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Wastewater-based surveillance (WBS) can monitor for the presence of human health pathogens in the population. During COVID-19, WBS was widely used to determine wastewater SARS-CoV-2 RNA concentration (concentrations) providing information on community COVID-19 cases (cases). However, studies examining the relationship between concentrations and cases tend to be localised or focussed on small-scale institutional settings. Few have examined this relationship in multiple settings, over long periods, with large sample numbers, nor attempted to quantify the relationship between concentrations and cases or detail how catchment characteristics affected these. This 18-month study (07/20-12/21) explored the correlation and quantitative relationship between concentrations and cases using censored regression. Our analysis used >94,000 wastewater samples collected from 452 diverse sampling sites (259 Sewage Treatment Works (STW) and 193 Sewer Network Sites (SNS)) covering ~65 % of the English population. Wastewater concentrations were linked to ~6 million diagnostically confirmed COVID-19 cases. High correlation coefficients were found between concentrations and cases (STW: median r = 0.66, IQR: 0.57-0.74; SNS: median r = 0.65, IQR: 0.54-0.74). The quantitative relationship (regression coefficient) between concentrations and cases was variable between catchments. Catchment and sampling characteristics (e.g. size of population and grab vs automated sampling) had significant but small effects on correlation and regression coefficients. During the last six months of the study correlation coefficients reduced and regression coefficients became highly variable between catchments. This coincided with a shift towards younger cases, a highly vaccinated population and rapid emergence of the variant Omicron. The English WBS programme was rapidly introduced at scale during COVID-19. Laboratory methods evolved and study catchments were highly diverse in size and characteristics. Despite this diversity, findings indicate that WBS provides an effective proxy for establishing COVID-19 dynamics across a wide variety of communities. While there is potential for predicting COVID-19 cases from wastewater concentration, this may be more effective at smaller scales., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

The purpose of syndromic surveillance is to provide early warning of public health incidents, real-time situational awareness during incidents and emergencies, and reassurance of the lack of impact on the population, particularly during mass gatherings. The United Kingdom Health Security Agency (UKHSA) currently coordinates a real-time syndromic surveillance service that encompasses 6 national syndromic surveillance systems reporting on daily health care usage across England. Each working day, UKHSA analyzes syndromic data from over 200,000 daily patient encounters with the National Health Service, monitoring over 140 unique syndromic indicators, risk assessing over 50 daily statistical exceedances, and taking and recommending public health action on these daily. This English syndromic surveillance service had its origins as a small exploratory pilot in a single region of England in 1999 involving a new pilot telehealth service, initially reporting only on "cold or flu" calls. This pilot showed the value of syndromic surveillance in England, providing advanced warning of the start of seasonal influenza activity over existing laboratory-based surveillance systems. Since this initial pilot, a program of real-time syndromic surveillance has evolved from the single-system, -region, -indicator pilot (using manual data transfer methods) to an all-hazard, multisystem, automated national service. The suite of systems now monitors a wide range of syndromes, from acute respiratory illness to diarrhea to cardiac conditions, and is widely used in routine public health surveillance and for monitoring seasonal respiratory disease and incidents such as the COVID-19 pandemic. Here, we describe the 25-year evolution of the English syndromic surveillance system, focusing on the expansion and improvements in data sources and data management, the technological and digital enablers, and novel methods of data analytics and visualization., (©Alex J Elliot, Helen E Hughes, Sally E Harcourt, Sue Smith, Paul Loveridge, Roger A Morbey, Amardeep Bains, Obaghe Edeghere, Natalia R Jones, Daniel Todkill, Gillian E Smith. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.09.2024.)

By embedding a spatially explicit ecosystem services modelling tool within a policy simulator we examine the insights that natural capital analysis can bring to the design of policies for nature recovery. Our study is illustrated through a case example of policies incentivising the establishment of new natural habitat in England. We find that a policy mirroring the current practice of offering payments per hectare of habitat creation fails to break even, delivering less value in improved flows of ecosystem services than public money spent and only 26% of that which is theoretically achievable. Using optimization methods, we discover that progressively more efficient outcomes are delivered by policies that optimally price activities (34%), quantities of environmental change (55%) and ecosystem service value flows (81%). Further, we show that additionally attaining targets for unmonetized ecosystem services (in our case, biodiversity) demands trade-offs in delivery of monetized services. For some policy instruments it is not even possible to achieve the targets. Finally, we establish that extending policy instruments to offer payments for unmonetized services delivers target-achieving and value-maximizing policy designs. Our findings reveal that policy design is of first-order importance in determining the efficiency and efficacy of programmes pursuing nature recovery. This article is part of the theme issue 'Bringing nature into decision-making'.

Background: The number of people living with dementia (PLWD) continues to increase, particularly those with severe symptomatology. Severe symptoms and greater ill-health result in more acute care need. Early healthcare interventions can prove beneficial. Healthcare use has not been analysed as a holistic set of interlinked events. This study explores different healthcare pathways among PLWD, social or spatial inequalities in healthcare pathways and subsequent mortality risk., Methods: Group-based trajectory models (GBTM) were applied to electronic healthcare records. We generated clusters of PLWD with similar five-year, post-diagnosis trajectories in rates of primary and secondary healthcare use. Potential social and spatial variations in healthcare use clusters were examined. Cox Proportional Hazards used to explore variation in subsequent mortality risk between healthcare use clusters., Results: Four healthcare use clusters were identified in both early- (n = 3732) and late-onset (n = 6224) dementia populations. Healthcare use variations were noted; consistent or diminishing healthcare use was associated with lower subsequent mortality risk. Increasing healthcare use was associated with increased mortality risk. Descriptive analyses indicated social and spatial variation in healthcare use cluster membership., Conclusion: Healthcare pathways can help indicate changing need and variation in need, with differential patterns in initial healthcare use post-diagnosis, producing similar subsequent mortality risk. Care in dementia needs to be more accessible and appropriate, with care catered to specific and changing needs. Better continuity of care and greater awareness of dementia in primary can enhance prospects for PLWD. Research needs to further illuminate holistic care need for PLWD, including health and social care use, inequalities in care, health and outcomes., (© 2024. The Author(s).)

Background: Whole-genome sequencing (WGS) is the gold standard diagnostic tool to identify and genetically characterise emerging pathogen mutations (variants), but cost, capacity, and timeliness limit its use when large populations need rapidly assessing. We assessed the potential of genotyping assays to provide accurate and timely variant information at scale by retrospectively examining surveillance for SARS-CoV-2 variants in England between March and September, 2021, when genotyping assays were used widely for variant detection., Methods: We chose a panel of four RT-PCR genotyping assays to detect circulating variants of SARS-COV-2 in England and developed a decision algorithm to assign a probable SARS-CoV-2 variant to samples using the assay results. We extracted surveillance data from the UK Health Security Agency databases for 115 934 SARS-CoV-2-positive samples (March 1-Sept 6, 2021) when variant information was available from both genotyping and WGS. By comparing the genotyping and WGS variant result, we calculated accuracy metrics (ie, sensitivity, specificity, and positive predictive value [PPV]) and the time difference between the sample collection date and the availability of variant information. We assessed the number of samples with a variant assigned from genotyping or WGS, or both, over time., Findings: Genotyping and an initial decision algorithm (April 10-May 11, 2021 data) were accurate for key variant assignment: sensitivities and PPVs were 0·99 (95% CI 0·99-0·99) for the alpha, 1·00 (1·00-1·00) for the beta, and 0·91 (0·80-1·00) for the gamma variants; specificities were 0·97 (0·96-0·98), 1·00 (1·00-1·00), and 1·00 (1·00-1·00), respectively. A subsequent decision algorithm over a longer time period (May 27-Sept 6, 2021 data) remained accurate for key variant assignment: sensitivities were 0·91 (95% CI 0·74-1·00) for the beta, 0·98 (0·98-0·99) for the delta, and 0·93 (0·81-1·00) for the gamma variants; specificities were 1·00 (1·00-1·00), 0·96 (0·96-0·97), and 1·00 (1·00-1·00), respectively; and PPVs were 0·83 (0·62-1·00), 1·00 (1·00-1·00), and 0·78 (0·59-0·97), respectively. Genotyping produced variant information a median of 3 days (IQR 2-4) after the sample collection date, which was faster than with WGS (9 days [8-11]). The flexibility of genotyping enabled a nine-times increase in the quantity of samples tested for variants by this method (from 5000 to 45 000)., Interpretation: RT-PCR genotyping assays are suitable for high-throughput variant surveillance and could complement WGS, enabling larger scale testing for known variants and timelier results, with important implications for effective public health responses and disease control globally, especially in settings with low WGS capacity. However, the choice of panels of RT-PCR assays is highly dependent on database information on circulating variants generated by WGS, which could limit the use of genotyping assays when new variants are emerging and spreading rapidly., Funding: UK Health Security Agency and National Institute for Health Research Health Protection Research Unit in Emergency Preparedness and Response., Competing Interests: Declaration of interests JDMF and PJ are employees of Thermo Fisher Scientific. All other authors declare no competing interests., (Crown Copyright © 2023. Published by Elsevier Ltd. All rights reserved.)

Background: During the COVID-19 pandemic, cases were tracked using multiple surveillance systems. Some systems were completely novel, and others incorporated multiple data streams to estimate case incidence and prevalence. How well these different surveillance systems worked as epidemic indicators is unclear, which has implications for future disease surveillance and outbreak management. The aim of this study was to compare case counts, prevalence and incidence, timeliness, and comprehensiveness of different COVID-19 surveillance systems in England., Methods: For this retrospective observational study of COVID-19 surveillance systems in England, data from 12 surveillance systems were extracted from publicly available sources (Jan 1, 2020-Nov 30, 2021). The main outcomes were correlations between different indicators of COVID-19 incidence or prevalence. These data were integrated as daily time-series and comparisons undertaken using Spearman correlation between candidate alternatives and the most timely (updated daily, clinical case register) and the least biased (from comprehensive household sampling) COVID-19 epidemic indicators, with comparisons focused on the period of Sept 1, 2020-Nov 30, 2021., Findings: Spearman statistic correlations during the full focus period between the least biased indicator (from household surveys) and other epidemic indicator time-series were 0·94 (95% CI 0·92 to 0·95; clinical cases, the most timely indicator), 0·92 (0·90 to 0·94; estimates of incidence generated after incorporating information about self-reported case status on the ZoeApp, which is a digital app), 0·67 (95% CI 0·60 to 0·73, emergency department attendances), 0·64 (95% CI 0·60 to 0·68, NHS 111 website visits), 0·63 (95% CI 0·56 to 0·69, wastewater viral genome concentrations), 0·60 (95% CI 0·52 to 0·66, admissions to hospital with positive COVID-19 status), 0·45 (95% CI 0·36 to 0·52, NHS 111 calls), 0·08 (95% CI -0·03 to 0·18, Google search rank for "covid"), -0·04 (95% CI -0·12 to 0·05, in-hours consultations with general practitioners), and -0·37 (95% CI -0·46 to -0·28, Google search rank for "coronavirus"). Time lags (-14 to +14 days) did not markedly improve these rho statistics. Clinical cases (the most timely indicator) captured a more consistent proportion of cases than the self-report digital app did., Interpretation: A suite of monitoring systems is useful. The household survey system was the most comprehensive and least biased epidemic monitor, but not very timely. Data from laboratory testing, the self-reporting digital app, and attendances to emergency departments were comparatively useful, fairly accurate, and timely epidemic trackers., Funding: National Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, a partnership between the UK Health Security Agency, King's College London, and the University of East Anglia., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

While social and spatial determinants of biomarkers have been reported, no previous study has examined both together within an intersectional perspective. We present a novel extension of quantitative intersectional analyses using cross-classified multilevel models to explore how intersectional positions and neighbourhood deprivation are associated with biomarkers, using baseline UK Biobank data (collected from 2006 to 2010). Our results suggest intersectional inequalities in biomarkers of healthy ageing are mostly established by age 40-49, but different intersections show different relationships with deprivation. Our study suggests that certain biosocial pathways are more strongly implicated in how neighbourhoods and intersectional positions affect healthy ageing than others., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Environmental and management pressures are considered a threat for preserving plant communities worldwide. Identification of long-term impacts of changing management practices on plant community composition must, therefore, be a major priority to ensure improvement in conservation value. Land abandonment/wilding is one topical area where there is little available information on long-term impacts. To address this, here, we describe plant species compositional change over relatively long-time scales in a range of four British upland communities (high-level grasslands, intermediate grasslands, blanket bogs and high-level bogs) and its relationships with a series of life-history and plant trait variables. Our aims were to determine whether the business-as-usual sheep grazing practice was maintaining these communities, and if grazing was to be removed as part of abandonment/wilding strategies, would there be a conservation benefit. We used a series of long-term experimental grazing-exclosure studies at twelve sites (>40 years) on the Moor House National Nature Reserve in northern England. Each site consisted of paired plots; i.e. sheep-grazed versus ungrazed. Our results showed that there was relatively little change in dominant plant species with most change occurring within sub-dominant species. Similarly, different temporal responses in plant species richness were detected between the experiments (richness was reduced in three experiments, only one increased). In any case, the vegetation temporal trajectories were moving in similar direction in grazed and ungrazed plots at most sites. Interestingly, blanket bog experiments showed a clear compositional convergence for both grazed and ungrazed plots, although, the between-site differences related to a combination of elevation and past burning testament. Finally, the bryophytes (especially liverworts) and lichens were the groups that contributed most to the reductions in species richness. Moreover, implementation of a no-stock grazing strategy under a land abandonment/wilding approach will not bring about much plant change in the short-term in the plant communities studied here., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Marrs is President of the Heather Trust, one of the funders. This is an ambassadorial position and has no decision-making authority. The funding was made by the Heather Trust to the University of Liverpool., (Crown Copyright © 2020. Published by Elsevier B.V. All rights reserved.)

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application of our results is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.

In April 2018, Public Health England was notified of cases of Shigella sonnei who had eaten food from three different catering outlets in England. The outbreaks were initially investigated as separate events, but whole-genome sequencing (WGS) showed they were caused by the same strain. The investigation included analyses of epidemiological data, the food chain and microbiological examination of food samples. WGS was used to determine the phylogenetic relatedness and antimicrobial resistance profile of the outbreak strain. Ultimately, 33 cases were linked to this outbreak; the majority had eaten food from seven outlets specialising in Indian or Middle Eastern cuisine. Five outlets were linked to two or more cases, all of which used fresh coriander although a shared supplier was not identified. An investigation at one of the venues recorded that 86% of cases reported eating dishes with coriander as an ingredient or garnish. Four cases were admitted to hospital and one had evidence of treatment failure with ciprofloxacin. Phylogenetic analysis showed that the outbreak strain was part of a wider multidrug-resistant clade associated with travel to Pakistan. Poor hygiene practices during cultivation, distribution or preparation of fresh produce are likely contributing factors.

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/m 3 , 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/m 3 , 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 (NO 2 ) appeared to be associated with increased consultations (for the category 70-85 µg/m 3 , 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) NO 2 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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: This study will analyse respiratory contacts to three healthcare services that capture more of the community disease burden than acute data sources, such as hospitalisations. The objective is to explore associations between contacts to these services and the patient's age, gender and deprivation. Results will be compared between healthcare services, and with non-respiratory contacts to explore how contacts differ by service and illness. It is crucial to investigate the sociodemographic patterns in healthcare-seeking behaviour to enable targeted public health interventions., Design: Ecological study., Setting: Surveillance of respiratory contacts to three healthcare services in England: telehealth helpline (NHS111); general practitioner in-hours (GPIH); and general practitioner out of hours unscheduled care (GPOOH)., Participants: 13 million respiratory contacts to NHS111, GPIH and GPOOH., Outcome Measures: Respiratory contacts to NHS111, GPIH and GPOOH, and non-respiratory contacts to NHS111 and GPOOH., Results: More respiratory contacts were observed for females, with 1.59, 1.73, and 1.95 times the rate of contacts to NHS111, GPOOH and GPIH, respectively. When compared with 15-44 year olds, there were 37.32, 18.66 and 6.21 times the rate of respiratory contacts to NHS111, GPOOH and GPIH in children <1 year. There were 1.75 and 2.70 times the rate of respiratory contacts in the most deprived areas compared with the least deprived to NHS111 and GPOOH. Elevated respiratory contacts were observed for males <5 years compared with females <5 years. Healthcare-seeking behaviours between respiratory and non-respiratory contacts were similar., Conclusion: When contacts to services that capture more of the disease burden are explored, the demographic patterns are similar to those described in the literature for acute systems. Comparable results were observed between respiratory and non-respiratory contacts suggesting that when a wider spectrum of disease is explored, sociodemographic factors may be the strongest influencers of healthcare-seeking behaviour., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Shiga toxin-producing Escherichia coli is carried in the intestine of ruminant animals, and outbreaks have occurred after contact with ruminant animals or their environment. The presence of STEC virulence genes in the environment was investigated along recreational walking paths in the North West and East Anglia regions of England. In all, 720 boot sock samples from walkers' shoes were collected between April 2013 and July 2014. Multiplex PCR was used to detect E. coli based on the amplification of the uidA gene and investigate STEC-associated virulence genes eaeA, stx1 and stx2. The eaeA virulence gene was detected in 45·5% of the samples, where stx1 and/or stx2 was detected in 12·4% of samples. There was a difference between the two regions sampled, with the North West exhibiting a higher proportion of positive boot socks for stx compared to East Anglia. In univariate analysis, ground conditions, river flow and temperature were associated with positive boot socks. The detection of stx genes in the soil samples suggests that STEC is present in the English countryside and individuals may be at risk for infection after outdoor activities even if there is no direct contact with animals. SIGNIFICANCE AND IMPACT OF THE STUDY: Several outbreaks within the UK have highlighted the danger of contracting Shiga toxin-producing Escherichia coli from contact with areas recently vacated by livestock. This is more likely to occur for STEC infections compared to other zoonotic bacteria given the low infectious dose required. While studies have determined the prevalence of STEC within farms and petting zoos, determining the risk to individuals enjoying recreational outdoor activities that occur near where livestock may be present is less researched. This study describes the prevalence with which stx genes, indicative of STEC bacteria, were found in the environment in the English countryside., (© 2020 The Authors. Letters in Applied Microbiology published by John Wiley & Sons Ltd on behalf of Society for Applied Microbiology.)

For much of the 20th century, the Mersey in North West England was one of the worst polluted estuaries in Europe. Water from a range of polluting industries plus domestic sewage was discharged into the Mersey Catchment and Estuary. Recovery came through a concerted clean-up campaign and tightening environmental regulations, partly driven by European Commission Directives, coupled with de-industrialisation from the 1970s onward. Recovery of oxygen levels in the Estuary led to the return of a productive ecosystem. This led to conservation designations, but also concerns about transfer of pollutants to higher trophic levels in fish, birds and humans. As part of urban renewal, ecosystems in disused dock basins were restored using mussel biofiltration and artificial de-stratification, facilitating commercial redevelopment and creation of a tourist destination. The degradation and recovery of the Mersey from peak-pollution in the mid-20th century is put in the context of wider environmental change and briefly compared to other systems to develop a hysteresis model of degradation and recovery, often to novel ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions., Methods: We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included., Results: We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models., Conclusion: Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity., Competing Interests: The authors have declared that no competing interests exist.

Identifying geographical areas with significantly higher or lower rates of infectious diseases can provide important aetiological clues to inform the development of public health policy and interventions designed to reduce morbidity. We applied kernel smoothing to estimate the spatial and spatio-temporal variation in risk of STEC O157 infection in England between 2009 and 2015, and to explore differences between the residential locations of cases reporting travel and those not reporting travel. We provide evidence that the distribution of STEC O157 infection in England is non-uniform with respect to the distribution of the at-risk population; that the spatial distribution of the three main genetic lineages infecting humans (I, II and I/II) differs significantly and that the spatio-temporal risk is highly dynamic. Our results also indicate that cases of STEC O157 reporting travel within or outside the UK are more likely to live in the south/south-east of the country, meaning that their residential location may not reflect the location of exposure that led to their infection. We suggest that the observed variation in risk reflects exposure to sources of STEC O157 that are geographically prescribed. These differences may be related to a combination of changes in the strains circulating in the ruminant reservoir, animal movements (livestock, birds or wildlife) or the behavior of individuals prior to infection. Further work to identify the importance of behaviours and exposures reported by cases relative to residential location is needed., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Many plants benefit from synchronous year-to-year variation in seed production, called masting. Masting benefits plants because it increases the efficiency of pollination and satiates predators, which reduces seed loss. Here, using a 39-year-long dataset, we show that climate warming over recent decades has increased seed production of European beech but decreased the year-to-year variability of seed production and the reproductive synchrony among individuals. Consequently, the benefit that the plants gained from masting has declined. While climate warming was associated with increased reproductive effort, we demonstrate that less effective pollination and greater losses of seeds to predators offset any benefits to the plants. This shows that an apparently simple benefit of climate warming unravels because of complex ecological interactions. Our results indicate that in masting systems, the main beneficiaries of climate-driven increases in seed production are seed predators, not plants.

Effective landscape-scale management of source-sink deer populations will be strengthened by understanding whether local variation in habitat quality drives heterogeneity in productivity. We related female roe deer Capreolus capreolus fecundity and body mass to habitat composition and landscape context, separately for adults and yearlings, using multi-model inference (MMI) applied to a large sample of individuals (yearlings: fecundity = 202, body mass = 395; adults: fecundity = 908, body mass = 1669) culled during 2002-2015 from an extensive (195 km2) heterogeneous forest landscape. Adults were heavier (inter-quartile, IQ, effect size = +0.5kg) when culled in buffers comprising more arable lands while contrary to our prediction no effects on body mass of grassland, young forest or access to vegetation on calcareous soil were found. Heavier adults were more fertile (IQ effect size, +12% probability of having two embryos instead of one or zero). Counter-intuitively, adults with greater access to arable lands were less fecund (IQ effect of arable: -7% probability of having two embryos, instead of one or zero), and even accounting for greater body mass of adults with access to arable, their modelled fecundity was similar to or lower than that of adults in the forest interior. In contrast, effects of grassland, young forest and calcareous soil did not receive support. Yearling body mass had an effect on fecundity twice that found in adults (+23% probability of having one additional embryo), but yearling body mass and fecundity were not affected by any candidate habitat or landscape variables. Effect of arable lands on body mass and fecundity were small, with little variance explained (Coefficient of Variation of predicted fecundity across forest sub-regions = 0.03 for adults). More variance in fecundity was attributed to other differences between forest management sub-regions (modelled as random effects), suggesting other factors might be important. When analysing source-sink population dynamics to support management, an average value of fecundity can be appropriate across a heterogeneous forest landscape., Competing Interests: The authors have declared that no competing interests exist.

International research linking food outlets and body mass index (BMI) is largely cross-sectional, yielding inconsistent findings. However, addressing the exposure of food outlets is increasingly considered as an important adult obesity prevention strategy. Our study investigates associations between baseline food environment types and change in BMI over time. Survey data were used from the Yorkshire Health Study (n=8,864; wave one: 2010-2012, wave two: 2013-2015) for adults aged 18-86. BMI was calculated using self-reported height (cm) and weight (kg). Restaurants, cafés, fast-food, speciality, convenience and large supermarkets were identified from the Ordnance Survey Point of Interest database within 1600m radial buffer of home postcodes. K-means cluster analysis developed food environment typologies based on food outlets and population density. Large supermarkets, restaurants, cafés, fast-food, speciality and convenience food outlets all clustered together to some extent. Three neighbourhood typologies were identified. However, multilevel models revealed that relative to cluster one all were unrelated to change in BMI (cluster 2, b= -0.146 [-0.274, 0.566]; cluster 3, b= 0.065 [-0.224, 0.356]). There was also little evidence of gender-based differences in these associations when examined in a three-way interaction. Policymakers may need to begin to consider multiple types of food outlet clusters, while further research is needed to confirm how these relate to changed BMI., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Motivation: Public health authorities can provide more effective and timely interventions to protect populations during health events if they have effective multi-purpose surveillance systems. These systems rely on aberration detection algorithms to identify potential threats within large datasets. Ensuring the algorithms are sensitive, specific and timely is crucial for protecting public health. Here, we evaluate the performance of three detection algorithms extensively used for syndromic surveillance: the 'rising activity, multilevel mixed effects, indicator emphasis' (RAMMIE) method and the improved quasi-Poisson regression-based method known as 'Farrington Flexible' both currently used at Public Health England, and the 'Early Aberration Reporting System' (EARS) method used at the US Centre for Disease Control and Prevention. We model the wide range of data structures encountered within the daily syndromic surveillance systems used by PHE. We undertake extensive simulations to identify which algorithms work best across different types of syndromes and different outbreak sizes. We evaluate RAMMIE for the first time since its introduction. Performance metrics were computed and compared in the presence of a range of simulated outbreak types that were added to baseline data., Results: We conclude that amongst the algorithm variants that have a high specificity (i.e. >90%), Farrington Flexible has the highest sensitivity and specificity, whereas RAMMIE has the highest probability of outbreak detection and is the most timely, typically detecting outbreaks 2-3 days earlier., Availability and Implementation: R codes developed for this project are available through https://github.com/FelipeJColon/AlgorithmComparison., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press.)

Methods of reconstructing changes in plant traits over long time scales are needed to understand the impact of changing environmental conditions on ecosystem processes and services. Although Holocene pollen have been extensively used to provide records of vegetation history, few studies have adopted a functional trait approach that is pertinent to changes in ecosystem processes. Here, for woody and herbaceous fen peatland communities, we use modern pollen and vegetation data combined with pollen records from Holocene deposits to reconstruct vegetation functional dynamics. The six traits chosen (measures of leaf area-to-mass ratio and leaf nutrient content) are known to modulate species' fitness and to vary with changes in ecosystem processes. We fitted linear mixed effects models between community weighted mean (CWM) trait values of the modern pollen and vegetation to determine whether traits assigned to pollen types could be used to reconstruct traits found in the vegetation from pollen assemblages. We used relative pollen productivity (RPP) correction factors in an attempt to improve this relationship. For traits showing the best fit between modern pollen and vegetation, we applied the model to dated Holocene pollen sequences from Fenland and Romney Marsh in eastern and southern England and reconstructed temporal changes in trait composition. RPP adjustment did not improve the linear relationship between modern pollen and vegetation. Leaf nutrient traits (leaf C and N) were generally more predictable from pollen data than mass-area traits. We show that inferences about biomass accumulation and decomposition rates can be made using Holocene trait reconstructions. While it is possible to reconstruct community-level trends for some leaf traits from pollen assemblages preserved in sedimentary archives in wetlands, we show the importance of testing methods in modern systems first and encourage further development of this approach to address issues concerning the pollen-plant abundance relationship and pollen source area., Competing Interests: The authors have declared that no competing interests exist.

Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms., Methods: A record of the risk assessment process was obtained from Public Health England for all 67,505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final 'Decision' outcome made by an epidemiologist of 'Alert', 'Monitor' or 'No-action'. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of 'No-action' outcomes., Results: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of 'Alert' outcomes. If the 'Alert' and 'Monitor' actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system., Conclusions: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process.

The environment may lead to lower body mass index (BMI) and obesity risk by providing opportunities to be physically active. However, while intuitively appealing, associations are often inconsistent in direction and small scale. This longitudinal study examined if change in BMI and obesity was associated with the availability of physical activity (PA) facilities and parks and explored if these associations differed by age. Longitudinal data (n = 8,864, aged 18-86 years) were provided at baseline (wave I: 2010-2012) and follow up (wave II: 2013-2015) of the Yorkshire Health Study. BMI was calculated using self-reported height (cm) and weight (kg) (obesity = BMI≥30.00). To define availability, home addresses were geocoded based on postcode zone centroids and neighbourhood was defined as a 2 km radial buffer. PA facilities were sourced from Ordnance Survey Points of Interest (PoI) and parks were sourced from OpenStreetMap. Environmental data temporally matched individual-level baseline data collection. PA facilities (b = -0.006 [-0.015, 0.003]) and parks (b = -0.001 [-0.015, 0.013]) at baseline were not associated with change in BMI. Change in obesity was unrelated to parks (OR = 0.994 [0.975, 1.015]) and while PA facilities were related (OR = 0.979 [0.965, 0.993]), effects were small. A combined measure of the recreational PA environment including parks and PA facilities was unrelated to change in BMI and obesity. Despite this, statistically significant interactions were found for both PA facilities, parks, and change in obesity by age. Based on the premise that an individual's mobility varies with age, and although effects were small, this offers tentative evidence which suggests it may be useful for policymakers in Public Health and Planning to consider the impact of environmental interventions across the life course., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The Asian tiger mosquito Aedes albopictus is able to transmit various pathogens to humans and animals and it has already caused minor outbreaks of dengue and chikungunya in southern Europe. Alarmingly, it is spreading northwards and its eggs have been found in the UK in 2016 and 2017. Climate-driven models can help to analyse whether this originally subtropical species could become established in northern Europe. But so far, these models have not considered the impact of the diurnal temperature range (DTR) experienced by mosquitoes in the field. Here, we describe a dynamical model for the life cycle of Ae. albopictus, taking into account the DTR, rainfall, photoperiod and human population density. We develop a new metric for habitat suitability and drive our model with different climate data sets to analyse the UK's suitability for this species. For now, most of the UK seems to be rather unsuitable, except for some densely populated and high importation risk areas in southeast England. But this picture changes in the next 50 years: future scenarios suggest that Ae. albopictus could become established over almost all of England and Wales, indicating the need for continued mosquito surveillance.

This study investigated if the relationship between residential fast-food outlet availability and obesity varied due to methodological diversity or by age. Cross-sectional data (n = 22,889) from the Yorkshire Health Study, England were used. Obesity was defined using self-reported height and weight (BMI ≥ 30). Food outlets ("fast-food", "large supermarkets", and "convenience or other food retail outlets") were mapped using Ordnance Survey Points of Interest (PoI) database. Logistic regression was used for all analyses. Methodological diversity included adjustment for other food outlets as covariates and continuous count vs. quartile. The association between residential fast-food outlets and obesity was inconsistent and effects remained substantively the same when considering methodological diversity. This study contributes to evidence by proposing the use of a more comprehensive conceptual model adjusting for wider markers of the food environment. This study offers tentative evidence that the association between fast-food outlets and obesity varies by age., (Copyright © 2018. Published by Elsevier Ltd.)

Background: With over 800 million cases globally, campylobacteriosis is a major cause of food borne disease. In temperate climates incidence is highly seasonal but the underlying mechanisms are poorly understood, making human disease control difficult. We hypothesised that observed disease patterns reflect complex interactions between weather, patterns of human risk behaviour, immune status and level of food contamination. Only by understanding these can we find effective interventions., Methods: We analysed trends in human Campylobacter cases in NE England from 2004 to 2009, investigating the associations between different risk factors and disease using time-series models. We then developed an individual-based (IB) model of risk behaviour, human immunological responses to infection and environmental contamination driven by weather and land use. We parameterised the IB model for NE England and compared outputs to observed numbers of reported cases each month in the population in 2004-2009. Finally, we used it to investigate different community level disease reduction strategies., Results: Risk behaviours like countryside visits (t = 3.665, P < 0.001 and t = - 2.187, P = 0.029 for temperature and rainfall respectively), and consumption of barbecued food were strongly associated with weather, (t = 3.219, P = 0.002 and t = 2.015, P = 0.045 for weekly average temperature and average maximum temperature respectively) and also rain (t = 2.254, P = 0.02527). This suggests that the effect of weather was indirect, acting through changes in risk behaviour. The seasonal pattern of cases predicted by the IB model was significantly related to observed patterns (r = 0.72, P < 0.001) indicating that simulating risk behaviour could produce the observed seasonal patterns of cases. A vaccination strategy providing short-term immunity was more effective than educational interventions to modify human risk behaviour. Extending immunity to 1 year from 20 days reduced disease burden by an order of magnitude (from 2412-2414 to 203-309 cases per 50,000 person-years)., Conclusions: This is the first interdisciplinary study to integrate environment, risk behaviour, socio-demographics and immunology to model Campylobacter infection, including pathways to mitigation. We conclude that vaccination is likely to be the best route for intervening against campylobacteriosis despite the technical problems associated with understanding both the underlying human immunology and genetic variation in the pathogen, and the likely cost of vaccine development.

Background: Previous research shows that mortality varies significantly by residential context; however, the nature of this variation is unclear. Some studies report higher mortality levels in urban compared to rural areas, whereas others suggest elevated mortality in rural areas or a complex U-shaped relationship. Further, the extent to which compositional factors explain urban-rural mortality variation, the extent to which contextual factors play a role and whether and how the patterns vary by gender also remain unclear. This study investigates urban-rural mortality variation in England and Wales and the causes of this variation., Method: The study applies survival analysis to the Office for National Statistics Longitudinal Study; the population aged 20 and older in 2001 is followed for 10 years., Results and Conclusions: The analysis demonstrates a clear urban-rural mortality gradient, with the risk of dying increasing with each level of urbanisation. The exceptions are those living in areas adjacent to London, who consistently exhibit lower mortality than anticipated. Once the models are adjusted to individuals' socio-economic characteristics, the variation across the urban-rural continuum reduces substantially, although the gradient persists suggesting contextual effects. Females are found to be influenced more by their surrounding environment and males by their socio-economic position, although both experience lower mortality in rural compared to urban areas., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: This paper examines cause-specific mortality by partnership status. Although non-marital cohabitation has spread rapidly in industrialised countries, only a few studies have investigated mortality by partnership status and no recent study has investigated cause-specific mortality by partnership status., Methods: We use data from the Office for National Statistics Longitudinal Study and apply competing risks survival models., Results: The simultaneous analysis shows that married individuals have lower mortality than non-married from circulatory, respiratory, digestive, alcohol and accident related causes of deaths, but not from cancer. The analysis by partnership status reveals that once we distinguish premarital and postmarital cohabitants from other non-married groups, the differences between partnered and non-partnered individuals become even more pronounced for all causes of death; this is largely due to similar cause-specific mortality levels between married and cohabiting individuals., Conclusions: With declining marriage rates and the spread of cohabitation and separation, a distinction between partnered and non-partnered individuals is critical to understanding whether and how having a partner shapes the individuals' health behaviour and mortality. The cause-specific analysis supports both the importance of selection into partnership and the protective effect of living with someone together., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Carbonate formation in waste from the steel industry could constitute a nontrivial proportion of the global requirements for removing carbon dioxide from the atmosphere at a potentially low cost. To utilize this potential, we examined atmospheric carbon dioxide sequestration in a >20 million ton legacy slag deposit in northern England, United Kingdom. Carbonates formed from the drainage water of the heap had stable carbon and oxygen isotope values between -12 and -25 ‰ and -5 and -18 ‰ for δ 13 C and δ 18 O, respectively, suggesting atmospheric carbon dioxide sequestration in high-pH solutions. From the analyses of solution saturation states, we estimate that between 280 and 2900 tons of CO 2 have precipitated from the drainage waters. However, by combining a 37 year long data set of the drainage water chemistry with geospatial analysis, we estimate that <1% of the maximum carbon-capture potential of the deposit may have been realized. This implies that uncontrolled deposition of slag is insufficient to maximize carbon sequestration, and there may be considerable quantities of unreacted legacy deposits available for atmospheric carbon sequestration.

Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect., Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of detection to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis., Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different outbreak types with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings., Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response.

This paper introduces a novel method for sampling pathogens in natural environments. It uses fabric boot socks worn over walkers' shoes to allow the collection of composite samples over large areas. Wide-area sampling is better suited to studies focusing on human exposure to pathogens (e.g., recreational walking). This sampling method is implemented using a citizen science approach: groups of three walkers wearing boot socks undertook one of six routes, 40 times over 16 months in the North West (NW) and East Anglian (EA) regions of England. To validate this methodology, we report the successful implementation of this citizen science approach, the observation that Campylobacter bacteria were detected on 47% of boot socks, and the observation that multiple boot socks from individual walks produced consistent results. The findings indicate higher Campylobacter levels in the livestock-dominated NW than in EA (55.8% versus 38.6%). Seasonal differences in the presence of Campylobacter bacteria were found between the regions, with indications of winter peaks in both regions but a spring peak in the NW. The presence of Campylobacter bacteria on boot socks was negatively associated with ambient temperature ( P = 0.011) and positively associated with precipitation ( P < 0.001), results consistent with our understanding of Campylobacter survival and the probability of material adhering to boot socks. Campylobacter jejuni was the predominant species found; Campylobacter coli was largely restricted to the livestock-dominated NW. Source attribution analysis indicated that the potential source of C. jejuni was predominantly sheep in the NW and wild birds in EA but did not differ between peak and nonpeak periods of human incidence. IMPORTANCE There is debate in the literature on the pathways through which pathogens are transferred from the environment to humans. We report on the success of a novel method for sampling human-pathogen interactions using boot socks and citizen science techniques, which enable us to sample human-pathogen interactions that may occur through visits to natural environments. This contrasts with traditional environmental sampling, which is based on spot sampling techniques and does not sample human-pathogen interactions. Our methods are of practical value to scientists trying to understand the transmission of pathogens from the environment to people. Our findings provide insight into the risk of Campylobacter exposure from recreational visits and an understanding of seasonal differences in risk and the factors behind these patterns. We highlight the Campylobacter species predominantly encountered and the potential sources of C. jejuni ., (Copyright © 2017 Jones et al.)

Exercise causes alterations in redox homeostasis (ARH). Measuring ARH in elite athletes may aid in the identification of training tolerance, fatigued states, and underperformance. To the best of our knowledge, no studies have examined ARH in elite male and female distance runners at sea level. The monitoring of ARH in athletes is hindered by a lack of reliable and repeatable in-the-field testing tools and by the rapid turnaround of results. We examined the effects of various exercise intensities on ARH in healthy (non-over-reached) elite male and female endurance athletes using clinical point-of-care (POC) redox tests, referred to as the free oxygen radical test (FORT) (pro-oxidant) and the free oxygen radical defence (FORD) (antioxidant). Elite male and female endurance athletes (n = 22) completed a discontinuous incremental treadmill protocol at submaximal running speeds and a test to exhaustion. Redox measures were analyzed via blood sampling at rest, warm-up, submaximal exercise, exhaustion, and recovery. FORD was elevated above rest after submaximal and maximal exercise, and recovery (p < 0.05, d = 0.87-1.55), with only maximal exercise and recovery increasing FORT (p < 0.05, d = 0.23-0.32). Overall, a decrease in oxidative stress in response to submaximal and maximal exercise was evident (p < 0.05, d = 0.46). There were no gender differences for ARH (p > 0.05). The velocity at lactate threshold (vLT) correlated with the FORD response at rest, maximal exercise, and recovery (p < 0.05). Using the clinical POC redox test, an absence of oxidative stress after exhaustive exercise is evident in the nonfatigued elite endurance athlete. The blood antioxidant response (FORD) to exercise appears to be related to a key marker of aerobic fitness: vLT.

Background: Determining the host feeding patterns of mosquitoes by identifying the origin of their blood-meals is an important part of understanding the role of vector species in current and future disease transmission cycles. Collecting large numbers of blood-fed mosquitoes from the field is difficult, therefore it is important to maximise the information obtained from each specimen. This study aimed to use mosquito genome sequence to identify the species within Anopheles maculipennis sensu lato (An. maculipennis s.l.), identify the vertebrate hosts of field-caught blood-fed An. maculipennis s.l. , and to test for the presence of myxoma virus (Poxviridae, genus Leporipoxvirus) in specimens found to have fed on the European rabbit (Oryctolagus cuniculus)., Methods: Blood-fed An. maculipennis s.l. were collected from resting sites at Elmley Nature Reserve, Kent, between June and September 2013. Hosts that An. maculipennis s.l. had fed on were determined by a PCR-sequencing approach based on the partial amplification of the mitochondrial cytochrome C oxidase subunit I gene. Mosquitoes were then identified to species by sequencing a region of the internal transcribed spacer-2. DNA extracts from all mosquitoes identified as having fed on rabbits were subsequently screened using PCR for the presence of myxoma virus., Results: A total of 94 blood-fed Anopheles maculipennis s.l. were collected, of which 43 (46%) provided positive blood-meal identification results. Thirty-six of these specimens were identified as Anopheles atroparvus, which had fed on rabbit (n = 33, 92%) and cattle (n = 3, 8%). Seven mosquitoes were identified as Anopheles messeae, which had fed on cattle (n = 6, 86%) and dog (n = 1, 14%). Of the 33 An. atroparvus that contained rabbit blood, nine (27%) were positive for myxoma virus., Conclusions: Results demonstrate that a single DNA extract from a blood-fed mosquito can be successfully used for molecular identification of members of the An. maculipennis complex, blood-meal identification, and for the targeted detection of a myxoma virus. This study shows that An. atroparvus has a strong feeding preference for both healthy and myxoma-infected rabbits, providing evidence that this species may play a significant role in the transmission of myxomatosis among wild rabbit populations in the United Kingdom (UK).

Studies of geographical variations in physical activity behaviours have suggested that activity levels are particularly low in areas that have undergone employment loss associated with the decline of industry. This is of concern given that affected populations are already at risk of poor health. Applying focus group methodology amongst 19 participants in four groups, this study aims to unpack how broader societal and environmental changes associated with industrial decline affect beliefs and attitudes towards physical activity in ex-mining communities in the North-East of England. Identified core themes comprise the direct impact of deindustrialisation on social and physical environments. Based on our findings, we provide evidence for mechanisms that operate via loss of occupational physical activity as well as the progressive development of environments that are not fit to support population activity levels. Particularly important was the loss of recreational facilities, public green spaces and sports facilities that were owned and organised by the miners themselves with support from the mining companies. Attitudes and beliefs directly related to the areas' industrial past were also seen to be key. We suggest that the development of interventions considering the socio-cultural history and socio-economic reality of communities could be a promising route to encourage more active lifestyles in deprived areas with particularly low levels of physical activity., (Copyright © 2015. Published by Elsevier Ltd.)

Previous research shows low mortality for most immigrants compared to natives in host countries. This advantage is often attributed to health selection processes in migration and to protective health behaviours. Little research has examined the role of data quality, especially the registration of moves. Registration errors relating to moves between origin and host countries can mismatch deaths and risk populations, leading to denominator bias and an under-estimation of migrant mortality (data artefact). The paper investigates the mortality of immigrants in England and Wales from 1971 to 2001 using the Office for National Statistics Longitudinal Study (ONS LS), a 1% sample of the population of England and Wales. We apply parametric survival models to study the mortality of 450,000 individuals. We conduct sensitivity analysis to assess the impact of entry and exit uncertainty on immigrant mortality rates. The analysis shows that most international migrants have lower mortality than natives in England and Wales. Differences largely persist when we adjust models to entry and exit uncertainty and they become pronounced once we control for individual socioeconomic characteristics. This study supports low mortality among immigrants and shows that results are not a data artefact., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Using a large cross sectional English sample, we quantified the association between weight status in children aged 4-5 and 10-11 year, characteristics of the food environment, and area deprivation. We observed a positive association between the density of unhealthy food outlets in a neighbourhood and the prevalence of overweight and obesity in children. An association in the opposite direction was observed for other types of food outlets, although after adjustment this was only statistically significant for older children. The prevalence of fast food and other unhealthy food outlets explained only a small proportion of the observed associations between weight status and socioeconomic deprivation. Children׳s weight status may be influenced by their local environment, particularly older children, but associations between obesity and deprivation do not appear strongly due to local food environment characteristics., (Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The health of rural and urban populations differs, with rural areas appearing healthier. However, it is unknown whether the benefit of living in rural areas is felt by individuals in all levels of deprivation, or whether some suffer a disadvantage of rural residence. For England and Wales 2001-2003 premature mortality rates were calculated, subdivided by individual deprivation and gender, for areas with differing rurality characteristics. Premature mortality data (age 50-retirement) and a measure of the individual's deprivation (National Statistics Socio-economic Classification 1-7) was obtained from death certificates. Overall premature mortality was examined as well as premature mortality subdivided by major cause. Male premature mortality rates (age 50-64) fell with increasing rurality for individuals in all socio-economic status classifications. The most deprived individuals benefitted most from residence in increasingly rural areas. Similar trends were observed when premature mortality was subdivided by the major causes of death. Female premature mortality rates (age 50-59) demonstrated similar trends but the differences between urban and rural areas were less marked., (© 2013 Elsevier Ltd. All rights reserved.)

Objective: To examine the association between breakfast consumption and physical activity in a well-characterised sample of English children., Design: Cross-sectional study using food diaries to record breakfast consumption and accelerometry to assess physical activity., Setting: Norfolk county, England., Subjects: Children (n 1697) aged 9–10 years from the SPEEDY (Sport, Physical Activity and Eating behaviour: Environmental Determinants in Young people) study., Results: Boyswho consumed a poor-quality breakfast based on dairy product, cereal and fruit intakes spent approximately 7 min more time in moderate-to-vigorous physical activity (MVPA) during weekday afternoons and evenings compared with those who did not consume breakfast (P,0?05). On weekend days, boys who consumed a poor- or good-quality breakfast spent approximately 6 and 5min less time respectively being sedentary during the mornings compared with breakfast nonconsumers (P,0?05). Boys who consumed a good-quality breakfast spent almost 3min more in MVPA during the morning on weekend days compared with nonconsumers, and boys who consumed a poor- or good-quality breakfast were 22% and 16% more active overall respectively than breakfast non-consumers (P,0?05). During the rest of the day, boys who consumed a good-quality breakfast spent about 11 min less time being sedentary (P,0?05) and 7minmore time in MVPA (P,0?01)., Conclusions: Although some associations between breakfast consumption and physical activity were detected for boys, the present study does not provide strong evidence that failing to consume breakfast, or having a low energy intake at breakfast time, is detrimental to children’s physical activity levels.

Introduction: Process evaluations of environmental public health interventions tend not to consider issues of spatial equity in programme delivery. However, an intervention is unlikely to be effective if it is not accessible to those in need. Methods are required to enable these considerations to be integrated into evaluations. Using the Healthy Towns programme in England, we demonstrate the potential of spatial equity analysis in the evaluation of environmental interventions for diet and physical activity, examining whether the programme was delivered to those in greatest need., Methods: Locations of new physical infrastructure, such as cycle lanes, gyms and allotments, were mapped using a geographic information system. A targeting ratio was computed to indicate how well-located the infrastructure was in relation to those at whom it was specifically aimed, as detailed in the relevant project documentation, as well as to generally disadvantaged populations defined in terms of U.K. Census data on deprivation, age and ethnicity. Differences in targeting were examined using Kruskal-Wallis and t-tests., Results: The 183 separate intervention components identified were generally well located, with estimated targeting ratios above unity for all population groups of need, except for black and ethnic minorities and children aged 5-19 years. There was no evidence that clustering of population groups influenced targeting, or that trade-offs existed when components were specifically targeted at more than one group., Conclusions: The analysis of spatial equity is a valuable initial stage in assessing the provision of environmental interventions. The Healthy Towns programme can be described as well targeted in that interventions were for the most part located near populations of need.

Using a sample of English school children, we use accelerometery and global positioning systems to identify whether different intensities of activity (light, moderate, and vigorous) occur in different environments, and whether environments for bouts of moderate to vigorous activity (MVPA) vary from those for non-bout MVPA. We find that land uses such as buildings and roads and pavements were generally used for light activity, whilst green environments such as gardens, parks, grassland and farmland appear supportive of vigorous activity. Built land uses such as hard surface play areas were particularly used for activity of short duration. Future work may consider differentiating light activity from moderate and vigorous, and separating bout and non-bout MVPA to better identify environmental supportiveness for activity in children., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Urban greenspace is hypothesised to be an important location for physical activity in children, but their actual use of the resource to be active is not well known. In this study, global positioning systems (GPS) and accelerometers were used to measure activity within green environments for 902 English children aged 11-12. We summarised activity intensities in different types of greenspace on weekday evenings, weekend days and by season. Around half of outdoor moderate-vigorous activity took place in greenspace at the weekend and use was consistent across seasons. The findings suggest the importance of certain types of greenspace to children's physical activity., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Road bends are known to cause traffic crashes, but the hypothesis in this study was that small geographical areas with many road bends have less, not more, road casualties than comparable areas with fewer bends. Data on road crashes involving fatal, serious and slight casualties in 571 wards in Eastern England were examined against four measures of average road curvature (mean angle per bend, cumulative angle per km, number of bends per km and ratio of road distance to straight distance) using regression analysis. Taking account of other risk factors, measures of average road curvature in wards were negatively associated with crash numbers, especially for fatal crashes. The strongest associations were with the cumulative angle turned per km. The results add to evidence suggesting that road casualty risk effects vary with geographical scale. Although individual road bends might be hazardous, frequent bends have a protective effect over a few kilometres of road., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

A dual-isotope and solute flux mass-balance was used to elucidate the processes that lead to attenuation of nitrogen contamination in an agriculturally impacted river. The River Wensum drains a lowland catchment with an area of 570 km² in East Anglia, eastern England. Analysis of nitrate concentration, δ¹⁵N(NO₃) and δ¹⁸O(NO₃) of samples from the River Wensum collected from upstream locations to the catchment outlet through all seasons and flow conditions showed a consistent pattern of increasing isotope values with decreasing nitrate concentrations downstream. δ¹⁵N(NO₃) and δ¹⁸O(NO₃) of catchment surface water and groundwater samples revealed a dominant influence from microbially cycled and nitrified source-nitrogen, which results in high nitrate concentrations in Chalk groundwater and upstream in the River Wensum. Denitrification of Chalk groundwater-baseflow in the hyporheic zone results in the downstream trend observed in the river. Hyporheic denitrification is estimated to remove 931 kg/day of nitrate-nitrogen by the catchment outlet, representing 31% of the potential riverine nitrate load. The use of dual-isotope and solute flux modeling at the catchment scale is a novel application to quantify denitrification within the river valley, demonstrating the importance of hyporheic zone processes in attenuating the impacts of anthropogenic contamination of hydrologic systems.

The rapid speed of the recent rise in obesity rates suggest environmental causes. There is therefore a need to determine which components of the environment may be contributing to this increase. In this cross-sectional study, we examined the associations between adiposity and the characteristics of areas around homes, schools and routes to school among 1995 9-10 year old boys and girls in Norfolk, UK. The relationships between Fat Mass Index (FMI, calculated as fat mass (kg)/height (m)(2)) and objectively computed environmental indicators describing access to food outlets and physical activity facilities, the safety and connectivity of the road network, and the mix of land uses present were investigated. Multivariable hierarchical regression models were fitted with log-transformed FMI as the outcome, and stratification by gender and mode of travel to school. Among girls, better access to healthy food outlets (supermarkets and greengrocers) in the home environment was associated with lower FMI while better access to unhealthy outlets (takeaways and convenience stores) around homes and schools was associated with higher FMI. Also in girls, a higher proportion of accessible open land and a lower mix of land uses around the school were associated with higher FMI. Among boys the presence of major roads in the home neighbourhood was associated with higher FMI among non-active travellers, while major roads in the school neighbourhood were associated with lower FMI among active travellers. No significant associations were seen between FMI and any of the route characteristics. While the relative paucity of associations provides few indicators for the design of effective interventions, there was some evidence that environmental characteristics may be more important among active travellers than non-active travellers, and among girls than boys, suggesting that future interventions should be sensitive to such differences., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Background: The rising prevalence of childhood obesity is a key public health issue worldwide. Limited evidence suggests that there may be interactions between environmental factors at a neighborhood level and the development of obesity, with the availability and accessibility of food outlets being potentially important., Purpose: To examine how the weight status and dietary intake of 1669 children aged 9-10 years was associated with neighborhood food outlets in a cross-sectional study., Methods: Availability of food outlets was computed from GIS data for each child's unique neighborhood. Outlets were grouped into BMI-healthy, BMI-unhealthy, or BMI-intermediate categories according to food type sold. Weight status measurements were objectively collected, and food intake was recorded using 4-day food diaries. Data were collected in 2007 and analyzed in 2009., Results: Availability of BMI-healthy outlets in neighborhoods was associated with lower body weight (1.3 kg, p=0.03); BMI (0.5 kg/m(2), p=0.02); BMI z-score (0.20, p=0.02); waist circumference (1.3 cm, p=0.02); and percentage body fat (1.1%, p=0.03) compared to no availability. In contrast, neighborhood availability of BMI-unhealthy outlets was inversely associated with body weight (1.3 kg, p=0.02); BMI (0.4 kg/m(2), p=0.05); BMI z-score (0.15, p=0.05); waist circumference (1.1 cm, p=0.04); and percentage body fat (1.0%, p=0.03). Unhealthy food intake (fizzy drinks 15.3%, p=0.04, and noncarbonated "fruit" drinks 11.8%, p=0.03) was also associated with availability of BMI-unhealthy food outlets., Conclusions: Features of the built environment relating to food purchasing opportunities are correlated with weight status in children., (Copyright © 2011 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Levels of physical activity have declined considerably over recent decades in England, and there is evidence that activity patterns vary across areas. Previous studies of the geography of physical activity have frequently relied on model based synthetic estimates. Using data from a large population survey this study develops a direct measure of recreational physical activity and investigates variations in activity patterns across English Local Authorities. For both sexes the results show a distinct geography of recreational physical activity associated with north/south variations and urban/rural status. The environmental and behavioural factors driving those patterns are still poorly understood. We conclude that the variations observed might reflect recreational opportunities and the socio-cultural context of areas., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Background: Numerous studies have suggested an inverse relationship between drinking water hardness and cardiovascular disease. However, the weight of evidence is insufficient for the WHO to implement a health-based guideline for water hardness. This study followed WHO recommendations to assess the feasibility of using ecological time series data from areas exposed to step changes in water hardness to investigate this issue., Method: Monthly time series of cardiovascular mortality data, subdivided by age and sex, were systematically collected from areas reported to have undergone step changes in water hardness, calcium and magnesium in England and Wales between 1981 and 2005. Time series methods were used to investigate the effect of water hardness changes on mortality., Results: No evidence was found of an association between step changes in drinking water hardness or drinking water calcium and cardiovascular mortality. The lack of areas with large populations and a reasonable change in magnesium levels precludes a definitive conclusion about the impact of this cation. We use our results on the variability of the series to consider the data requirements (size of population, time of water hardness change) for such a study to have sufficient power. Only data from areas with large populations (>500,000) are likely to be able to detect a change of the size suggested by previous studies (rate ratio of 1.06)., Conclusion: Ecological time series studies of populations exposed to changes in drinking water hardness may not be able to provide conclusive evidence on the links between water hardness and cardiovascular mortality unless very large populations are studied. Investigations of individuals may be more informative.

Background: There is some previous evidence that diagnosis of cancer at death, recorded as registry death certificate only records, is associated with problems of access to care., Methods: Records from the Northern and Yorkshire Cancer Registry for patients registered with breast, colorectal, lung, ovarian or prostate cancer between 1994 and 2002 were supplemented with measures of travel time to general practitioner and hospital services, and social deprivation. Logistic regression was used to identify predictors of records where diagnosis was at death., Results: There was no association between the odds diagnosis at death and access to primary care. For all sites except breast, the highest odds of being a cancer diagnosed at death fell among those living in the highest quartile of hospital travel time, although it was only statistically significant for colorectal and ovary tumours. Those in the most deprived and furthest travel time to hospital quartile were 2.6 times more likely to be a diagnosis at death case compared with those in the most affluent and proximal areas., Conclusions: There is some evidence that poorer geographical access to tertiary care, in particular when coupled with social disadvantages, may be associated with increased odds of diagnosis at death.