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Detecting gastrointestinal (GI) infection transmission among men who have sex with men (MSM) in England is complicated by a lack of routine sexual behavioural data. We investigated whether gender distributions might generate signals for increased transmission of GI pathogens among MSM. We examined the percentage male of laboratory-confirmed patient-episodes for patients with no known travel history for 10 GI infections of public health interest in England between 2003 and 2013, stratified by age and region. An adult male excess was observed forShigellaspp. (annual maximum 71% male); most pronounced for those aged 25–49 years and living in London, Brighton and Manchester. An adult male excess was observed every year forEntamoeba histolytica(range 59.8–76.1% male),Giardia(53.1–57.6%) andCampylobacter(52.1–53.5%) and for a minority of years for hepatitis A (max. 69.8%) and typhoidal salmonella (max. 65.7%). This approach generated a signal for excess male episodes for six GI pathogens, including a characterised outbreak ofShigellaamong MSM. Stratified analyses by geography and age group were consistent with MSM transmission forShigella. Optimisation and routine application of this technique by public health authorities elsewhere might help identify potential GI infection outbreaks due to sexual transmission among MSM, for further investigation.

Established methods of recruiting population controls for case–control studies to investigate gastrointestinal disease outbreaks can be time consuming, resulting in delays in identifying the source or vehicle of infection. After an initial evaluation of using online market research panel members as controls in a case–control study to investigate aSalmonellaoutbreak in 2013, this method was applied in four further studies in the UK between 2014 and 2016. We used data from all five studies and interviews with members of each outbreak control team and market research panel provider to review operational issues, evaluate risk of bias in this approach and consider methods to reduce confounding and bias. The investigators of each outbreak reported likely time and cost savings from using market research controls. There were systematic differences between case and control groups in some studies but no evidence that conclusions on the likely source or vehicle of infection were incorrect. Potential selection biases introduced by using this sampling frame and the low response rate are unclear. Methods that might reduce confounding and some bias should be balanced with concerns for overmatching. Further evaluation of this approach using comparisons with traditional methods and population-based exposure survey data is recommended.

SummaryRecent cases of acute kidney injury due to Seoul hantavirus infection from exposure to wild or pet fancy rats suggest this infection is increasing in prevalence in the UK. We conducted a seroprevalence study in England to estimate cumulative exposure in at-risk groups with contact with domesticated and wild rats to assess risk and inform public health advice. From October 2013 to June 2014, 844 individual blood samples were collected. Hantavirus seroprevalence amongst the pet fancy rat owner group was 34.1% (95% CI 23·9–45·7%) compared with 3·3% (95% CI 1·6–6·0) in a baseline control group, 2·4% in those with occupational exposure to pet fancy rats (95% CI 0·6–5·9) and 1·7% with occupational exposure to wild rats (95% CI 0·2–5·9). Variation in seroprevalence across groups with different exposure suggests that occupational exposure to pet and wild rats carries a very low risk, if any. However incidence of hantavirus infection among pet fancy rat owners/breeders, whether asymptomatic, undiagnosed mild viral illness or more severe disease may be very common and public health advice needs to be targeted to this at-risk group.

Shiga-toxin producingEscherichia coli(STEC) is a pathogen that can cause bloody diarrhoea and severe complications. Cases occur sporadically but outbreaks are also common. Understanding the incubation period distribution and factors influencing it will help in the investigation of exposures and consequent disease control. We extracted individual patient data for STEC cases associated with outbreaks with a known source of exposure in England and Wales. The incubation period was derived and cases were described according to patient and outbreak characteristics. We tested for heterogeneity in reported incubation period between outbreaks and described the pattern of heterogeneity. We employed a multi-level regression model to examine the relationship between patient characteristics such as age, gender and reported symptoms; and outbreak characteristics such as mode of transmission with the incubation period. A total of 205 cases from 41 outbreaks were included in the study, of which 64 cases (31%) were from a single outbreak. The median incubation period was 4 days. Cases reporting bloody diarrhoea reported shorter incubation periods compared with cases without bloody diarrhoea, and likewise, cases aged between 40 and 59 years reported shorter incubation period compared with other age groups. It is recommended that public health officials consider the characteristics of cases involved in an outbreak in order to inform the outbreak investigation and the period of exposure to be investigated.

SUMMARYA pandemic influenza A(H1N1) 2009 outbreak in a summer school affected 117/276 (42%) students. Residential social contact was associated with risk of infection, and there was no evidence for transmission associated with the classroom setting. Although the summer school had new admissions each week, which provided susceptible students the outbreak was controlled using routine infection control measures (isolation of cases, basic hygiene measures and avoidance of particularly high-risk social events) and prompt treatment of cases. This was in the absence of chemoprophylaxis or vaccination and without altering the basic educational activities of the school. Modelling of the outbreak allowed estimation of the impact of interventions on transmission. These models and follow-up surveillance supported the effectiveness of routine infection control measures to stop the spread of influenza even in this high-risk setting for transmission.

SUMMARYWe sought to explain seasonality and other aspects ofCampylobacter jejuniepidemiology by integrating population genetic and epidemiological analysis in a large 3-year longitudinal, two-centre, population-based study. Epidemiological information was collected for 1505 isolates, which were multilocus sequence-typed. Analyses compared pathogen population structure between areas, over time, and between clinical presentations. Pooled analysis was performed with published international datasets. Subtype association with virulence was not observed. UK sites had nearly identicalC. jejunipopulations. A clade formed by ST45 and ST283 clonal complexes showed a summer peak. This clade was common in a Finnish dataset but not in New Zealand and Australian collections, countries with less marked seasonality. The UK, New Zealand and Australian collections were otherwise similar. These findings map to knownin-vitrodifferences of this clade. This identifies a target for studies to elucidate the drivers of the summer peak in humanC. jejuniinfection.

SUMMARYAn outbreak of gastroenteritis affected at least 240 persons who had eaten at a gourmet restaurant over a period of 7 weeks in 2009 in England. Epidemiological, microbiological, and environmental studies were conducted. The case-control study demonstrated increased risk of illness in those who ate from a special ‘tasting menu’ and in particular an oyster, passion fruit jelly and lavender dish (odds ratio 7·0, 95% confidence interval 1·1–45·2). Ten diners and six staff members had laboratory-confirmed norovirus infection. Diners were infected with multiple norovirus strains belonging to genogroups I and II, a pattern characteristic of molluscan shellfish-associated outbreaks. The ongoing risk from dining at the restaurant may have been due to persistent contamination of the oyster supply alone or in combination with further spread via infected food handlers or the restaurant environment. Delayed notification of the outbreak to public health authorities may have contributed to outbreak size and duration.

To estimate the incidence of Guillain-Barré syndrome (GBS) following Campylobacter jejuni infection (CI) we studied three populations where outbreaks of CI had occurred involving an estimated 8000 cases. No case of GBS was detected in the 6 months following the outbreaks in the local populations. The point estimate for the risk of GBS following CI estimated in this study was 0 in 8000 (95% confidence interval 0–3).