Paul Cleary

Background: Laboratory surveillance detected an unprecedented increase in Cryptosporidium spp. (predominantly Cryptosporidium hominis) in England and Wales in August 2023. Cases are not routinely followed up in all of England and Wales, and initial investigations identified no common exposures. Aim: To perform a retrospective case–case study investigation of the increase in Cryptosporidium spp. in England and Wales. Methods: We conducted an unmatched case–case study with 203 cases of laboratory-confirmed C. hominis and 614 comparator cases of laboratory-confirmed Campylobacter spp. reported between 14 August and 30 September 2023. We fitted a multilevel logistic regression model, with random intercepts for geographical region, to estimate adjusted odds ratios (aOR) for exposures. We present the final model as aOR and 95% confidence intervals (CI). Results: Multivariable analysis identified associations with swimming pool use (aOR: 5.3, 95% CI: 2.3–9.3), travel to Spain (aOR: 6.5, 95% CI: 3.5–12.3) and young age, with children 0–4 years having the strongest association of being a case (aOR: 3.6, 95% CI: 1.5–8.6). We also identified associations with swimming in a river, and travel to France or Türkiye, but there was low frequency of exposure among cases and comparator cases. Conclusions: Following the largest recorded increase of Cryptosporidium spp. and in particular C. hominis cases in England and Wales, we identified several exposures, suggesting that causation was likely to be multifactorial. We recommend development of a standardised questionnaire to enable rapid investigation of future case increases, which will improve existing surveillance and inform public health actions.

Background: Since May 2022, an mpox outbreak affecting primarily men who have sex with men (MSM) has occurred in numerous non-endemic countries worldwide. As MSM frequently reported multiple sexual encounters in this outbreak, reliably determining the time of infection is difficult; consequently, estimation of the incubation period is challenging. Aim: We aimed to provide valid and precise estimates of the incubation period distribution of mpox by using cases associated with early outbreak settings where infection likely occurred. Methods: Colleagues in European countries were invited to provide information on exposure intervals and date of symptom onset for mpox cases who attended a fetish festival in Antwerp, Belgium, a gay pride festival in Gran Canaria, Spain or a particular club in Berlin, Germany, where early mpox outbreaks occurred. Cases of these outbreaks were pooled; doubly censored models using the log-normal, Weibull and Gamma distributions were fitted to estimate the incubation period distribution. Results: We included data on 122 laboratory-confirmed cases from 10 European countries. Depending on the distribution used, the median incubation period ranged between 8 and 9 days, with 5th and 95th percentiles ranging from 2 to 3 and from 20 to 23 days, respectively. The shortest interval that included 50% of incubation periods spanned 8 days (4–11 days). Conclusion: Current public health management of close contacts should consider that in approximately 5% of cases, the incubation period exceeds the commonly used monitoring period of 21 days.

When SARS-CoV-2 Omicron emerged in 2021, S gene target failure enabled differentiation between Omicron and the dominant Delta variant. In England, where S gene target surveillance (SGTS) was already established, this led to rapid identification (within ca 3 days of sample collection) of possible Omicron cases, alongside real-time surveillance and modelling of Omicron growth. SGTS was key to public health action (including case identification and incident management), and we share applied insights on how and when to use SGTS.

Background: During the first wave of the influenza A(H1N1)pdm09 pandemic in England in 2009, morbidity and mortality were higher in patients of South Asian (Indian, Pakistani or Bangladeshi) ethnic minority groups.Objectives: This study aims to provide insights in the representation of this group among reported cases, indicating susceptibility and exposure.Methods: All laboratory‐confirmed cases including basic demographic and limited clinical information that were reported to the FluZone surveillance system between April and October 2009 were retrieved. Missing ethnicity data were imputed using the previously developed and validated South Asian Names and Group Recognition Algorithm (SANGRA). Differences between ethnic groups were calculated using chi‐square, log‐rank and t tests and rate ratios. Geographic clustering was compared using Ripley's K functions.Results: SANGRA identified 2447 (28%) of the total of 8748 reported cases as South Asian. South Asian cases were younger (P < .001), more often male (P = .002) and more often from deprived areas (P < .001) than cases of other ethnic groups. Time between onset of symptoms and laboratory sampling was longer in this group (P < .001), and they were less often advised antiviral treatment (P < .001), however, declined treatment less. The highest cumulative incidence was seen in the West Midlands region (32.7/10 000), London (7.0/10 000) and East of England region (5.7/10 000).Conclusions: People of South Asian ethnic groups were disproportionally affected by the first wave of the influenza pandemic in England in 2009. The findings presented contribute to further understanding of demographic, socioeconomic and ethnic factors of the outbreak and inform future influenza preparedness to ensure appropriate prevention and care.

Background: Human papillomavirus (HPV) is the main cause of cervical cancer and contributes to a number of other cancers that affect both men and women. Vaccines exist that offer protection against the most common cancer-causing HPV types. In England, a school-based vaccination programme for girls has been in place since 2008 but vaccine coverage rates have declined since its introduction. Understanding variation between schools and between local authorities may help to inform quality improvement and guide policy development and commissioning. Methods: Cross-sectional, ecological analysis of vaccine uptake among 164 schools representing 13,127 children in eight out of ten local authorities in Greater Manchester. Logistic mixed effects regression models were used to test for associations between school level factors and vaccine uptake, while allowing for variation between local authorities. Results: In multivariable mixed effects models, lower vaccination rates were associated with: increasing numbers of children eligible for vaccination; increasing proportions of children eligible for free school meals; increasing proportions of children with English as an additional language; Ofsted ‘inadequate’ ratings; Christian and Muslim faith schools; independent schools and special schools. Conclusions: Consistent with previous studies on vaccine uptake, this study identifies a number of factors that are associated with uptake of the school-based HPV vaccine programme. We also show that local authority variation remains after adjustment for the mix of schools in each area. This evidence may be used to guide vaccine providers, commissioners, and policymakers who want to increase uptake of the school-based HPV vaccine.

Background: Diarrheal disease, which affects 1 in 4 people in the United Kingdom annually, is the most common cause of outbreaks in community and health care settings. Traditional surveillance methods tend to detect point-source outbreaks of diarrhea and vomiting; they are less effective at identifying low-level and intermittent food supply contamination. Furthermore, it can take up to 9 weeks for infections to be confirmed, reducing slow-burn outbreak recognition, potentially impacting hundreds or thousands of people over wide geographical areas. There is a need to address fundamental problems in traditional diarrheal disease surveillance because of underreporting and subsequent unconfirmed infection by patients and general practitioners (GPs); varying submission practices and selective testing of samples in laboratories; limitations in traditional microbiological diagnostics, meaning that the timeliness of sample testing and etiology of most cases remains unknown; and poorly integrated human and animal surveillance systems, meaning that identification of zoonoses is delayed or missed. Objective: This study aims to detect anomalous patterns in the incidence of gastrointestinal disease in the (human) community; to target sampling; to test traditional diagnostic methods against rapid, modern, and sensitive molecular and genomic microbiology methods that identify and characterize responsible pathogens rapidly and more completely; and to determine the cost-effectiveness of rapid, modern, sensitive molecular and genomic microbiology methods. Methods: Syndromic surveillance will be used to aid identification of anomalous patterns in microbiological events based on temporal associations, demographic similarities among patients and animals, and changes in trends in acute gastroenteritis cases using a point process statistical model. Stool samples will be obtained from patients’ consulting GPs, to improve the timeliness of cluster detection and characterize the pathogens responsible, allowing health protection professionals to investigate and control outbreaks quickly, limiting their size and impact. The cost-effectiveness of the proposed system will be examined using formal cost-utility analysis to inform decisions on national implementation. Results: The project commenced on April 1, 2013. Favorable approval was obtained from the Research Ethics Committee on June 15, 2015, and the first patient was recruited on October 13, 2015, with 1407 patients recruited and samples processed using traditional laboratory techniques as of March 2017. Conclusions: The overall aim of this study is to create a new One Health paradigm for detecting and investigating diarrhea and vomiting in the community in near-real time, shifting from passive human surveillance and management of laboratory-confirmed infection toward an integrated, interdisciplinary enhanced surveillance system including management of people with symptoms. International Registered Report Identifier (IRRID): DERR1-10.2196/13941