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In December 2016, Public Health England investigated an outbreak of campylobacteriosis in North West England, with 69 cases in total. Epidemiological, microbiological and environmental investigations associated the illness with the consumption of unpasteurised cows' milk from Farm X, where milk was predominantly sold from a vending machine. Campylobacter was detected in milk samples which, when sequenced, were identical in sequence type as pathogens isolated from cases (Clonal Complex ST-403, Sequence Type 7432). The farm was served with a Hygiene Emergency Prohibition Order to prevent further cases. To our knowledge, this is the first outbreak of campylobacter associated with unpasteurised milk in England since 1996. Our findings highlighted several important lessons, including that the current testing regime in England for unpasteurised milk is not fit for purpose and that the required warning label should include additional wording, underscoring the risk to vulnerable groups. There has been a substantial increase in both the volume of unpasteurised milk consumed in England and the use of vending machines to sell unpasteurised milk over the last 10 years, making unpasteurised milk more readily accessible to a wider population. The evidence generated from outbreaks like this is therefore critical and should be used to influence policy development.

Since April 2015, whole genome sequencing (WGS) has been the routine test for Salmonella identification, surveillance and outbreak investigation at the national reference laboratory in England and Wales. In May 2015, an outbreak of Salmonella Enteritidis cases was detected using WGS data and investigated. UK cases were interviewed to obtain a food history and links between suppliers were mapped to produce a food chain network for chicken eggs. The association between the food chain network and the phylogeny was explored using a network comparison approach. Food and environmental samples were taken from premises linked to cases and tested for Salmonella. Within the outbreak single nucleotide polymorphism defined cluster, 136 cases were identified in the UK and 18 in Spain. One isolate from a food containing chicken eggs was within the outbreak cluster. There was a significant association between the chicken egg food chain of UK cases and phylogeny of outbreak isolates. This is the first published Salmonella outbreak to be prospectively detected using WGS. This outbreak in the UK was linked with contemporaneous cases in Spain by WGS. We conclude that UK and Spanish cases were exposed to a common source of Salmonella-contaminated chicken eggs.

In August 2015, Public Health England detected an outbreak of Shiga toxin-producing Escherichia coli (STEC) serotype O157:H7 caused by contaminated salad leaves in a mixed leaf prepacked salad product from a national retailer. The implicated leaves were cultivated at five different farms and the zoonotic source of the outbreak strain was not determined. In March 2016, additional isolates from new cases were identified that shared a recent common ancestor with the outbreak strain. A case–case study involving the cases identified in 2016 revealed that ovine exposures were associated with illness ( n = 16; AOR 8·24; 95% CI 1·55–39·74). By mapping the recent movement of sheep and lambs across the United Kingdom, epidemiological links were established between the cases reporting ovine exposures. Given the close phylogenetic relationship between the outbreak strain and the isolates from cases with ovine exposures, it is plausible that ovine faeces may have contaminated the salad leaves via untreated irrigation water or run-off from fields nearby. Timely and targeted veterinary and environmental sampling should be considered during foodborne outbreaks of STEC, particularly where ready to eat vegetables and salads are implicated.

Current methods of control recruitment for case-control studies can be slow (a particular issue for outbreak investigations), resource-intensive and subject to a range of biases. Commercial market panels are a potential source of rapidly recruited controls. Our study evaluated food exposure data from these panel controls, compared with an established reference dataset. Market panel data were collected from two companies using retrospective internet-based surveys; these were compared with reference data from the National Diet and Nutrition Survey (NDNS). We used logistic regression to calculate adjusted odds ratios to compare exposure to each of the 71 food items between the market panel and NDNS participants. We compared 2103 panel controls with 2696 reference participants. Adjusted for socio-demographic factors, exposure to 90% of foods was statistically different between both panels and the reference data. However, these differences were likely to be of limited practical importance for 89% of Panel A foods and 79% of Panel B foods. Market panel food exposures were comparable with reference data for common food exposures but more likely to be different for uncommon exposures. This approach should be considered for outbreak investigation, in conjunction with other considerations such as population at risk, timeliness of response and study resources.

In August 2015 a gastroenteritis outbreak occurred following a wedding. An outbreak investigation was undertaken and a cohort study was conducted using an online survey. Of 140 guests, 134 received the survey and 113 responded (84·3% response rate). Seventy respondents met the case definition of vomiting and/or diarrhoea within 72 h of the wedding (61·9% attack rate). Fifteen exposures were associated with illness; on stratification, all were confounded by the ham hock starter. Multivariable analysis showed a significant association with exposure to ham hock (risk ratio 6·62, 95% confidence interval 2·19–20·03). Eight guests and two catering staff submitted stool samples. All tested positive for norovirus GI-6 infection, including a food handler who had vomiting less than 48 h before the wedding. A single genotype was detected among all samples, suggesting a single source of contamination. The transmission pattern suggested point-source exposure. The most plausible cause of the outbreak was transmission from an infected food handler via contaminated food. This highlights the importance of appropriate exclusions for symptomatic food handlers. Additionally, the food handler's stool sample was submitted 7 days after symptom resolution. The potential for extended viral excretion, and the extremely low infective dose of norovirus, may mean that current exclusion guidelines are not of sufficient duration.

For outbreaks of gastrointestinal disease, rapid identification of the source is crucial to enable public health intervention and prevent further cases. Outbreak investigation comprises analyses of exposure information from cases and, if required, undertaking analytical epidemiological studies. Hypothesis generation has been reliant on empirical knowledge of exposures historically associated with a given pathogen. Epidemiology studies are resource-intensive and prone to bias, one of the reasons being the difficulties in recruiting appropriate controls. For this paper, the information from cases was compared against pre-defined background exposure information. As exemplars, three past outbreaks were used, one of common and two of rare exposures. Information from historical case trawling questionnaires was used to define background exposure having removed any exposures implicated with the outbreak. The case-background approach showed good sensitivity and specificity, identifying correctly all outbreak-related exposures. One additional exposure related to a retailer was identified and four food items where all cases had been exposed. In conclusion, the case-background method, a development of the case-case design, can be used to assist with hypothesis generation or when a case-control study may not be possible to carry out.

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 a Salmonella outbreak 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.

Background Reduced cardiorespiratory fitness (CRF) is an independent risk factor for dependency, cognitive impairment and premature mortality. High-intensity interval training (HIIT) is a proven time-efficient stimulus for improving both CRF and other facets of cardiometabolic health also known to decline with advancing age. However, the efficacy of equipment-free, unsupervised HIIT to improve the physiological resilience of older adults is not known. Methods Thirty independent, community-dwelling older adults (71(SD: 5) years) were randomised to 4 weeks (12 sessions) equipment-free, supervised (in the laboratory (L-HIIT)) or unsupervised (at home (H-HIIT)) HIIT, or a no-intervention control (CON). HIIT involved 5, 1-minute intervals of a bodyweight exercise each interspersed with 90-seconds recovery. CRF, exercise tolerance, blood pressure (BP), body composition, muscle architecture, circulating lipids and glucose tolerance were assessed at baseline and after the intervention period. Results When compared to the control group, both HIIT protocols improved the primary outcome of CRF ((via anaerobic threshold) mean difference, L-HIIT: +2.27, H-HIIT: +2.29, both p  < 0.01) in addition to exercise tolerance, systolic BP, total cholesterol, non-HDL cholesterol and m. vastus lateralis pennation angle, to the same extent. There was no improvement in these parameters in CON. There was no change in diastolic BP, glucose tolerance, whole-body composition or HDL cholesterol in any of the groups. Conclusions This is the first study to show that short-term, time-efficient, equipment-free, HIIT is able to elicit improvements in the CRF of older adults irrespective of supervision status. Unsupervised HIIT may offer a novel approach to improve the physiological resilience of older adults, combating age-associated physiological decline, the rise of inactivity and the additional challenges currently posed by the COVID-19 pandemic. Trial registration This study was registered at clinicaltrials.gov and coded: NCT03473990 .