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Medical student fitness to practise committees at UK medical schools
2009
BMC Research Notes
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In December 2008, Tim David contacted Jocelyn Aldridge at the Medical Schools Council, to enquire about the arrangement for student fitness to practise cases, and to assist with this enquiry a survey was ...
Methods On 16 December 2008, Jocelyne Aldridge at the Medical Schools Council emailed the named fitness to practise leads of all 31 full members of the Medical Schools Council with a medical undergraduate ...
doi:10.1186/1756-0500-2-97
pmid:19500404
pmcid:PMC2701437
fatcat:dwcnezudynat7lpwoqsmu5uwsa
Control of Signaling in a MAP-kinase Pathway by an RNA-Binding Protein
2007
PLoS ONE
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Citation: Prinz S, Aldridge C, Ramsey SA, Taylor RJ, Galitski T (2007) Control of Signaling in a MAP-kinase Pathway by an RNA-Binding Protein. PLoS ONE 2(2): e249. ...
doi:10.1371/journal.pone.0000249
pmid:17327913
pmcid:PMC1803019
fatcat:4lxqpy4tnnggnndbfdbbw5ebwq
Prioritizing landscapes for grassland bird conservation with hierarchical community models
2021
Landscape Ecology
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We also note that uniform reductions in bare ground and shrub cover could negatively impact shrubland-breeding guilds that we did not consider here (Aldridge et al. 2011; Duchardt et al. 2018 ). ...
doi:10.1007/s10980-021-01211-z
fatcat:bplm7kzewnbk3igozbizjbay4i
A surface water flooding impact library for flood risk assessment
2016
E3S Web of Conferences
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The growing demand for improved risk-based Surface Water Flooding (SWF) warning systems is evident in EU directives and in the UK *RYHUQPHQW ¶s Pitt Review of the 2007 summer floods. This paper presents a novel approach for collating receptor and vulnerability datasets via the concept of an Impact Library, developed by the Health and Safety Laboratory as a depository of pre-calculated impact information on SWF risk for use in a real-time SWF Hazard Impact Model (HIM). This has potential
doi:10.1051/e3sconf/20160718006
fatcat:igmmrdbfz5fjpccel5o7ez57zm
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... for the Flood Forecasting Centre (FFC) as the organisation responsible for the issuing of flood guidance information for England and Wales. The SWF HIM takes a pixel-based approach to link probabilistic surface water runoff IRUHFDVWV SURGXFHG E\ &(+ ¶V *ULG-to-Grid hydrological model with Impact Library information to generate impact assessments. These are combined to estimate flood risk as a combination of impact severity and forecast likelihood, at 1km pixel level, and summarised for counties and local authorities. The SWF HIM takes advantage of recent advances in operational ensemble forecasting of rainfall by the Met Office and of SWF by the Environment Agency and CEH working together through the FFC. Results are presented for a case study event which affected the North East of England during 2012. The work has EHHQ GHYHORSHG WKURXJK WKH 8. ¶V 1DWXUDO +D]DUGV 3DUWQHUVKLS 1+3 D JURXS RI RUJDQLVDWLRQV JDWhered to provide information, research and analysis on natural hazards for civil contingencies, government and responders across the UK.
COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study
[article]
2021
medRxiv
pre-print
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AbstractBackgroundA large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic. However, information on the rate of outbreak occurrences which helps to identify the type of workplaces that are more likely to experience an outbreak, or infection attack rates which estimates the potential extent of the virus transmission in an outbreak, has not yet been available to inform intervention strategies to limit
doi:10.1101/2021.05.06.21256757
fatcat:hs4mnaw3ureihey42a2tddyvpe
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... sTo link datasets on workplace settings and COVID-19 workplace outbreaks in England in order to: identify the geographical areas and workplace sectors with a high rate of outbreaks; and compare infection attack rates by workplace size and sector.MethodsWe analysed Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, covering the time period of 18 May – 12 October 2020. The workplaces analysed excluded care homes, hospitals and educational settings. We calculated the workplace outbreak rates by nine English regions, 151 Upper Tier Local Authorities (UTLAs) and twelve industrial sectors, using National Population Database (NPD) data extracted in May 2019 on the total number of the relevant workplaces as the denominator. We also calculated the infection attack rates by enterprise size (small, medium, large) and industrial sector, using PHE Situations of Interest (SOI) data on the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator, and using NPD data on the number employed in that workplace as the denominator.ResultsIn total, 1,317 confirmed workplace outbreaks were identified from HPZone data, of which 1,305 were available for estimation of outbreak rates. The average outbreak rate was 66 per 100,000 workplaces. Of the nine geographical regions in England, the North West had the highest workplace outbreak rate (155/100,000 workplaces), based on 351 outbreaks. Of the UTLAs, the highest workplace outbreak rate was Blackburn with Darwen (387/100,000 workplaces). The industrial sector with the highest workplace outbreak rate was manufacturers and packers of food (1,672/100,000), based on 117 outbreaks: this was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.In total, 390 outbreaks were identified from SOI data and 264 of them allowed for estimation of attack rates. The overall median attack rate was 3.4% of the employed persons with confirmed COVID-19 at a workplace with an outbreak. Most of these outbreaks (162) had an attack rate less than 6%. However, in a small number of outbreaks (57) the attack rate was over 15%. The attack rates increased as the size of the enterprise decreased. The highest attack rate was for outbreaks in close contact services (median 16.5%), which was followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%).ConclusionsOur linked dataset analysis approach allows early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks as well as estimation of attack rates by enterprise size and sector. This can be used to inform interventions to limit transmission of the virus. Our approach to analysing the workplace outbreak data can also be applied to calculation of outbreak rates and attack rates in other types of settings such as care homes, hospitals and educational settings.
Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales
2017
Ecological Applications
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For instance, if grazing increases forb coverage (Smith et al. 1979 , Evans 1986 , Biondini and Manske 1996 , Manley et al. 1997 , enhanced foraging opportunities for Sage-grouse broods (Evans 1986 , Aldridge ...
doi:10.1002/eap.1512
pmid:28329422
fatcat:evhakhw7w5atpnreketeobqyha
Leveraging 35 years of forest research in the southeastern U.S. to constrain carbon cycle predictions: regional data assimilation using ecosystem experiment
2017
Biogeosciences Discussions
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Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. However, the influence of different
doi:10.5194/bg-2017-46
fatcat:t35ewklvoza6te7t2xinddrcwa
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... tal treatments on those predictions depends on the exact methods and techniques used for data assimilation. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation of Pine Plantation Ecosystem Research, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the Southeastern U.S. to constrain parameters in a modified version of the 3-PG forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO<sub>2</sub>) concentration, water, and nutrients, along with non-experimental studies that spanned environmental gradients across an 8.6&thinsp;&times;&thinsp;10<sup>5</sup>&thinsp;km<sup>2</sup> region. We optimized regionally representative posterior distributions for the most sensitive model parameters, which dependably predicted data from plots withheld from the data assimilation. The posterior distributions of parameters associated with ecosystem responses to CO<sub>2</sub>, precipitation, and nutrient addition, along with the corresponding regional changes in production associated with nutrient fertilization and drought, depended on how the experimental data were assimilated. In particular, assimilating nutrient addition experiments reduced the predicted sensitivity to nutrient fertilization while assimilated water manipulation experiments increased the sensitivity to drought. Further, it was necessary to assimilate data from the CO<sub>2</sub> experimental enrichment site before other studies to constrain the parameters associated with the influence of CO<sub>2</sub> on canopy photosynthesis. The ambient CO<sub>2</sub> plots were numerous and had a large contribution to the cost function compared to the low number of elevated CO<sub>2</sub> plots (289 ambient vs. 5 elevated plots). Overall, we demonstrated how three decades of research in southeastern U.S. planted pine forests can be used to develop data assimilation techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters. This approach allows for future predictions to be consistent with a rich history of ecosystem research across a region.
Mobile-based and open-source case detection and infectious disease outbreak management systems: a review
2020
Wellcome Open Research
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In this paper we perform a rapid review of existing mobile-based, open-source systems for infectious disease outbreak data collection and management. Our inclusion criteria were designed to match the PANDORA-ID-NET consortium's goals for capacity building in sub-Saharan Africa, and to reflect the lessons learned from the 2014–16 West African Ebola outbreak. We found eight candidate systems that satisfy some or most of these criteria, but only one (SORMAS) fulfils all of them. In addition, we
doi:10.12688/wellcomeopenres.15723.1
fatcat:2egq5q7b3bagfnfbxbz6lqdaru
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... line a number of desirable features that are not currently present in most outbreak management systems.
High prevalence of latent tuberculosis and bloodborne virus infection in a homeless population
2018
Thorax
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Table
Aldridge RW, et al. ...
doi:10.1136/thoraxjnl-2016-209579
pmid:29378859
pmcid:PMC5969342
fatcat:xtonu6lka5blxb3hg5f34gbdkm
Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments
2017
Biogeosciences
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<p><strong>Abstract.</strong> Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data
doi:10.5194/bg-14-3525-2017
fatcat:2iqrcpapirg63nqvtsvz3fxwvq
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... on (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO<sub>2</sub>) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6<span class="thinspace"></span> × <span class="thinspace"></span>10<sup>5</sup><span class="thinspace"></span>km<sup>2</sup> region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO<sub>2</sub> enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO<sub>2</sub> strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO<sub>2</sub> study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO<sub>2</sub>, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.</p>
Beyond the closed suture in apert syndrome mouse models: Evidence of primary effects of FGFR2 signaling on facial shape at birth
2010
Developmental Dynamics
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., 2009; Aldridge et al., 2010; Du et al., 2010) . ...
It is clear that tissues other than bone are affected by these two mutations (Wang et al., 2005 Aldridge et al., 2010) . ...
doi:10.1002/dvdy.22414
pmid:20842696
pmcid:PMC2965208
fatcat:tjfcdhpp2bhulcn6rsmmbnfjqi
Beyond the Closed Suture in Apert Syndrome Mouse Models: Evidence of Primary Effects of FGFR2 Signaling on Facial Shape at Birth
2010
Developmental Dynamics
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., 2009; Aldridge et al., 2010; Du et al., 2010) . ...
It is clear that tissues other than bone are affected by these two mutations (Wang et al., 2005 Aldridge et al., 2010) . ...
doi:10.1002/dvdy.22523
fatcat:f3zr6upqhrgspdjjict5prazga
Effectiveness of peer educators on the uptake of mobile X-ray tuberculosis screening at homeless hostels: a cluster randomised controlled trial
2015
BMJ Open
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To cite: Aldridge RW, Hayward AC, Hemming S, et al. Effectiveness of peer educators on the uptake of mobile X-ray tuberculosis screening at homeless hostels: a cluster randomised controlled trial. ...
Aldridge RW, et al. ...
Downloaded from
Aldridge RW, et al. BMJ Open 2015;5:e008050. doi:10.1136/bmjopen-2015-008050 Open Access on 29 April 2019 by guest. ...
doi:10.1136/bmjopen-2015-008050
pmid:26391630
pmcid:PMC4577934
fatcat:stmqqmxefzgyjded6xae5cldpi
Enabling FAIR Research in Earth Science through Research Objects
[article]
2018
arXiv
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Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and resources in a way compliant with the FAIR principles and sustain the development of key infrastructure and tools. This paper provides an account of the challenges, experiences and solutions involved in the adoption of FAIR around research objects over
arXiv:1809.10617v1
fatcat:vixu3kwea5ax5p7deeuymuovee
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... everal Earth Science disciplines. During this journey, our work has been comprehensive, with outcomes including: an extended research object model adapted to the needs of earth scientists; the provisioning of digital object identifiers (DOI) to enable persistent identification and to give due credit to authors; the generation of content-based, semantically rich, research object metadata through natural language processing, enhancing visibility and reuse through recommendation systems and third-party search engines; and various types of checklists that provide a compact representation of research object quality as a key enabler of scientific reuse. All these results have been integrated in ROHub, a platform that provides research object management functionality to a wealth of applications and interfaces across different scientific communities. To monitor and quantify the community uptake of research objects, we have defined indicators and obtained measures via ROHub that are also discussed herein.
Management and control of tuberculosis control in socially complex groups: a research programme including three RCTs
2020
Programme Grants for Applied Research
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This was published in The Lancet 38 and the lead author (RW Aldridge) based a successful Wellcome Trust (London, UK) postdoctoral fellowship application on this approach. ...
Reproduced from Aldridge et al. 74 This is an Open Access article distributed in accordance with the terms of the Creative
Commons Attribution (CC BY 4.0) license, which permits others to distribute, ...
Work arising directly from work packages 1 and 2 (screening for latent tuberculosis and blood-borne viruses) Aldridge Programme Grants for Applied Research 2020 Vol. 8 No. 9 ...
doi:10.3310/pgfar08090
fatcat:h4w2k75nezcszpavml6negnkfy
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