In November 2019, an outbreak of Shiga toxin-producing Escherichia coli O157:H7 was detected in South Yorkshire, England. Initial investigations established consumption of milk from a local dairy as a common exposure. A sample of pasteurised milk tested the next day failed the phosphatase test, indicating contamination of the pasteurised milk by unpasteurised (raw) milk. The dairy owner agreed to immediately cease production and initiate a recall. Inspection of the pasteuriser revealed a damaged seal on the flow divert valve. Ultimately, there were 21 confirmed cases linked to the outbreak, of which 11 (52%) were female, and 12/21 (57%) were either <15 or >65 years of age. Twelve (57%) patients were treated in hospital, and three cases developed haemolytic uraemic syndrome. Although the outbreak strain was not detected in the milk samples, it was detected in faecal samples from the cattle on the farm. Outbreaks of gastrointestinal disease caused by milk pasteurisation failures are rare in the UK. However, such outbreaks are a major public health concern as, unlike unpasteurised milk, pasteurised milk is marketed as ‘safe to drink’ and sold to a larger, and more dispersed, population. The rapid, co-ordinated multi-agency investigation initiated in response to this outbreak undoubtedly prevented further cases.

Foodborne and waterborne gastrointestinal infections and their associated outbreaks are preventable, yet still result in significant morbidity, mortality and revenue loss. Many enteric infections demonstrate seasonality, or annual systematic periodic fluctuations in incidence, associated with climatic and environmental factors. Public health professionals use statistical methods and time series models to describe, compare, explain and predict seasonal patterns. However, descriptions and estimates of seasonal features, such as peak timing, depend on how researchers define seasonality for research purposes and how they apply time series methods. In this review, we outline the advantages and limitations of common methods for estimating seasonal peak timing. We provide recommendations improving reporting requirements for disease surveillance systems. Greater attention to how seasonality is defined, modelled, interpreted and reported is necessary to promote reproducible research and strengthen proactive and targeted public health policies, intervention strategies and preparedness plans to dampen the intensity and impacts of seasonal illnesses.

Established methods of recruiting population controls for case–control studies in infectious disease outbreak investigations are resource- and time-intensive, and are often subject to bias. The online panel have recently gained interest as an easy and timely method to select controls. We examined the feasibility, suitability and reliability of using an online panel to select controls for case–control studies as part of investigations of diffuse food and waterborne outbreaks. In January 2019, we deployed a web survey by email to the 277 members of a non-probabilistic online panel in Lower Saxony, Germany. We questioned them on basic sociodemographic characteristics and eating habits. They were frequency matched to cases on sex and age. Their food exposures were compared to those of traditionally recruited controls of four historical case–controls studies, which successfully investigated food and waterborne outbreaks. We used logistic regressions to assess the association between the food exposures and the disease (odds ratios). The use of a control panel successfully led to the identification of the food items in three of the four historical outbreak investigations, and their recruitment benefitted from increased speed and limited costs. Timely outbreak investigations would enable rapidly implementing control measures. We recommend the further evaluation of using panellists as controls in parallel case–control studies and case–panel studies.

Information on the kinetics of the serum antibody response to infection with Yersinia enterocolitica is essential to allow the estimation and comparison of seroconversion rates in a diversity of pools of cross-sectional serum antibody measurements. Data from 94 patients with acute enteritis caused by Yersinia infection were used. The follow-up period for the longitudinal study was 36 months, addressed by questionnaire. An indirect enzyme-linked immunosorbent assay method was adapted to determine the concentration of antibodies against Y. enterocolitica in human sera. A mathematical within-host model was used to describe the interaction between pathogen and immune system and the waning of immunity after clearing of the pathogen. All observed antibodies (IgG, IgM, IgA) reached peak levels shortly after infection and then decayed slowly indicating that the median levels decreased only little during the observation period. Estimated maximum peak antibody levels were highest in IgG. Seroresponse curves of all antibodies showed large individual variation between patients. There was no apparent pattern of variation with age, nor any notable difference between genders. Estimated half-times were very long for all antibodies, and their posterior distributions were highly skewed. IgA appeared to have the most persistent antibody response, compared with IgG and IgM. Median peak levels of all three antibodies were similar. There was no significance found between peak antibody levels and severity of symptoms of gastrointestinal infection and severity of joint pain. Our findings allow the use of cross-sectional serum antibody measurements as biomarkers, to estimate seroconversion rates. Such seroincidence estimates include asymptomatic seroconversions, thereby avoiding under-reporting, and allows the comparison of infection pressures among countries, independent of their healthcare and surveillance systems.

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.

The associations with weather and bathing water quality on infectious intestinal disease (IID) were investigated using data from two Scottish NHS Board areas. Monthly counts of viral and non-viral gastrointestinal infections were modelled as a smooth function of temperature, relative humidity and average monthly counts of faecal indicator organisms, respectively, adjusting for season and long-term trend effects. Strong seasonal patterns were observed for each group of pathogens. Peak viral gastrointestinal infection was in May while that of non-viral gastrointestinal infections was in July. A statistically significant negative association existed between weather (temperature and humidity) and viral infection. Average levels of non-viral gastrointestinal infections increased as temperature and relative humidity increased. Increasing levels of faecal indicator organisms in bathing waters were also associated with an increase in the average number of viral and non-viral gastrointestinal infections at the ecological level. Future climate change and prolonged precipitation events may result in increasing levels of faecal indicator organisms in bathing waters leading to likely increases in IIDs.

A retrospective cross-sectional survey of self-reported acute gastrointestinal infection (AGI) incidence in the community was performed in Poland, from December 2008 to November 2009. The aim of the study was to estimate the magnitude and distribution of self-reported AGI, in order to calibrate the routine AGI surveillance system in Poland. The study population were randomly selected residents of all Polish regions, having a fixed telephone line. An equal number of telephone interviews were collected each month, requesting the interviewee to identify gastrointestinal symptoms that had occurred in the previous 4 weeks. The international AGI case definition was used. In total 3583 complete interviews were obtained. The compliance ratio was 26%. Of 3583 respondents, 240 (6·7%) individuals fulfilled the AGI case definition. The annualized incidence of acute gastroenteritis was 0·9/person-year (95% confidence interval 0·8–1·0). Comparison of the obtained annual AGI estimate (33·3 million infections) with the number of cases reported to national surveillance during the corresponding period (73 512), yielded an underreporting factor of 453 cases occurring in the community for each reported case. Of the 240 AGI cases, 30·4% consulted a general practitioner, and 4·6% were admitted to hospital. Samples for microbiological confirmation were collected from four (1·6%) cases. This first population-based study in eastern Europe has confirmed that AGI places a high burden on Polish society, which is underestimated by national surveillance data. Efforts are necessary to improve AGI reporting and diagnostic practices in order to increase the effectiveness of the Polish surveillance system in detecting threats related to new AGI pathogens, new routes of transmission or the potential for international spread.