Genomic analysis of an outbreak of Shiga toxin-producing Escherichia coli O183:H18 in the United Kingdom, 2023.

In June 2023, UKHSA surveillance systems detected an outbreak of severe gastrointestinal symptoms caused by a rare serotype of Shiga toxin-producing Escherichia coli, STEC O183:H18. There were 26 cases aged 6 months to 74 years (42 % cases were aged 0-9 years), distributed across the UK with onset dates range between 22 May 2023 and 4 July 2023. The epidemiological and food chain investigations were inconclusive, although meat products made from beef mince were implicated as a potential vehicle. The outbreak strain belonged to sequence type (ST) 657 and harboured a Shiga toxin (stx) subtype stx2a located on a prophage that was unique in the UKHSA stx-encoding bacteriophage database. Plasmid encoded, putative virulence genes subA, ehxA, saa, iha, lpfA and iss were detected, however, the established STEC virulence genes involved in attachment to the gut mucosa (eae and aggR) were absent. The acquisition of stx across the global population structure of ST657 appeared to correspond with the presence of subA, ehxA, saa, iha, lpfA and iss. During the outbreak investigation, we used long read sequencing to characterise the plasmid and prophage content of this atypical STEC, to look for evidence to explain its recent emergence. Although we were unable to determine source and transmission route of the outbreak strain, the genomic analysis revealed potential clues as to how novel strains for STEC evolve. With the implementation of PCR capable of detecting all STEC, and genome sequencing for typing and virulence profiling, we have the tools to enable us to monitor the changing landscape of STEC. Improvements in the standardised collection of epidemiological data and trace-back strategies within the food industry, will ensure we have a surveillance system capable of alerting us to emerging threats to public health.

Salmonella Saintpaul outbreak associated with cantaloupe consumption, the United Kingdom and Portugal, September to November 2023.

In September 2023, the UK Health Security Agency identified cases of Salmonella Saintpaul distributed across England, Scotland, and Wales, all with very low genetic diversity. Additional cases were identified in Portugal following an alert raised by the United Kingdom. Ninety-eight cases with a similar genetic sequence were identified, 93 in the United Kingdom and 5 in Portugal, of which 46% were aged under 10 years. Cases formed a phylogenetic cluster with a maximum distance of six single nucleotide polymorphisms (SNPs) and average of less than one SNP between isolates. An outbreak investigation was undertaken, including a case-control study. Among the 25 UK cases included in this study, 13 reported blood in stool and 5 were hospitalized. One hundred controls were recruited via a market research panel using frequency matching for age. Multivariable logistic regression analysis of food exposures in cases and controls identified a strong association with cantaloupe consumption (adjusted odds ratio: 14.22; 95% confidence interval: 2.83-71.43; p-value: 0.001). This outbreak, together with other recent national and international incidents, points to an increase in identifications of large outbreaks of Salmonella linked to melon consumption. We recommend detailed questioning and triangulation of information sources to delineate consumption of specific fruit varieties during Salmonella outbreaks.

Genomic epidemiology of the clinically dominant clonal complex 1 in the Listeria monocytogenes population in the UK.

Listeria monocytogenes is a food-borne pathogen, typically affecting the elderly, immunocompromised patients and pregnant women. The aim of this study was to determine the population structure of L. monocytogenes clonal complex 1 (CC1) in the UK and describe the genomic epidemiology of this clinically significant CC. We interrogated a working dataset of 4073 sequences of L. monocytogenes isolated between January 2015 and December 2020 from human clinical specimens, food and/or food-production environments. A minimum spanning tree was reconstructed to determine the population structure of L. monocytogenes in the UK. Subsequent analysis focused on L. monocytogenes CC1, as the cause of the highest proportion of invasive listeriosis in humans. Sequencing data was integrated with metadata on food and environmental isolates, and information from patient questionnaires, including age, sex and clinical outcomes. All isolates either belonged to lineage I (n=1299/4073, 32%) or lineage II (n=2774/4073, 68%), with clinical isolates from human cases more likely to belong to lineage I (n=546/928, 59%) and food isolates more likely to belong to lineage II (n=2352/3067, 77%). Of the four largest CCs, CC1 (n=237) had the highest proportion of isolates from human cases of disease (CC1 n=160/237, 67.5 %; CC121 n=13/843, 2 %; CC9 n=53/360, 15 %; CC2 n=69/339, 20%). Within CC1, most cases were female (n=95/160, 59%, P=0.01771) and the highest proportion of cases were in people >60 years old (39/95, 41%, P=1.314×10-6) with a high number of them aged 20-39 years old (n=35/95, 37%) most linked to pregnancy-related listeriosis (n=29/35, 83%). Most of the male cases were in men aged over 60 years old (40/65, 62%), and most of the fatal cases in both males and females were identified in this age group (42/55, 76%). Phylogenetic analysis revealed 23 5 SNP single linkage clusters comprising 80/237 (34 %) isolates with cluster sizes ranging from 2 to 19. Five 5 SNP clusters comprised isolates from human cases and an implicated food item. Expanding the analysis to 25 SNP single linkage clusters resolved an additional two clusters linking human cases to a potential food vehicle. Analysis of demographic and clinical outcome data identified CC1 as a clinically significant cause of invasive listeriosis in the elderly population and in women of child-bearing age. Phylogenetic analysis revealed the population structure of CC1 in the UK comprised small, sparsely populated genomic clusters. Only clusters containing isolates from an implicated food vehicle, or food processing or farming environments, were resolved, emphasizing the need for clinical, food and animal-health agencies to share sequencing data in real time, and the importance of a One Health approach to public-health surveillance of listeriosis.

Comparison of statistical approaches to predicting norovirus laboratory reports before and during COVID-19: insights to inform public health surveillance.

Social distancing interrupted transmission patterns of contact-driven infectious agents such as norovirus during the Covid-19 pandemic. Since routine surveillance of norovirus was additionally disrupted during the pandemic, traditional naïve forecasts that rely only on past public health surveillance data may not reliably represent norovirus activity. This study investigates the use of statistical modelling to predict the number of norovirus laboratory reports in England 4-weeks ahead of time before and during Covid-19 pandemic thus providing insights to inform existing practices in norovirus surveillance in England. We compare the predictive performance from three forecasting approaches that assume different underlying structure of the norovirus data and utilized various external data sources including mobility, air temperature and relative internet searches (Time Series and Regularized Generalized Linear Model, and Quantile Regression Forest). The performance of each approach was evaluated using multiple metrics, including a relative prediction error against the traditional naive forecast of a five-season mean. Our data suggest that all three forecasting approaches improve predictive performance over the naïve forecasts, especially in the 2020/21 season (30-45% relative improvement) when the number of norovirus reports reduced. The improvement ranged from 7 to 22% before the pandemic. However, performance varied: regularized regression incorporating internet searches showed the best forecasting score pre-pandemic and the time series approach achieved the best results post pandemic onset without external data. Overall, our results demonstrate that there is a significant value for public health in considering the adoption of more sophisticated forecasting tools, moving beyond traditional naïve methods, and utilizing available software to enhance the precision and timeliness of norovirus surveillance in England.

Haemolytic uraemic syndrome in children England, Wales, Northern Ireland, and Ireland: A prospective cohort study.

Haemolytic uraemic syndrome (HUS) caused by infection with Shiga toxin-producing Escherichia coli (STEC) is a relatively rare but potentially fatal multisystem syndrome clinically characterised by acute kidney injury. This study aimed to provide robust estimates of paediatric HUS incidence in England, Wales, Northern Ireland, and the Republic of Ireland by using data linkage and case reconciliation with existing surveillance systems, and to describe the characteristics of the condition. Between 2011 and 2014, 288 HUS patients were included in the study, of which 256 (89.5%) were diagnosed as typical HUS. The crude incidence of paediatric typical HUS was 0.78 per 100,000 person-years, although this varied by country, age, gender, and ethnicity. The majority of typical HUS cases were 1 to 4 years old (53.7%) and female (54.0%). Clinical symptoms included diarrhoea (96.5%) and/or bloody diarrhoea (71.9%), abdominal pain (68.4%), and fever (41.4%). Where STEC was isolated (59.3%), 92.8% of strains were STEC O157 and 7.2% were STEC O26. Comparison of the HUS case ascertainment to existing STEC surveillance data indicated an additional 166 HUS cases were captured during this study, highlighting the limitations of the current surveillance system for STEC for monitoring the clinical burden of STEC and capturing HUS cases.

Understanding the impact of the COVID-19 pandemic response on GI infection surveillance trends in England, January 2020-April 2022.

Stepwise non-pharmaceutical interventions and health system changes implemented as part of the COVID-19 response have had implications on the incidence, diagnosis, and reporting of other communicable diseases. Here, we established the impact of the COVID-19 outbreak response on gastrointestinal (GI) infection trends using routinely collected surveillance data from six national English laboratory, outbreak, and syndromic surveillance systems using key dates of governmental policy to assign phases for comparison between pandemic and historic data. Following decreases across all indicators during the first lockdown (March-May 2020), bacterial and parasitic pathogens associated with foodborne or environmental transmission routes recovered rapidly between June and September 2020, while those associated with travel and/or person-to-person transmission remained lower than expected for 2021. High out-of-season norovirus activity was observed with the easing of lockdown measures between June and October 2021, with this trend reflected in laboratory and outbreak systems and syndromic surveillance indicators. Above expected increases in emergency department (ED) attendances may have reflected changes in health-seeking behaviour and provision. Differential reductions across specific GI pathogens are indicative of the underlying routes of transmission. These results provide further insight into the drivers for transmission, which can help inform control measures for GI infections.

Predicting Norovirus in England Using Existing and Emerging Syndromic Data: Infodemiology Study.

BACKGROUND: Norovirus is associated with approximately 18% of the global burden of gastroenteritis and affects all age groups. There is currently no licensed vaccine or available antiviral treatment. However, well-designed early warning systems and forecasting can guide nonpharmaceutical approaches to norovirus infection prevention and control. OBJECTIVE: This study evaluates the predictive power of existing syndromic surveillance data and emerging data sources, such as internet searches and Wikipedia page views, to predict norovirus activity across a range of age groups across England. METHODS: We used existing syndromic surveillance and emerging syndromic data to predict laboratory data indicating norovirus activity. Two methods are used to evaluate the predictive potential of syndromic variables. First, the Granger causality framework was used to assess whether individual variables precede changes in norovirus laboratory reports in a given region or an age group. Then, we used random forest modeling to estimate the importance of each variable in the context of others with two methods: (1) change in the mean square error and (2) node purity. Finally, these results were combined into a visualization indicating the most influential predictors for norovirus laboratory reports in a specific age group and region. RESULTS: Our results suggest that syndromic surveillance data include valuable predictors for norovirus laboratory reports in England. However, Wikipedia page views are less likely to provide prediction improvements on top of Google Trends and Existing Syndromic Data. Predictors displayed varying relevance across age groups and regions. For example, the random forest modeling based on selected existing and emerging syndromic variables explained 60% variance in the ≥65 years age group, 42% in the East of England, but only 13% in the South West region. Emerging data sets highlighted relative search volumes, including "flu symptoms," "norovirus in pregnancy," and norovirus activity in specific years, such as "norovirus 2016." Symptoms of vomiting and gastroenteritis in multiple age groups were identified as important predictors within existing data sources. CONCLUSIONS: Existing and emerging data sources can help predict norovirus activity in England in some age groups and geographic regions, particularly, predictors concerning vomiting, gastroenteritis, and norovirus in the vulnerable populations and historical terms such as stomach flu. However, syndromic predictors were less relevant in some age groups and regions likely due to contrasting public health practices between regions and health information-seeking behavior between age groups. Additionally, predictors relevant to one norovirus season may not contribute to other seasons. Data biases, such as low spatial granularity in Google Trends and especially in Wikipedia data, also play a role in the results. Moreover, internet searches can provide insight into mental models, that is, an individual's conceptual understanding of norovirus infection and transmission, which could be used in public health communication strategies.

Impact of the COVID-19 pandemic on gastrointestinal infection trends in England, February-July 2020.

OBJECTIVE: To establish the impact of the first 6 months of the COVID-19 outbreak response on gastrointestinal (GI) infection trends in England. DESIGN: Retrospective ecological study using routinely collected national and regional surveillance data from seven UK Health Security Agency coordinated laboratory, outbreak and syndromic surveillance systems using key dates of UK governmental policy change to assign phases for comparison between 2020 and historic data. RESULTS: Decreases in GI illness activity were observed across all surveillance indicators as COVID-19 cases began to peak. Compared with the 5-year average (2015-2019), during the first 6 months of the COVID-19 response, there was a 52% decrease in GI outbreaks reported (1544 vs 3208 (95% CI 2938 to 3478)) and a 34% decrease in laboratory confirmed cases (27 859 vs 42 495 (95% CI 40 068 to 44 922)). GI indicators began to rise during the first lockdown and lockdown easing, although all remained substantially lower than historic figures. Reductions in laboratory confirmed cases were observed across all age groups and both sexes, with geographical heterogeneity observed in diagnosis trends. Health seeking behaviour changed substantially, with attendances decreasing prior to lockdown across all indicators. CONCLUSIONS: There has been a marked change in trends of GI infections in the context of the COVID-19 pandemic. The drivers of this change are likely to be multifactorial; while changes in health seeking behaviour, pressure on diagnostic services and surveillance system ascertainment have undoubtably played a role, there has likely been a true decrease in the incidence for some pathogens resulting from the control measures and restrictions implemented. This suggests that if some of these changes in behaviour such as improved hand hygiene were maintained, then we could potentially see sustained reductions in the burden of GI illness.

Predicted norovirus resurgence in 2021-2022 due to the relaxation of nonpharmaceutical interventions associated with COVID-19 restrictions in England: a mathematical modeling study.

BACKGROUND: To reduce the coronavirus disease burden in England, along with many other countries, the government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions. METHODS: Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021. RESULTS: We report that susceptibility to norovirus infection has likely increased between March 2020 and mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels, the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels, there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages. CONCLUSIONS: Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Differential impact of the COVID-19 pandemic on laboratory reporting of norovirus and Campylobacter in England: A modelling approach.

BACKGROUND: The COVID-19 pandemic has impacted surveillance activities for multiple pathogens. Since March 2020, there was a decline in the number of reports of norovirus and Campylobacter recorded by England's national laboratory surveillance system. The aim is to estimate and compare the impact of the COVID-19 pandemic on norovirus and Campylobacter surveillance data in England. METHODS: We utilised two quasi-experimental approaches based on a generalised linear model for sequential count data. The first approach estimates overall impact and the second approach focuses on the impact of specific elements of the pandemic response (COVID-19 diagnostic testing and control measures). The following time series (27, 2015-43, 2020) were used: weekly laboratory-confirmed norovirus and Campylobacter reports, air temperature, conducted Sars-CoV-2 tests and Index of COVID-19 control measures stringency. RESULTS: The period of Sars-CoV-2 emergence and subsequent sustained transmission was associated with persistent reductions in norovirus laboratory reports (p = 0.001), whereas the reductions were more pronounced during pandemic emergence and later recovered for Campylobacter (p = 0.075). The total estimated reduction was 47% - 79% for norovirus (12-43, 2020). The total reduction varied by time for Campylobacter, e.g. 19% - 33% in April, 1% - 7% in August. CONCLUSION: Laboratory reporting of norovirus was more adversely impacted than Campylobacter by the COVID-19 pandemic. This may be partially explained by a comparatively stronger effect of behavioural interventions on norovirus transmission and a relatively greater reduction in norovirus testing capacity. Our study underlines the differential impact a pandemic may have on surveillance of gastrointestinal infectious diseases.

Predicted Norovirus Resurgence in 2021-2022 Due to the Relaxation of Nonpharmaceutical Interventions Associated with COVID-19 Restrictions in England: A Mathematical Modelling Study.

BACKGROUND: To reduce the coronavirus disease burden in England, along with many other countries, the Government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions. METHODS: Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021. RESULTS: We report that susceptibility to norovirus infection has likely increased between March 2020 to mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages. CONCLUSIONS: Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Retrospective analysis on confirmation rates for referred positive rotavirus samples in England, 2016 to 2017: implications for diagnosis and surveillance.

BackgroundRapid diagnostic tests are commonly used by hospital laboratories in England to detect rotavirus (RV), and results are used to inform clinical management and support national surveillance of the infant rotavirus immunisation programme since 2013. In 2017, the Public Health England (PHE) national reference laboratory for enteric viruses observed that the presence of RV could not be confirmed by PCR in a proportion of RV-positive samples referred for confirmatory detection.AimWe aimed to compare the positivity rate of detection methods used by hospital laboratories with the PHE confirmatory test rate.MethodsRotavirus specimens testing positive at local hospital laboratories were re-tested at the PHE national reference laboratory using a PCR test. Confirmatory results were compared to original results from the PHE laboratory information management system.ResultsHospital laboratories screened 70.1% (2,608/3,721) of RV samples using immunochromatographic assay (IC) or rapid tests, 15.5% (578/3,721) using enzyme immunoassays (EIA) and 14.4% (535/3,721) using PCR. Overall, 1,011/3,721 (27.2%) locally RV-positive samples referred to PHE in 2016 and 2017 failed RV detection using the PHE reference laboratory PCR test. Confirmation rates were 66.9% (1,746/2,608) for the IC tests, 87.4% (505/578) for the EIA and 86.4% (465/535) for the PCR assays. Seasonal confirmation rate discrepancies were also evident for IC tests.ConclusionsThis report highlights high false positive rates with the most commonly used RV screening tests and emphasises the importance of implementing verified confirmatory tests for RV detections. This has implications for clinical diagnosis and national surveillance.

Abscisic Acid Analogues That Act as Universal or Selective Antagonists of Phytohormone Receptors.

The plant hormone abscisic acid (ABA) plays many important roles in controlling plant development and physiology, from flowering to senescence. ABA is now known to exert its effects through a family of soluble ABA receptors, which in Arabidopsis thaliana has 13 members divided into three clades. Homologues of these receptors are present in other plants, also in relatively large numbers. Investigation of the roles of each homologue in mediating the diverse physiological roles of ABA is hampered by this genetic redundancy. We report herein the in vitro screening of a targeted ABA-like analogue library and identification of novel antagonist hits, including the analogue PBI686 that had been developed previously as a probe for identifying ABA-binding proteins. Further in vitro characterization of PBI686 and development of second-generation leads yielded both receptor-selective and universal antagonist hits. In planta assays in different species have demonstrated that these antagonist leads can overcome various ABA-induced physiological changes. While the general antagonists open up a hitherto unexplored avenue for controlling plant growth through inhibition of ABA-regulated physiological processes, the receptor-selective antagonist can be developed into chemical probes to explore the physiological roles of individual receptors.

Synthesis and structural studies of chiral indium(III) complexes supported by tridentate diaminophenol ligands.

Indium(III) dimethyl, dihalide, and alkoxy-bridged complexes bearing a chiral diaminophenoxy tridentate ligand [NN(H)O](-) were synthesized. The dimethyl complex (NN(H)O)InMe(2) (1) was unreactive toward ethanol and 2-propanol and only partially reactive toward the more acidic phenol. The dihalide complexes (NN(H)O)InX(2) (X = Cl (3), Br (4), I (5)) reacted with NaOEt to form robust alkoxy-bridged complexes with the formula {[(NN(H)O)InX](2)(mu-X)(mu-OEt)} (X = Cl (6), Br (7), I (8)). The reaction of the alkoxy-bridged complexes with water produced hydroxy-bridged dinuclear indium compounds. The hydroxy-bridged complex bearing a chloride ligand [(NN(H)O)InCl(mu-OH)](2) (9) was significantly more reactive toward dissociation and formation of a pyridine adduct than the iodo analogue [(NN(H)O)InI(mu-OH)](2) (10). All compounds were fully characterized in solution by NMR spectroscopy and in the solid state by single-crystal X-ray diffraction. In addition, DFT calculations were used to help explain the reactivity trends observed.