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The aim of this work was the establishment of a national laboratory sentinel surveillance service for human clinical Campylobacter in Ireland. This included detailed genomic molecular epidemiology of Campylobacter for 2019. For February-December 2019, 24 clinical microbiology laboratories in Ireland submitted all PCR/culture-positive clinical Campylobacter spp. specimens to Public Health Laboratory (PHL) Dublin one week out of every four. Antimicrobial susceptibility testing (AST) according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) criteria was carried out for Campylobacter spp. isolates for ciprofloxacin, tetracycline and erythromycin. Batch whole genome sequencing (WGS) was carried out on cultures and analysis was performed to determine species, genotype, identify antimicrobial resistance (AMR) and virulence determinants and identify clusters. A total of 75 isolates and 366 PCR-positive stools were received, and 277 isolates recovered (55.7% recovery from stools). Of 257 isolates characterized by WGS, 86.4% (n = 222) were Campylobacter jejuni, 11.7% (n = 30) Campylobacter coli and 1.9% (n = 5) Campylobacter lari. There were 20 clonal complexes with ST-21 clonal complex most prevalent at 26.8% (n = 69). 50.5% (n = 140) of isolates were susceptible to all three antimicrobials tested. 39.3% (n = 109) isolates were ciprofloxacin resistant, 26.3% (n = 73) tetracycline resistant and two isolates erythromycin resistant. Congruence between phenotypic and genotypic AST was observed. There was 95.9% and 95.6% sensitivity and specificity for WGS to predict ciprofloxacin sensitivity and 98.6% and 99.5% sensitivity and specificity for WGS to predict tetracycline sensitivity. Virulence factors flaA, racR, ciaB and cdtB were detected in all isolates. WGS identified 31 potential clusters for public health alert. This sentinel surveillance of human campylobacteriosis in Ireland establishes the basis for a national reference service. Linking with other partners in a 'One Health' framework will help us better understand sources of infection to reduce disease burden and the threat of AMR.

Highlights • Very low antiviral resistance in Irish 2018/2019 influenza season • Supports current antiviral use • Continued molecular neuraminidase surveillance essential for resistance emergence • Surveillance also useful for monitoring vaccine effectiveness • Mutations associated with reduced antibody effectiveness detected, Neuraminidase inhibitor (NAI) resistance levels globally are currently low. However, as antivirals are increasingly being used, but even in the absence of selective pressure, resistance may increase or emerge. The neuraminidase (NA) genes from influenza viruses from the Irish 2018/2019 season were sequenced: 1/144 (0.7%) A(H1N1)pdm09 sequences harboured a substitution associated with highly-reduced susceptibility to NAIs. The very low NAI resistance we describe supports current Irish NAI use recommendations. However, continued monitoring is essential. NA characterisation also identified substitutions associated with reduced antibody effectiveness, thereby highlighting the potential of NA sequence surveillance as an additional tool for investigating influenza vaccine effectiveness (VE).

Shiga toxigenic Escherichia coli (STEC) are pathogenic E. coli that cause infectious diarrhoea. In some cases infection may be complicated by renal failure and death. The incidence of human infection with STEC in Ireland is the highest in Europe. The objective of the study was to examine the spatial incidence of human STEC infection in a region of Ireland with significantly higher rates of STEC incidence than the national average and to identify possible risk factors of STEC incidence at area level. Anonymised laboratory records (n = 379) from 2009 to 2015 were obtained from laboratories serving three counties in the West of Ireland. Data included location and sample date. Population and electoral division (ED) data were obtained from the Irish 2011 Census of Population. STEC incidence was calculated for each ED (n = 498) and used to map hotspots/coldspots using the Getis-Ord Gi* spatial statistic and significant spatial clustering using the Anselin's Local Moran's I statistic. Multivariable regression analysis was used to consider the importance of a number of potential predictors of STEC incidence. Incidence rates for the seven-year period ranged from 0 to 10.9 cases per 1000. A number of areas with significant local clustering of STEC incidence as well as variation in the spatial distribution of the two main serogroups associated with disease in the region i.e. O26 and O157 were identified. Cattle density was found to be a statistically significant predictor of STEC in the region. GIS analysis of routine data indicates that cattle density is associated STEC infection in this high incidence region. This finding points to the importance of agricultural practices for human health and the importance of a “one-health” approach to public policy in relation to agriculture, health and environment. Thanks to the Division of Clinical Microbiology for their help in particular Belinda Hanahoe. This work was funded through an Irish Research Council (GOIPD/2015/610) Government of Ireland Postdoctoral Fellowship. Icons in graphical abstract made by Freepik (www.freepik.com) from Flaticon (www.flaticon.com). Flaticon is licensed by Creative Commons BY 3.0. peer-reviewed 2020-05-12

International audience; Invasive meningococcal disease surveillance in Europe combines isolate characterisation and epidemiological data to support public health intervention. A representative European Meningococcal Strain Collection (EMSC) of IMD isolates was obtained, and whole genome sequenced to characterise 799 EMSC isolates from the epidemiological year July 2011-June 2012. To establish a genome library (GL), the isolate information was deposited in the pubMLST.org/neisseria database. Genomes were curated and annotated at 2,429 meningococcal loci, including those defining clonal complex, capsule, antigens, and antimicrobial resistance. Most genomes contained genes encoding B (n = 525; 65.7%) or C (n = 163; 20.4%) capsules; isolates were genetically highly diverse, with >20 genomic lineages, five of which comprising 60.7% (n = 485) of isolates. There were >350 antigenic fine-types: 307 were present once, the most frequent (P1.7-2,4:F5-1) comprised 8% (n = 64) of isolates. Each genome was characterised for Bexsero Antigen Sequence Typing (BAST): 25.5% (n = 204) of isolates contained alleles encoding the fHbp and/or the PorA VR1 vaccine component, but most genomes (n = 513; 64.2%) did not contain the NadA component. EMSC-GL will support an integrated surveillance of disease-associated genotypes in Europe, enabling the monitoring of hyperinvasive lineages, outbreak identification, and supporting vaccine programme implementation.

In this study, New Delhi metallo-beta-lactamase (NDM)-producing Enterobacteriaceae were identified in Irish recreational waters and sewage. Indistinguishable NDM-producing Escherichia coli by pulsed-field gel electrophoresis were isolated from sewage, a fresh water stream and a human source. NDM-producing Klebsiella pneumoniae isolated from sewage and seawater in the same area were closely related to each other and to a human isolate. This raises concerns regarding the potential for sewage discharges to contribute to the spread of carbapenemase-producing Enterobacteriaceae.

To the editor: We concur with Anderson et al. [1] that estimates of the coverage of the protection elicited by novel meningococcal protein vaccine formulations are dependent on knowledge of cross-reactivity. Indeed, we stressed this point in our penultimate paragraph of our article [2], where we referenced the surrogate assays developed by two companies to address this issue for their particular formulations.

Background In September, 2015, the meningococcal group B vaccine (Bexsero, GlaxoSmithKline) was introduced into the UK childhood immunisation schedule. Prelicensure coverage estimates used Meningococcal Antigen Typing System (MATS) to determine phenotype and function of circulating meningococci. Using whole-genome sequencing, we aimed to perform rapid, scalable, high-resolution analysis of peptide vaccine antigens in disease-causing meningococci before and after vaccine implementation. Methods All culture-confirmed invasive meningococcal disease isolates from July 1, 2010, to June 30, 2016, from the UK underwent whole-genome sequencing (n=2994), representing 56·7% of cases reported to Public Health England. Genomes were hosted on the PubMLST database. The Bexsero Antigen Sequence Type (BAST) scheme was used to catalogue antigenic variants for comparison with the Bexsero type, BAST-1 (fHbp:1, NHBA:2, NadA:8, PorA VR1:7-2, PorA VR2:4). Statistical analysis was performed with R software (v3.2.4). Findings Complete BASTs were obtained for 2915 isolates (97·4%). Within the fHbp family 1, variant 1 was only present in 105 (3·5%) of 2994 isolates. Variant 4 dominated since 2010–11 in BASTs 220, 226, and 229. From 2013–14 onwards, family 2 variants were more frequent than family 1 variants. NHBA variant 2 decreased from 373 (15·3%) of 2441 prevaccine isolates to 45 (9·4%) of 479 postvaccine isolates (p=0·001). The most common variant was 29 (557/2994). NadA was absent in 2049 (70·1%) of 2921 isolates. PorA VR2 had 106 variants, most frequently variants 2 (n=542), 9 (350), and 4 (333). Genotypic matches to BAST-1 (≥1 antigen) decreased from 30·4% (167/550) to 15·5% (83/536) over a 6 year period. Coverage including cross-reactive antigens was 60·2–69·0%. Genotype–phenotype modelling estimated coverage of 62·1% (95% CI 60·9–63·3), with no significant change before or after vaccine implementation. Interpretation Recent clonal expansion of South American/UK serogroup W strain accounts for many antigenic changes, such as the increase in family 2 fHbp and NHBA variant 29. Cross-reactivity within the fHbp family 1 is a key determinant of vaccine immunogenicity. MATS coverage estimates of 73% (95% CI 57–87) were key to policy decisions for introduction of the vaccine in the UK. Analysis of recent disease isolates with genomic and genotype–phenotype correlations suggests that coverage estimates are lower but within the limits of previous MATS studies. Funding Wellcome Trust.