National predictors of hedgehog Erinaceus europaeus distribution and decline in Britain

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Abstract We utilise a volunteer survey recording roadkills between 2001 and 2011 to examine the factors affecting hedgehog Erinaceus europaeus abundance and decline. Hedgehogs were most abundant in the North and East of England and in Scotland, regions characterised by low badger numbers. Hedgehogs selected arable land and urban areas relative to their availability. Badger Meles meles and fox Vulpes vulpes abundance were negatively associated with hedgehog abundance at the 10 km2 scale. At the county level, foxes were positively associated with hedgehog numbers and badgers negatively associated. The mechanism behind the relationships between hedgehogs and badgers and foxes merits further investigation.

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  • 10.1136/bmjopen-2016-014210
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  • Mar 1, 2017
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ObjectivesThis paper compares patterns of smoking and high-risk alcohol use across regions in England, and assesses the impact on these of adjusting for sociodemographic characteristics.DesignPopulation survey of 53 922 adults...

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Spatial Statistics and Influencing Factors of the COVID-19 Epidemic at Both Prefecture and County Levels in Hubei Province, China.
  • May 31, 2020
  • International Journal of Environmental Research and Public Health
  • Yongzhu Xiong + 3 more

The coronavirus disease 2019 (COVID-19) epidemic has had a crucial influence on people’s lives and socio-economic development. An understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic on multiple scales could benefit the control of the outbreak. Therefore, we used spatial autocorrelation and Spearman’s rank correlation methods to investigate these two topics, respectively. The COVID-19 epidemic data reported publicly and relevant open data in Hubei province were analyzed. The results showed that (1) at both prefecture and county levels, the global spatial autocorrelation was extremely significant for the cumulative confirmed COVID-19 cases (CCC) in Hubei province from 30 January to 18 February 2020. Further, (2) at both levels, the significant hotspots and cluster/outlier areas were observed solely in Wuhan city and most of its districts/sub-cities from 30 January to 18 February 2020. (3) At the prefecture level in Hubei province, the number of CCC had a positive and extremely significant correlation (p < 0.01) with the registered population (RGP), resident population (RSP), Baidu migration index (BMI), regional gross domestic production (GDP), and total retail sales of consumer goods (TRS), respectively, from 29 January to 18 February 2020 and had a negative and significant correlation (p < 0.05) with minimum elevation (MINE) from 2 February to 18 February 2020, but no association with the land area (LA), population density (PD), maximum elevation (MAXE), mean elevation (MNE), and range of elevation (RAE) from 23 January to 18 February 2020. (4) At the county level, the number of CCC in Hubei province had a positive and extremely significant correlation (p < 0.01) with PD, RGP, RSP, GDP, and TRS, respectively, from 27 January to 18 February 2020, and was negatively associated with MINE, MAXE, MNE, and RAE, respectively, from 26 January to 18 February 2020, and negatively associated with LA from 30 January to 18 February 2020. It suggested that (1) the COVID-19 epidemics at both levels in Hubei province had evident characteristics of significant global spatial autocorrelations and significant centralized high-risk outbreaks. (2) The COVID-19 epidemics were significantly associated with the natural factors, such as LA, MAXE, MNE, and RAE, -only at the county level, not at the prefecture level, from 2 February to 18 February 2020. (3) The COVID-19 epidemics were significantly related to the socioeconomic factors, such as RGP, RSP, TRS, and GDP, at both levels from 26 January to 18 February 2020. It is desired that this study enrich our understanding of the spatiotemporal patterns and influencing factors of the COVID-19 epidemic and benefit classified prevention and control of the COVID-19 epidemic for policymakers.

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G430(P) Research and development approval timelines for an NIHR portfolio adopted multicentre observational study in England and Wales
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Over the last 15 years the processes for obtaining research and development (R&D) approval for conducting multicentre medical research in England have undergone some changes. The introduction of participant identification...

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The Occurrence of Palæoliths in North-East Lancashire
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Large-scale implementation of stroke early supported discharge: the WISE realist mixed-methods study
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Background In England, the provision of early supported discharge is recommended as part of an evidence-based stroke care pathway. Objectives To investigate the effectiveness of early supported discharge services when implemented at scale in practice and to understand how the context within which these services operate influences their implementation and effectiveness. Design A mixed-methods study using a realist evaluation approach and two interlinking work packages was undertaken. Three programme theories were tested to investigate the adoption of evidence-based core components, differences in urban and rural settings, and communication processes. Setting and interventions Early supported discharge services across a large geographical area of England, covering the West and East Midlands, the East of England and the North of England. Participants Work package 1: historical prospective patient data from the Sentinel Stroke National Audit Programme collected by early supported discharge and hospital teams. Work package 2: NHS staff (n = 117) and patients (n = 30) from six purposely selected early supported discharge services. Data and main outcome Work package 1: a 17-item early supported discharge consensus score measured the adherence to evidence-based core components defined in an international consensus document. The effectiveness of early supported discharge was measured with process and patient outcomes and costs. Work package 2: semistructured interviews and focus groups with NHS staff and patients were undertaken to investigate the contextual determinants of early supported discharge effectiveness. Results A variety of early supported discharge service models had been adopted, as reflected by the variability in the early supported discharge consensus score. A one-unit increase in early supported discharge consensus score was significantly associated with a more responsive early supported discharge service and increased treatment intensity. There was no association with stroke survivor outcome. Patients who received early supported discharge in their stroke care pathway spent, on average, 1 day longer in hospital than those who did not receive early supported discharge. The most rural services had the highest service costs per patient. NHS staff identified core evidence-based components (e.g. eligibility criteria, co-ordinated multidisciplinary team and regular weekly multidisciplinary team meetings) as central to the effectiveness of early supported discharge. Mechanisms thought to streamline discharge and help teams to meet their responsiveness targets included having access to a social worker and the quality of communications and transitions across services. The role of rehabilitation assistants and an interdisciplinary approach were facilitators of delivering an intensive service. The rurality of early supported discharge services, especially when coupled with capacity issues and increased travel times to visit patients, could influence the intensity of rehabilitation provision and teams’ flexibility to adjust to patients’ needs. This required organising multidisciplinary teams and meetings around the local geography. Findings also highlighted the importance of good leadership and communication. Early supported discharge staff highlighted the need for collaborative and trusting relationships with patients and carers and stroke unit staff, as well as across the wider stroke care pathway. Limitations Work package 1: possible influence of unobserved variables and we were unable to determine the effect of early supported discharge on patient outcomes. Work package 2: the pragmatic approach led to ‘theoretical nuggets’ rather than an overarching higher-level theory. Conclusions The realist evaluation methodology allowed us to address the complexity of early supported discharge delivery in real-world settings. The findings highlighted the importance of context and contextual features and mechanisms that need to be either addressed or capitalised on to improve effectiveness. Trial registration Current Controlled Trials ISRCTN15568163. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 9, No. 22. See the NIHR Journals Library website for further project information.

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Introduction: At present there is no national register of the population size and scope of reporting radiographers in England. This makes operational workforce and succession planning for sustainable healthcare services in the National Health Service England (NHSE) difficult, affecting implementing NHSE policies and priorities such as 50% of X-rays reported by reporting radiographers and decreasing reporting Turnaround Times (TATs). This survey aimed to establish the workforce population employed as reporting radiographers in NHSE. Methods: An online anonymous seven question survey was distributed on social media and at the UK Imaging and Oncology Congress. Participant criteria included NHSE radiology staff (diagnostic radiographer, reporting radiographer, radiology manager, imaging superintendent modality lead, consultant radiologist, etc.) or a student diagnostic radiographer working within an NHSE trust. The survey recorded the participant's NHSE region (North Western, North Eastern and Yorkshire, Midlands, East of England, London, South Eastern and South Western regions), Integrated Care Systems (ICS), NHSE Trust, hospital, the amount of reporting radiographers and trainees employed, the Agenda for Change (AfC) job banding and imaging modality reported (X-ray, CT, MRI, NM, PET, DEXA). The data analysis applied descriptive statistics for estimating patterns and trends in the distrubtion of data (English region, AfC banding and imaging modality). Results: Responses were received from all seven of the NHSE regions (n=36/43 ICSs). The data demonstrated a larger workforce in the north of England than in the south, with employment at a range of AfC bandings from 5-8. The imaging modalities reported by radiographers in England demonstrated X-ray (n=34), the most reported imaging examination by region, and Nuclear Medicine (n=3) the least, with evidence of clinical reporting for CT (n=20), MRI (n=18), DEXA (n=16), Mammography (n=13) and fluoroscopy (n=12) being completed by radiographers in England. Conclusion: The findings for England (n=704 reporters; n=142 trainees) provide an estimate based on the response rate of the current reporting radiographer workforce across the NHSE regions, and their contribution to the skills mix radiology reporting service delivery. It is hoped future surveys will provide ongoing workforce estimates for the diagnostic radiographer reporting workforce in NHSE to support workforce transformation and sustainability plans for the radiography profession and to meet government healthcare targets and priorities.

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Some conclusions on the geography of historical surnames in Vas County
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  • Gábor Ferenczi

In my study, I examined the material of the National Tax Census of 1720 (Conscriptio Regnicolaris) of Vas County included in the database of the Atlas of Historical Surnames in Hungary (AHSH) from two approaches. On the one hand, by using the method of name analysis, I sought to reveal the distribution by origin on the basis of the contemporary surname etymons according to which the surnames in Vas County are divided into three categories: German, Hungarian and Slavic. The high representation of the two latter name etymon groups is clearly due to the double border region and the resulting increased inter-ethnic relations compared to the inland areas of the language area. The distribution of surname etymons between Kőszeg and the districts further complicates the picture. A greater number of Hungarian surnames are found in the northern (Kőszeg) and inland (Kemenesalja and Árokközi) districts of the county. In the town of Kőszeg, as well as in the district of Szombathely, which lies directly on the western border, the number of people with German surname etymons is dominant, as do the Slavs in the district of Tótság on the south-south-western edge, for understandable reasons. On the other hand, with the help of János N. Fodor's (2010) functional-semantic theoretical framework applied at the research on personal names in the Upper Tisza region, I examined the motivations for naming in the Hungarian-origin surname material of Vas County, by districts and in the case of Kőszeg. The results showed that Hungarian names account for about one third of the total family name stock (33.52%), and 92.61% of these names can be classified into one of the five motivation categories (individual attribute; relationship to people, groups of people; social role, status, situation; relationship to place; relationship to things, circumstances). At both county and district (and in the case of Kőszeg, urban) level, it is clear that the vast majority of all motivational options are distributed between the first four categories. This distribution is relatively even at county level, but is more nuanced at district and Kőszeg level. After this overview, I will briefly present the percentage distribution of ethnonymic surnames at county level and then at district (and Kőszeg) level. Concerning the distribution between the districts (and the city of Kőszeg), the percentage within this category is the highest in the Kőszeg district due to the peripheral location and the consequent greater occurance of interethnic relations. The Kőszeg district is followed by the Szombathely district, which is also peripheral, but lies further south; then by two inland districts, Kemenesalja and Árokköz; and then, interestingly, since it is also a peripheral district, by Tótsági. Finally, this ratio is the lowest in the town of Kőszeg.

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