Spatio-temporal surveillance and early detection of SARS-CoV-2 variants of concern: a retrospective analysis.

The SARS-CoV-2 pandemic has been characterized by the repeated emergence of genetically distinct virus variants of increased transmissibility and immune evasion compared to pre-existing lineages. In many countries, their containment required the intervention of public health authorities and the imposition of control measures. While the primary role of testing is to identify infection, target treatment, and limit spread (through isolation and contact tracing), a secondary benefit is in terms of surveillance and the early detection of new variants. Here we study the spatial invasion and early spread of the Alpha, Delta and Omicron (BA.1 and BA.2) variants in England from September 2020 to February 2022 using the random neighbourhood covering (RaNCover) method. This is a statistical technique for the detection of aberrations in spatial point processes, which we tailored here to community PCR (polymerase-chain-reaction) test data where the TaqPath kit provides a proxy measure of the switch between variants. Retrospectively, RaNCover detected the earliest signals associated with the four novel variants that led to large infection waves in England. With suitable data our method therefore has the potential to rapidly detect outbreaks of future SARS-CoV-2 variants, thus helping to inform targeted public health interventions.

DiD IT?: a differences-in-differences investigation tool to quantify the impact of local incidents on public health using real-time syndromic surveillance health data.

Syndromic surveillance was originally developed to provide early warning compared to laboratory surveillance, but it is increasing used for real-time situational awareness. When a potential threat to public health is identified, a rapid assessment of its impact is required for public health management. When threats are localised, analysis is more complex as local trends need to be separated from national trends and differences compared to unaffected areas may be due to confounding factors such as deprivation or age distributions. Accounting for confounding factors usually requires an in-depth study, which takes time. Therefore, a tool is required which can provide a rapid estimate of local incidents using syndromic surveillance data.Here, we present 'DiD IT?', a new investigation tool designed to measure the impact of local threats to public health. 'DiD IT?' uses a difference-in-differences statistical approach to account for temporal and spatial confounding and provide a direct estimate of impact due to incidents. Temporal confounding differences are estimated by comparing unaffected locations during and outside of exposure periods. Whilst spatial confounding differences are estimated by comparing unaffected and exposed locations outside of the exposure period. Any remaining differences can be considered to be the direct effect of the local incident.We illustrate the potential utility of the tool through four examples of localised health protection incidents in England. The examples cover a range of data sources including general practitioner (GP) consultations, emergency department (ED) attendances and a telehealth call and online health symptom checker; and different types of incidents including, infectious disease outbreak, mass-gathering, extreme weather and an industrial fire. The examples use the UK Health Security Agency's ongoing real-time syndromic surveillance systems to show how results can be obtained in near real-time.The tool identified 700 additional online difficulty breathing assessments associated with a severe thunderstorm, 53 additional GP consultations during a mumps outbreak, 2-3 telehealth line calls following an industrial fire and that there was no significant increase in ED attendances during the G7 summit in 2021.DiD IT? can provide estimates for the direct impact of localised events in real-time as part of a syndromic surveillance system. Thus, it has the potential for enhancing surveillance and can be used to evaluate the effectiveness of extending national surveillance to a more granular local surveillance.

Representativeness, Vaccination Uptake, and COVID-19 Clinical Outcomes 2020-2021 in the UK Oxford-Royal College of General Practitioners Research and Surveillance Network: Cohort Profile Summary.

BACKGROUND: The Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) is one of Europe's oldest sentinel systems, working with the UK Health Security Agency (UKHSA) and its predecessor bodies for 55 years. Its surveillance report now runs twice weekly, supplemented by online observatories. In addition to conducting sentinel surveillance from a nationally representative group of practices, the RSC is now also providing data for syndromic surveillance. OBJECTIVE: The aim of this study was to describe the cohort profile at the start of the 2021-2022 surveillance season and recent changes to our surveillance practice. METHODS: The RSC's pseudonymized primary care data, linked to hospital and other data, are held in the Oxford-RCGP Clinical Informatics Digital Hub, a Trusted Research Environment. We describe the RSC's cohort profile as of September 2021, divided into a Primary Care Sentinel Cohort (PCSC)-collecting virological and serological specimens-and a larger group of syndromic surveillance general practices (SSGPs). We report changes to our sampling strategy that brings the RSC into alignment with European Centre for Disease Control guidance and then compare our cohort's sociodemographic characteristics with Office for National Statistics data. We further describe influenza and COVID-19 vaccine coverage for the 2020-2021 season (week 40 of 2020 to week 39 of 2021), with the latter differentiated by vaccine brand. Finally, we report COVID-19-related outcomes in terms of hospitalization, intensive care unit (ICU) admission, and death. RESULTS: As a response to COVID-19, the RSC grew from just over 500 PCSC practices in 2019 to 1879 practices in 2021 (PCSC, n=938; SSGP, n=1203). This represents 28.6% of English general practices and 30.59% (17,299,780/56,550,136) of the population. In the reporting period, the PCSC collected >8000 virology and >23,000 serology samples. The RSC population was broadly representative of the national population in terms of age, gender, ethnicity, National Health Service Region, socioeconomic status, obesity, and smoking habit. The RSC captured vaccine coverage data for influenza (n=5.4 million) and COVID-19, reporting dose one (n=11.9 million), two (n=11 million), and three (n=0.4 million) for the latter as well as brand-specific uptake data (AstraZeneca vaccine, n=11.6 million; Pfizer, n=10.8 million; and Moderna, n=0.7 million). The median (IQR) number of COVID-19 hospitalizations and ICU admissions was 1181 (559-1559) and 115 (50-174) per week, respectively. CONCLUSIONS: The RSC is broadly representative of the national population; its PCSC is geographically representative and its SSGPs are newly supporting UKHSA syndromic surveillance efforts. The network captures vaccine coverage and has expanded from reporting primary care attendances to providing data on onward hospital outcomes and deaths. The challenge remains to increase virological and serological sampling to monitor the effectiveness and waning of all vaccines available in a timely manner.

Cluster detection with random neighbourhood covering: Application to invasive Group A Streptococcal disease.

The rapid detection of outbreaks is a key step in the effective control and containment of infectious diseases. In particular, the identification of cases which might be epidemiologically linked is crucial in directing outbreak-containment efforts and shaping the intervention of public health authorities. Often this requires the detection of clusters of cases whose numbers exceed those expected by a background of sporadic cases. Quantifying exceedances rapidly is particularly challenging when only few cases are typically reported in a precise location and time. To address such important public health concerns, we present a general method which can detect spatio-temporal deviations from a Poisson point process and estimate the odds of an isolate being part of a cluster. This method can be applied to diseases where detailed geographical information is available. In addition, we propose an approach to explicitly take account of delays in microbial typing. As a case study, we considered invasive group A Streptococcus infection events as recorded and typed by Public Health England from 2015 to 2020.

The Utility of Ambulance Dispatch Call Syndromic Surveillance for Detecting and Assessing the Health Impact of Extreme Weather Events in England.

Extreme weather events present significant global threats to health. The National Ambulance Syndromic Surveillance System collects data on 18 syndromes through chief presenting complaint (CPC) codes. We aimed to determine the utility of ambulance data to monitor extreme temperature events for action. Daily total calls were observed between 01/01/2018−30/04/2019. Median daily 'Heat/Cold' CPC calls during "known extreme temperature" (identified a priori), "extreme temperature"; (within 5th or 95th temperature percentiles for central England) and meteorological alert periods were compared to all other days using Wilcoxon signed-rank test. During the study period, 12,585,084 calls were recorded. In 2018, median daily "Heat/Cold" calls were higher during periods of known extreme temperature: heatwave (16/day, 736 total) and extreme cold weather events (28/day, 339 total) compared to all other days in 2018 (6/day, 1672 total). Median daily "Heat/Cold" calls during extreme temperature periods (16/day) were significantly higher than non-extreme temperature periods (5/day, p < 0.001). Ambulance data can be used to identify adverse impacts during periods of extreme temperature. Ambulance data are a low resource, rapid and flexible option providing real-time data on a range of indicators. We recommend ambulance data are used for the surveillance of presentations to healthcare related to extreme temperature events.

Associations between socioeconomic deprivation and pharmaceutical prescribing in primary care in England.

BACKGROUND: Socioeconomic deprivation is associated with health inequality. Previous studies have described associations between primary care prescribing rates and deprivation for individual drugs or drug classes. We explore the correlation between socioeconomic deprivation and the rate of prescribing of individual pharmaceutical drugs, and drug classes, in primary care in England, to identify prescribing inequalities that would require further investigation. METHODS: In this cross-sectional study, national primary care prescribing data, by primary care practice, were retrieved for the calendar year 2019 in England. Socioeconomic deprivation was quantified using the Index of Multiple Deprivation (IMD) score. Correlations were calculated using Spearman's rank correlation coefficient (ρ), adjusting for practice list size and demographics, with a Bonferroni-corrected p value threshold of 5×10-5. RESULTS: We included 1.05 billion prescription items dispensed from 6896 England practices. 142/206 (69%) drug classes and 505/774 (65%) drugs were significantly correlated with IMD score (p<5×10-5). Of the 774 included drugs, 31 (4%) were moderately positively associated with IMD score (ρ>0.4). Only one was moderately negatively correlated with IMD score (ρ<-0.4), suggesting higher prescribing rates in more affluent areas. The drug classes most strongly associated with IMD score included opioid and non-opioid analgesics, antipsychotics and reflux medications. Drug classes most strongly associated with affluence included epinephrine, combined oral contraceptives and hormone replacement therapy. CONCLUSION: We identify novel associations of prescribing with deprivation. Further work is required to identify the underlying reasons for these associations so that appropriate interventions can be formulated to address drivers of inequality.

Outbreak of Shiga toxin-producing Escherichia coli O157 linked with consumption of a fast-food product containing imported cucumbers, United Kingdom, August 2020.

BACKGROUND: In August 2020, an outbreak of Shiga toxin-producing Escherichia coli (STEC) O157:H7 occurred in the United Kingdom. Whole genome sequencing revealed that these cases formed a genetically distinct cluster. METHODS: Hypotheses generated from case interviews were tested in analytical studies, and results informed environmental sampling and food chain analysis. A case-case study used non-outbreak 'comparison' STEC cases; a case-control study used a market research panel to recruit controls. RESULTS: A total of 36 cases were identified; all cases reported symptom onset between August 3 and August 16, 2020. The majority of cases (83%) resided in the Midlands region of England and in Wales. A high proportion of cases reported eating out, with one fast-food restaurant chain mentioned by 64% (n = 23) of cases. Both the case-case study (adjusted odds ratio (aOR) 31.8, 95% confidence interval (CI) 1.6-624.9) and the case-control study (aOR 9.19, 95% CI 1.0-82.8) revealed statistically significant results, showing that the consumption of a specific fast-food product was independently associated with infection. CONCLUSIONS: Consumption of a specific fast-food product was a likely cause of this outbreak. The only ingredient specific to the product was cucumbers. The supply of cucumbers was immediately halted, and no further cases have been identified.

Guidance impact on primary care prescribing rates of simple analgesia: an interrupted time series analysis in England.

BACKGROUND: In March 2018, NHS England published guidance for clinical commissioning groups (CCGs) to encourage implementation of policy to reduce primary care prescriptions of over-the-counter medications, including simple analgesia. AIM: To investigate the impact of guidance publication on prescribing rates of simple analgesia (oral paracetamol, oral ibuprofen, and topical non-steroidal anti-inflammatory drugs) in primary care; CCG guidance implementation intentions; and whether the guidance has created health inequality based on socioeconomic status. DESIGN AND SETTING: Interrupted time series analysis of primary care prescribing data in England. METHOD: Practice-level prescribing data from January 2015 to March 2019 were obtained from NHS Digital. Interrupted time series analyses were used to assess the association of guidance publication with prescribing rates. The association between practice-level prescribing rates and Index of Multiple Deprivation scores before and after publication was quantified using multivariable Poisson regression. Freedom of information requests were submitted to all CCGs. RESULTS: There was a statistically significant 4.4% reduction in prescribing of simple analgesia following guidance publication (adjusted incidence rate ratio 0.96, 95% CI = 0.92 to 0.99, P = 0.027), adjusting for underlying time trend and seasonality. There was considerable diversity across CCGs in whether or how they chose to implement the guidance. Practice-level prescribing rates were greater in more deprived areas. CONCLUSION: Guidance publication was associated with a small reduction in the prescribing rates of simple analgesia across England, without evidence of creating additional health inequality. Careful implementation by CCGs would be required to optimise cost saving to the NHS.

Evaluating multi-purpose syndromic surveillance systems - a complex problem.

Surveillance systems need to be evaluated to understand what the system can or cannot detect. The measures commonly used to quantify detection capabilities are sensitivity, positive predictive value and timeliness. However, the practical application of these measures to multi-purpose syndromic surveillance services is complex. Specifically, it is very difficult to link definitive lists of what the service is intended to detect and what was detected. First, we discuss issues arising from a multi-purpose system, which is designed to detect a wide range of health threats, and where individual indicators, e.g. 'fever', are also multi-purpose. Secondly, we discuss different methods of defining what can be detected, including historical events and simulations. Finally, we consider the additional complexity of evaluating a service which incorporates human decision-making alongside an automated detection algorithm. Understanding the complexities involved in evaluating multi-purpose systems helps design appropriate methods to describe their detection capabilities.

Environmental factors associated with general practitioner consultations for allergic rhinitis in London, England: a retrospective time series analysis.

OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186 401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m3, relative risk (RR) 3.33, 95% CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m3, RR 1.69, 95% CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95% CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO2) appeared to be associated with increased consultations (for the category 70-85 µg/m3, RR 1.33, 95% CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20 mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO2 concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.

Socioeconomic status and HRT prescribing: a study of practice-level data in England.

BACKGROUND: Concerns have been raised that women from deprived backgrounds are less likely to be receiving hormone replacement therapy (HRT) treatment and its benefits, although evidence in support of this is lacking. AIM: To investigate general practice HRT prescription trends and their association with markers of socioeconomic deprivation. DESIGN AND SETTING: Cross-sectional study of primary care prescribing data in England in 2018. METHOD: Practice-level prescribing rate was defined as the number of items of HRT prescribed per 1000 registered female patients aged ≥40 years. The association between Index of Multiple Deprivation (IMD) score and HRT prescribing rate was tested using multivariate Poisson regression, adjusting for practice proportions of obesity, smoking, hypertension, diabetes, coronary heart disease and cerebrovascular disease, and practice list size. RESULTS: The overall prescribing rate of HRT was 29% lower in practices from the most deprived quintile compared with the most affluent (incidence rate ratio [IRR] = 0.71; 95% confidence interval [CI] = 0.68 to 0.73). After adjusting for all cardiovascular disease outcomes and risk factors, the prescribing rate in the most deprived quintile was still 18% lower than in the least deprived quintile (adjusted IRR = 0.82; 95% CI = 0.77 to 0.86). In more deprived practices, there was a significantly higher tendency to prescribe oral HRT than transdermal preparations (P<0.001). CONCLUSION: This study highlights inequalities associated with HRT prescription. This may reflect a large unmet need in terms of menopause care in areas of deprivation. Further research is needed to identify the factors from patient and GP perspectives that may explain this.

Outbreak of Clostridium perfringens food poisoning linked to leeks in cheese sauce: an unusual source.

Between 11-13 December 2018, local public health authorities in the West Midlands, England were alerted to 34 reports of diarrhoea with abdominal cramps. Symptom onset was ~10 h after diners ate Christmas meals at a restaurant between 7-9 December 2018. A retrospective case-control study, environmental and microbiological investigations were undertaken to determine the source and control the outbreak. An analytical study was undertaken with odds ratios (OR) and 95% confidence intervals (CI). Forty persons were recruited to the analytical study (28/40 cases). Multivariable analysis found that leeks in cheese sauce was the only item associated with illness (aOR 51.1; 95% CI 4.13-2492.1). Environmental investigations identified significant lapses in food safety, including lapses in temperature control during cooking and hot holding, likely cross-contamination between raw and cooked foods and the reuse of leftover cheese sauce for the next day's service. No food samples were taken during the exposure period. Two faecal samples were positive for Clostridium perfringens with one confirming the enterotoxigenic gene. Cheese sauce is an unusual vehicle for the organism and the first time this has been reported in England.

Utility of Ambulance Data for Real-Time Syndromic Surveillance: A Pilot in the West Midlands Region, United Kingdom.

Introduction The Public Health England (PHE; United Kingdom) Real-Time Syndromic Surveillance Team (ReSST) currently operates four national syndromic surveillance systems, including an emergency department system. A system based on ambulance data might provide an additional measure of the "severe" end of the clinical disease spectrum. This report describes the findings and lessons learned from the development and preliminary assessment of a pilot syndromic surveillance system using ambulance data from the West Midlands (WM) region in England. Hypothesis/Problem Is an Ambulance Data Syndromic Surveillance System (ADSSS) feasible and of utility in enhancing the existing suite of PHE syndromic surveillance systems? METHODS: An ADSSS was designed, implemented, and a pilot conducted from September 1, 2015 through March 1, 2016. Surveillance cases were defined as calls to the West Midlands Ambulance Service (WMAS) regarding patients who were assigned any of 11 specified chief presenting complaints (CPCs) during the pilot period. The WMAS collected anonymized data on cases and transferred the dataset daily to ReSST, which contained anonymized information on patients' demographics, partial postcode of patients' location, and CPC. The 11 CPCs covered a broad range of syndromes. The dataset was analyzed descriptively each week to determine trends and key epidemiological characteristics of patients, and an automated statistical algorithm was employed daily to detect higher than expected number of calls. A preliminary assessment was undertaken to assess the feasibility, utility (including quality of key indicators), and timeliness of the system for syndromic surveillance purposes. Lessons learned and challenges were identified and recorded during the design and implementation of the system. RESULTS: The pilot ADSSS collected 207,331 records of individual ambulance calls (daily mean=1,133; range=923-1,350). The ADSSS was found to be timely in detecting seasonal changes in patterns of respiratory infections and increases in case numbers during seasonal events. CONCLUSIONS: Further validation is necessary; however, the findings from the assessment of the pilot ADSSS suggest that selected, but not all, ambulance indicators appear to have some utility for syndromic surveillance purposes in England. There are certain challenges that need to be addressed when designing and implementing similar systems. Todkill D , Loveridge P , Elliot AJ , Morbey RA , Edeghere O , Rayment-Bishop T , Rayment-Bishop C , Thornes JE , Smith G . Utility of ambulance data for real-time syndromic surveillance: a pilot in the West Midlands region, United Kingdom. Prehosp Disaster Med. 2017;32(6):667-672.

An Observational Study Using English Syndromic Surveillance Data Collected During the 2012 London Olympics - What did Syndromic Surveillance Show and What Can We Learn for Future Mass-gathering Events?

Introduction In preparation for the London 2012 Olympic Games, existing syndromic surveillance systems operating in England were expanded to include daily general practitioner (GP) out-of-hours (OOH) contacts and emergency department (ED) attendances at sentinel sites (the GP OOH and ED syndromic surveillance systems: GPOOHS and EDSSS). Hypothesis/Problem The further development of syndromic surveillance systems in time for the London 2012 Olympic Games provided a unique opportunity to investigate the impact of a large mass-gathering event on public health and health services as monitored in near real-time by syndromic surveillance of GP OOH contacts and ED attendances. This can, in turn, aid the planning of future events. METHODS: The EDSSS and GPOOHS data for London and England from July 13 to August 26, 2012, and a similar period in 2013, were divided into three distinct time periods: pre-Olympic period (July 13-26, 2012); Olympic period (July 27 to August 12); and post-Olympic period (August 13-26, 2012). Time series of selected syndromic indicators in 2012 and 2013 were plotted, compared, and risk assessed by members of the Real-time Syndromic Surveillance Team (ReSST) in Public Health England (PHE). Student's t test was used to test any identified changes in pattern of attendance. RESULTS: Very few differences were found between years or between the weeks which preceded and followed the Olympics. One significant exception was noted: a statistically significant increase (P value = .0003) in attendances for "chemicals, poisons, and overdoses, including alcohol" and "acute alcohol intoxication" were observed in London EDs coinciding with the timing of the Olympic opening ceremony (9:00 pm July 27, 2012 to 01:00 am July 28, 2012). CONCLUSIONS: Syndromic surveillance was able to provide near to real-time monitoring and could identify hourly changes in patterns of presentation during the London 2012 Olympic Games. Reassurance can be provided to planners of future mass-gathering events that there was no discernible impact in overall attendances to sentinel EDs or GP OOH services in the host country. The increase in attendances for alcohol-related causes during the opening ceremony, however, may provide an opportunity for future public health interventions. Todkill D , Hughes HE , Elliot AJ , Morbey RA , Edeghere O , Harcourt S , Hughes T , Endericks T , McCloskey B , Catchpole M , Ibbotson S , Smith G . An observational study using English syndromic surveillance data collected during the 2012 London Olympics - what did syndromic surveillance show and what can we learn for future mass-gathering events? Prehosp Disaster Med. 2016;31(6):628-634.

Extending the diabetic retinopathy screening interval beyond 1†year: systematic review.

To determine whether the recommended screening interval for diabetic retinopathy (DR) in the UK can safely be extended beyond 1 year. Systematic review of clinical and cost-effectiveness studies. Nine databases were searched with no date restrictions. Randomised controlled trials (RCTs), cohort studies, prognostic or economic modelling studies which described the incidence and progression of DR in populations with type 1 diabetes mellitus or type 2 diabetes mellitus of either sex and of any age reporting incidence and progression of DR in relation to screening interval (vs annual screening interval) and/or prognostic factors were included. Narrative synthesis was undertaken. 14,013 papers were identified, of which 11 observational studies, 5 risk stratification modelling studies and 9 economic studies were included. Data were available for 262,541 patients of whom at least 228,649 (87%) had type 2 diabetes. There were no RCTs. Studies concluded that there is little difference between clinical outcomes from screening 1 yearly or 2 yearly in low-risk patients. However there was high loss to follow-up (13-31%), heterogeneity in definitions of low risk and variation in screening and grading protocols for prior retinopathy results. Observational and economic modelling studies in low-risk patients show little difference in clinical outcomes between 1-year and 2-year screening intervals. The lack of experimental research designs and heterogeneity in definition of low risk considerably limits the reliability and validity of this conclusion. Cost-effectiveness findings were mixed. There is insufficient evidence to recommend a move to extend the screening interval beyond 1 year.