 121) of the total patients were under 5 years-old. In 146 patients with medical reviews, 73% (n = 107) presented with acute respiratory distress. Among paediatric patients with medical reviews (n = 133), 55% (n=73) had an asthma/wheezing history, while among adults (n = 13), 11 had underlying diseases. In total, 45 patients had severe infections and 28 patients needed intensive care unit stays. No acute flaccid myelitis (AFM) was detected. We found genotypes A, B1, B2 B3 and D circulating, and no associations between these and clinical presentations. During the study, new genotypes continuously emerged, being replaced over time. We estimated that ancestors of currently circulating genotypes emerged in the late-1990s to 2010. Rises of the EV-D68 effective population size in Lyon coincided with infection upsurges. Phylogenetic analyses showed ongoing diversification of EV-D68 worldwide, coinciding with more infections in recent years and increases of reported AFM paediatric cases. Conclusions: Reinforcement of diagnostic capacities and clinical-based surveillance of EV-D68 infections is needed in Europe to assess the EV-D68 burden.

HAVNet 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.