Eurosurveillance - Volume 24, Issue 31, 01 August 2019

Campylobacter is the main cause of bacterial gastroenteritis worldwide. The main transmission route is through consumption of food contaminated with Campylobacter species or contact with infected animals. In Latvia, the prevalence of campylobacteriosis is reported to be low (4.6 cases per 100,000 population in 2016).

To determine prevalence, species spectrum and antimicrobial resistance (AMR) of Campylobacter spp. in Latvia, using data from various livestock and human clinical samples.

We analysed data of Campylobacter microbiological monitoring and AMR (2008 and 2014–16) in Latvia. Data from broilers, poultry, pigs, calves and humans were used to determine prevalence of Campylobacter. Additionally, 45 different origin isolates (22 human) were sequenced on the Illumina MiSeq platform; for each isolate core genome multilocus sequence typing was used and relevant antimicrobial resistance mechanisms were identified.

Overall, Campylobacter prevalence in was 83.3% in pigs, 50.2% in broilers, 16.1% in calves and 5.3% in humans; C. jejuni was the predominant species in all sources except pigs where C. coli was main species. High level of resistance in Campylobacter were observed against fluoroquinolones, tetracycline and streptomycin, in most of sequenced isolates genetic determinants of relevant AMR profiles were identified.

In Latvia, prevalence of Campylobacter in livestock is high, especially in pigs and broilers; prevalence in poultry and humans were lower than in other European countries. AMR analysis reveals increase of streptomycin and tetracycline resistant broiler origin C. jejuni strains. WGS demonstrates a high compliance between resistance phenotype and genotype for quinolones and tetracyclines.

Influenza immunisation is recommended for elderly people each season. The influenza vaccine effectiveness (IVE) varies annually due to influenza viruses evolving and the vaccine composition.

To estimate, in inpatients ≥ 60 years old, the 2017/18 trivalent IVE, overall, by vaccine type and by strain. The impact of vaccination in any of the two previous seasons (2016/17 and 2015/16) on current (2017/18) IVE was also explored.

This was a multicentre prospective observational study within the Valencia Hospital Surveillance Network for the Study of Influenza and Respiratory Viruses Disease (VAHNSI, Spain). The test-negative design was applied taking laboratory-confirmed influenza as outcome and vaccination status as main exposure. Information about potential confounders was obtained from clinical registries and/or by interviewing patients; vaccine information was only ascertained by registries.

Overall, 2017/18 IVE was 9.9% (95% CI: −15.5 to 29.6%), and specifically, 48.3% (95% CI: 13.5% to 69.1%), −29.9% (95% CI: −79.1% to 5.8%) and 25.7% (95% CI: −8.8% to 49.3%) against A(H1N1)pdm09, A(H3N2) and B/Yamagata lineage, respectively. For the adjuvanted and non-adjuvanted vaccines, overall IVE was 10.0% (95% CI: −24.4% to 34.9%) and 7.8% (95% CI: −23.1% to 31.0%) respectively. Prior vaccination significantly protected against influenza B/Yamagata lineage (IVE: 50.2%; 95% CI: 2.3% to 74.6%) in patients not vaccinated in the current season. For those repeatedly vaccinated against influenza A(H1N1)pdm09, IVE was 46.4% (95% CI: 6.8% to 69.2%).

Our data revealed low vaccine effectiveness against influenza in hospitalised patients ≥60 years old in 2017/18. Prior vaccination protected against influenza A(H1N1)pdm09 and B/Yamagata-lineage.

In the United Kingdom (UK), in recent influenza seasons, children are offered a quadrivalent live attenuated influenza vaccine (LAIV4), and eligible adults mainly trivalent inactivated vaccine (TIV).

To estimate the UK end-of-season 2017/18 adjusted vaccine effectiveness (aVE) and the seroprevalence in England of antibodies against influenza viruses cultured in eggs or tissue.

This observational study employed the test-negative case–control approach to estimate aVE in primary care. The population-based seroprevalence survey used residual age-stratified samples.

Influenza viruses A(H3N2) (particularly subgroup 3C.2a2) and B (mainly B/Yamagata/16/88-lineage, similar to the quadrivalent vaccine B-virus component but mismatched to TIV) dominated. All-age aVE was 15% (95% confidence interval (CI): −6.3 to 32) against all influenza; −16.4% (95% CI: −59.3 to 14.9) against A(H3N2); 24.7% (95% CI: 1.1 to 42.7) against B and 66.3% (95% CI: 33.4 to 82.9) against A(H1N1)pdm09. For 2–17 year olds, LAIV4 aVE was 26.9% (95% CI: −32.6 to 59.7) against all influenza; −75.5% (95% CI: −289.6 to 21) against A(H3N2); 60.8% (95% CI: 8.2 to 83.3) against B and 90.3% (95% CI: 16.4 to 98.9) against A(H1N1)pdm09. For ≥ 18 year olds, TIV aVE against influenza B was 1.9% (95% CI: −63.6 to 41.2). The 2017 seroprevalence of antibody recognising tissue-grown A(H3N2) virus was significantly lower than that recognising egg-grown virus in all groups except 15–24 year olds.

Overall aVE was low driven by no effectiveness against A(H3N2) possibly related to vaccine virus egg-adaption and a new A(H3N2) subgroup emergence. The TIV was not effective against influenza B. LAIV4 against influenza B and A(H1N1)pdm09 was effective.

A variety of airline passenger data sources are used for modelling the international spread of infectious diseases. Questions exist regarding the suitability and validity of these sources.

We conducted a systematic review to identify the sources of airline passenger data used for these purposes and to assess validation of the data and reproducibility of the methodology.

Articles matching our search criteria and describing a model of the international spread of human infectious disease, parameterised with airline passenger data, were identified. Information regarding type and source of airline passenger data used was collated and the studies’ reproducibility assessed.

We identified 136 articles. The majority (n = 96) sourced data primarily used by the airline industry. Governmental data sources were used in 30 studies and data published by individual airports in four studies. Validation of passenger data was conducted in only seven studies. No study was found to be fully reproducible, although eight were partially reproducible.

By limiting the articles to international spread, articles focussed on within-country transmission even if they used relevant data sources were excluded. Authors were not contacted to clarify their methods. Searches were limited to articles in PubMed, Web of Science and Scopus.

We recommend greater efforts to assess validity and biases of airline passenger data used for modelling studies, particularly when model outputs are to inform national and international public health policies. We also recommend improving reporting standards and more detailed studies on biases in commercial and open-access data to assess their reproducibility.