Abstract Background Between February and September 2024 NHS Lanarkshire managed an outbreak of Hepatitis A (HAV) which occurred in three distinct clusters focused in one town. Outbreaks HAV are relatively infrequent events, but when they do occur urgent action is required to identify close contacts, chains of transmission and provide vaccination and where required immunoglobulin to close contacts and exclusion when required for some contacts in high risk occupations. Objectives Prevent onward transmission of HAV Methods Outbreak Management included vaccination at two nurseries, a primary school and ASN school. Results A total of 20 confirmed cases across the three clusters, 11 of which required hospitalisation. Epidemiological links were identified between all three clusters, and chains of transmission identified within each cluster. Cases clustered genetically based on molecular typing. Molecular typing did not identify cases elsewhere in the UK supporting hypothesis of local chains of person to person transmission. As the outbreak evolved the criteria for close contacts and those eligible for vaccination was extended to include social contacts and the household members of staff/pupils offered vaccination in one of the nurseries and the ASN school. Over 600 individuals were vaccinated to control the outbreak. Conclusions Challenges included the tight timescales for establishing clinics, ensuring a high uptake rate and extensive contact tracing. Testing was expanded to some asymptomatic individuals which supported case ascertainment especially among children who were often identified as likely sources of infection for others within the clusters. Consideration was also given to the potential of onwards transmission through the cases having been donors of substances of human origin (SoHO) such as donation of blood or bone. This prompted liaison with the Scottish National Blood Transfusion Service to make sure that the supply chain of SoHO was not compromised during the outbreak

National foodborne outbreaks of gastrointestinal disease often require rapid case-control investigations to identify the source. Online market panels offer a potential alternative to traditional control recruitment. We compared market panel controls to traditional controls in case-control recruitment during a 2024 UK outbreak of STEC O145. Two case-control studies were conducted for two different control groups (a) Salmonella cases as case-controls and (b) online market panel members. Timeliness, cost, and resources were compared, and a logistic regression compared findings in a control-control analysis. In total, 43 cases of STEC O145, 63 Salmonella case-controls, and 93 panel controls were recruited. Neither control group reached the recruitment target for the younger adult age group. Salmonella case-controls had a ninefold greater staff time to recruit and cost five times more than panel controls (£25.82 vs. £4.99 per control), partially due to interviewer-administered questionnaires compared with self-completion by panel controls. Both analytical approaches identified the same outbreak source, with no significant differences in exposures between the control groups. The cost and resource savings associated with panel controls justify their use as a standard procedure in outbreak investigations. We recommend exploring engagement with age groups that are difficult to recruit and assessing alternative strategies to reach them.

Shiga toxin-producing Escherichia coli (STEC) is a group of bacteria that causes gastrointestinal illness and occasionally causes large foodborne outbreaks. It represents a major public health concern due to its ability to cause severe illness which can sometimes be fatal. This study was undertaken as part of a rapid investigation into a national foodborne outbreak of STEC O145. On 22 May 2024, United Kingdom (UK) public health agencies and laboratories identified an increase in stool specimens submissions and patients testing positive for Shiga toxin-producing E. coli (STEC). Whole genome sequencing (WGS) identified serotype O145:H28 stx2a/eae belonging to the same five single nucleotide polymorphism (SNP) single linkage cluster as the causative agent. By 3 July 2024, 288 cases had been linked to the cluster. Most cases were adults (87%) and females (57%), 49% were hospitalized with a further 10% attending emergency care. Descriptive epidemiology and analytical studies were conducted which identified consumption of nationally distributed pre-packed sandwiches as a common food exposure. The implicated food business operators voluntarily recalled ready-to-eat sandwiches and wraps containing lettuce on 14 June 2024.

ObjectivesWe aimed to assess the effects of risk-based travel restrictions on (1) international travel frequency, (2) SARS-CoV-2 case importation risk, (3) national SARS-CoV-2 incidence and (4) importation of SARS-CoV-2 variants into Scotland.DesignPopulation-based surveillance study.SettingThe study utilises SARS-CoV-2 community testing from February 2021 to May 2022 in Scotland, UK and spans the introduction of the UK’s ‘traffic light system’ policy in May 2021.Primary outcome measuresTravel-related cases of COVID-19 were defined as PCR-positive Scottish residents self-reporting international travel within 14 days of booking a postarrival travel test. The Red-Amber-Green (RAG) status of the reported travel destination was determined through data linkage using country and date.ResultsInternational flight passengers arriving into Scotland increased by 754% during the traffic light period. Amber list countries were the most frequently visited and ranked highly for both SARS-CoV-2 importations and contribution to national case incidence. Rates of international travel and associated SARS-CoV-2 case rates varied significantly across age, health board and deprivation groups. Multivariable logistic regression revealed SARS-CoV-2 case detections were less likely through travel-based than community-based surveillance systems, although increased from green-to-amber and amber-to-red lists. When examined according to travel destination, SARS-CoV-2 importation risks did not strictly follow RAG designations, and red lists did not prevent establishment of novel SARS-CoV-2 variants.ConclusionsOur findings suggest that country-specific postarrival screening undertaken in Scotland did not prohibit the public health impact of COVID-19 in Scotland. Travel rates likely contributed to patterns of SARS-CoV-2 case importation and population incidence.

Characterising drivers of SARS-CoV-2 circulation is crucial for understanding COVID-19 because of the severity of control measures adopted during the pandemic. Whole genome sequence data augmented with demographic metadata provides the best opportunity to do this. We use Random Forest Decision Tree models to analyse a combination of over 4000 SARS-CoV2 sequences from a densely sampled, mixed urban and rural population (Tayside) in Scotland in the period from August 2020 to July 2021, with fine scale geographical and socio-demographic metadata. Comparing periods in versus out of "lockdown" restrictions, we show using genetic distance relationships that individuals from more deprived areas are more likely to get infected during lockdown but less likely to spread the infection further. As disadvantaged communities were the most affected by both COVID-19 and its restrictions, our finding has important implications for informing future approaches to control future pandemics driven by similar respiratory infections.

Background Decisions to impose temporary travel measures are less common as the global epidemiology of COVID-19 evolves. Risk-based travel measures may avoid the need for a complete travel ban, however evaluations of their effects are lacking. Here we investigated the public health effects of a temporary traffic light system introduced in the United Kingdom (UK) in 2021, imposing red-amber-green (RAG) status based on risk assessment. Methods We analysed data on international flight passengers arriving into Scotland, COVID-19 testing surveillance, and SARS-CoV-2 whole genome sequences to quantify effects of the traffic light system on (i) international travel frequency, (ii) travel-related SARS-CoV-2 case importations, (iii) national SARS-CoV-2 case incidence, and (iv) importation of novel SARS-CoV-2 variants. Results International flight passengers arriving into Scotland had increased by 754% during the traffic light period. Amber list countries were the most frequently visited and ranked highly for SARS-CoV-2 importations and contribution to national case incidence. Rates of international travel and associated SARS-CoV-2 cases varied significantly across age, health board, and deprivation groups. Multivariable logistic regression revealed SARS-CoV-2 cases detections were less likely among travellers than non-travellers, although increasing from green-to-amber and amber-to-red lists. When examined according to travel destination, SARS-CoV-2 importation risks did not strictly follow RAG designations, and red lists did not prevent establishment of novel SARS-CoV-2 variants. Conclusions Our findings suggest that country-specific post-arrival screening undertaken in Scotland did not prohibit the public health impact of COVID-19 in Scotland. Travel rates likely contributed to patterns of high SARS-CoV-2 case importation and population impact.

Abstract Despite promising steps towards the elimination of hepatitis C virus (HCV) in the UK, several indicators provide a cause for concern for future disease burden. We aimed to improve understanding of geographical variation in HCV-related severe liver disease and historic risk factor prevalence among clinic attendees in England and Scotland. We used metadata from 3829 HCV-positive patients consecutively enrolled into HCV Research UK from 48 hospital centres in England and Scotland during 2012–2014. Employing mixed-effects statistical modelling, several independent risk factors were identified: age 46–59 y (ORadj 3.06) and ≥60 y (ORadj 5.64) relative to <46 y, male relative to female sex (ORadj 1.58), high BMI (ORadj 1.73) and obesity (ORadj 2.81) relative to normal BMI, diabetes relative to no diabetes (ORadj 2.75), infection with HCV genotype (GT)-3 relative to GT-1 (ORadj 1.75), route of infection through blood products relative to injecting drug use (ORadj 1.40), and lower odds were associated with black ethnicity (ORadj 0.31) relative to white ethnicity. A small proportion of unexplained variation was attributed to differences between hospital centres and local health authorities. Our study provides a baseline measure of historic risk factor prevalence and potential geographical variation in healthcare provision, to support ongoing monitoring of HCV-related disease burden and the design of risk prevention measures.

Download This Paper Open PDF in Browser Add Paper to My Library Share: Permalink Using these links will ensure access to this page indefinitely Copy URL Copy DOI

Whole genome sequencing of SARS-CoV-2 has occurred at an unprecedented scale, and can be exploited for characterising outbreak risks at the fine-scale needed to inform control strategies. One setting at continued risk of COVID-19 outbreaks are higher education institutions, associated with student movements at the start of term, close living conditions within residential halls, and high social contact rates. Here we analysed SARS-CoV-2 whole genome sequences in combination with epidemiological data to investigate a large cluster of student cases associated with University of Glasgow accommodation in autumn 2020, Scotland. We identified 519 student cases of SARS-CoV-2 infection associated with this large cluster through contact tracing data, with 30% sequencing coverage for further analysis. We estimated at least 11 independent introductions of SARS-CoV-2 into the student population, with four comprising the majority of detected cases and consistent with separate outbreaks. These four outbreaks were curtailed within a week following implementation of control measures. The impact of student infections on the local community was short-term despite an underlying increase in community infections. Our study highlights the need for context-specific information in the formation of public health policy for higher educational settings.

Comparing age and sex differences in SARS-CoV-2 hospitalization and mortality with MERS-CoV, seasonal coronaviruses, influenza and other health outcomes opens the way to generating hypotheses as to underlying mechanisms driving disease risk. Using 60-year-olds as a reference age group, we find that relative rates of hospitalization and mortality associated with the emergent coronaviruses are lower during childhood and start to increase earlier (around puberty) as compared with influenza and seasonal coronaviruses. The changing distribution of disease risk by age for emerging pathogens appears to broadly track the gradual deterioration of the immune system (immunosenescence), which starts around puberty. By contrast, differences in severe disease risk by age from endemic pathogens are more decoupled from the immune ageing process. Intriguingly, age-specific sex differences in hospitalizations are largely similar across endemic and emerging infections. We discuss potential mechanisms that may be associated with these patterns.

Identifying drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure and quantifying population immunity is crucial to prepare for future epidemics. We performed a serial cross-sectional serosurvey throughout the first pandemic wave among patients from the largest health board in Scotland. Screening of 7480 patient serum samples showed a weekly seroprevalence ranging from 0.10% to 8.23% in primary and 0.21% to 17.44% in secondary care, respectively. Neutralization assays showed that highly neutralizing antibodies developed in about half of individuals who tested positive with enzyme-linked immunosorbent assay, mainly among secondary care patients. We estimated the individual probability of SARS-CoV-2 exposure and quantified associated risk factors. We show that secondary care patients, male patients, and 45-64-year-olds exhibit a higher probability of being seropositive. The identification of risk factors and the differences in virus neutralization activity between patient populations provided insights into the patterns of virus exposure during the first pandemic wave and shed light on what to expect in future waves.

Not 1 year has passed since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). Since its emergence, great uncertainty has surrounded the potential for COVID-19 to establish as a seasonally recurrent disease. Many infectious diseases, including endemic human coronaviruses, vary across the year. They show a wide range of seasonal waveforms, timing (phase), and amplitudes, which differ depending on the geographical region. Drivers of such patterns are predominantly studied from an epidemiological perspective with a focus on weather and behavior, but complementary insights emerge from physiological studies of seasonality in animals, including humans. Thus, we take a multidisciplinary approach to integrate knowledge from usually distinct fields. First, we review epidemiological evidence of environmental and behavioral drivers of infectious disease seasonality. Subsequently, we take a chronobiological perspective and discuss within-host changes that may affect susceptibility, morbidity, and mortality from infectious diseases. Based on photoperiodic, circannual, and comparative human data, we not only identify promising future avenues but also highlight the need for further studies in animal models. Our preliminary assessment is that host immune seasonality warrants evaluation alongside weather and human behavior as factors that may contribute to COVID-19 seasonality, and that the relative importance of these drivers requires further investigation. A major challenge to predicting seasonality of infectious diseases are rapid, human-induced changes in the hitherto predictable seasonality of our planet, whose influence we review in a final outlook section. We conclude that a proactive multidisciplinary approach is warranted to predict, mitigate, and prevent seasonal infectious diseases in our complex, changing human-earth system.

Public health preparedness for coronavirus disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal human coronaviruses (sCoVs) and other cocirculating viruses in the West of Scotland, UK. We analyzed routine diagnostic data for >70,000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43 and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was funded by the Medical Research Council of the UK. ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The patient-level data used in this study are available upon request to NHS Scotland (https://www.informationgovernance.scot.nhs.uk/pbpphsc/home/for-applicants/). Aggregated forms of summary data may be made available upon request to the corresponding author.

It was very interesting to learn about Kloepfer et al.’s study investigating the link between asthma and influenza A H1N1 infection incidence and severity (1). Their finding that influenza A virus (IAV) infections reduced the subsequent risk of infection with human rhinoviruses (HRVs) was contrary to theories at the time of a reverse directionality (2, 3). However, as Kloepfer and Gern (4) state in their Letter, it is certainly consistent with our recent large-scale study on respiratory virus–virus interactions (5). Our study primarily aimed to provide statistical evidence for interactions … [↵][1]1To whom correspondence may be addressed. Email: pablo.murcia{at}glasgow.ac.uk. [1]: #xref-corresp-1-1

Public health preparedness for coronavirus (CoV) disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal CoVs (sCoVs) and other cocirculating viruses in the West of Scotland, United Kingdom. We analyzed routine diagnostic data for >70 000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43, and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently, and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.

Public health preparedness for coronavirus disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal human coronaviruses (sCoVs) and other cocirculating viruses in the West of Scotland, UK. We analyzed routine diagnostic data for >70,000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43 and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.

It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.