scholarly journals PrAna: an R package to calculate and visualize England NHS primary care prescribing data

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Kishore Kumar Jagadeesan ◽  
James Grant ◽  
Sue Griffin ◽  
Ruth Barden ◽  
Barbara Kasprzyk-Hordern
Keyword(s):  
Real Time ◽  
National Level ◽  
Open Data ◽  
R Package ◽  
Public Healthcare ◽  
Prescription Data ◽  
Support Tool ◽  
North East ◽  
Long Term Trends

Abstract Background The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage. Design We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England’s national level prescription data provided by National Health Service, for the years 2015–2018. Datasets generated using PrAna can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region. Results PrAnaViz’s targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region. Conclusion PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.

scholarly journals PrAna: An R package to calculate and visualize England NHS primary care prescribing data

2021 ◽  
Author(s):  
Kishore Kumar Jagadeesan ◽  
James Grant ◽  
Sue Griffin ◽  
Ruth Barden ◽  
Barbara Kasprzyk-Hordern
Keyword(s):  
Real Time ◽  
National Level ◽  
Open Data ◽  
R Package ◽  
Public Healthcare ◽  
Prescription Data ◽  
Support Tool ◽  
North East ◽  
Long Term Trends

Abstract Background The objective of this work to calculate prescribed quantity of an active pharmaceutical ingredient (API) in prescription medications for human use, to facilitate research on the prediction of amount of API released to the environment and create an open-data tool to facilitate spatiotemporal and long-term prescription trends for wider usage. Design We have developed an R package, PrAna to calculate the prescribed quantity (in kg) of an APIs by postcode using England’s national level prescription data provided by National Health Service, for the years 2015–2018. Datasets generated using Prana can be visualized in a real-time interactive web-based tool, PrAnaViz to explore spatiotemporal and long-term trends. The visualisations can be customised by selecting month, year, API, and region. Results PrAnaViz’s targeted API approach is demonstrated with the visualisation of prescribed quantities of 14 APIs in the Bath and North East Somerset (BANES) region during 2018. Once the APIs list is loaded, the back end retrieves relevant data and populates the graphs based on user-defined data features in real-time. These plots include the prescribed quantity of APIs over a year, by month, and individual API by month, general practice, postcode, and medicinal form. The non-targeted API approach is demonstrated with the visualisation of clarithromycin prescribed quantities at different postcodes in the BANES region. Conclusion PrAna and PrAnaViz enables the analysis of spatio-temporal and long-term trends with prescribed quantities of different APIs by postcode. This can be used as a support tool for policymakers, academics and researchers in public healthcare, and environmental scientist to monitor different group of pharmaceuticals emitted to the environment and for prospective risk assessment of pharmaceuticals in the environment.

scholarly journals Climate Change and Future Long-Term Trends of Rainfall at North-East of Iraq

2014 ◽  
Vol 8 (6) ◽  
Author(s):  
Nadhir Al-Ansari ◽  
Mawada Abdellatif ◽  
Mohammad Ezeelden ◽  
Salahalddin S. Ali ◽  
Sven Knutsson
Keyword(s):  
Climate Change ◽  
North East ◽  
Long Term Trends

Long Term Trends in the Occurrence of Phaeocystis Sp. in the North-East Atlantic

1989 ◽  
Vol 69 (4) ◽  
pp. 813-821 ◽  
Author(s):  
N.J.P. Owens ◽  
D. Cook ◽  
M. Colebrook ◽  
H. Hunt ◽  
P.C. Reid
Keyword(s):  
North Sea ◽  
Plant Biomass ◽  
Nitrogen And Phosphorus ◽  
Sulphur Compounds ◽  
North East ◽  
The North ◽  
The North Sea ◽  
Long Term Trends ◽  
Flagellate Algae

The effects of nutrient enrichment of natural water bodies range from small increases in plant biomass and production, to gross deterioration of water quality. The input of nutrients (e.g. nitrogen and phosphorus) to the sea off NW Europe (especially the North Sea) has increased dramatically over the last three or four decades (Folkard & Jones, 1974; Bennekom et al., 1975; Postma, 1978; Cadee, 1986a) but there is uncertainty about the effects on the ecosystem. One possible effect might be to induce changes in the phytoplankton community. Such an effect has been reported for the North Sea, where increases in flagellate algae have been observed (Gieskes & Kraay, 1977; Postma, 1985; Cadee, 1986b; Batje & Michaelis, 1986). Phaeocystis is one such alga, and its purported involvement in the formation of large quantities of foam, observed on European beaches (Batje & Michaelis, 1986; Weisse et al, 1986), together with evidence that the alga is a source of atmospheric sulphur compounds (Barnard et al, 1984) (with implications for atmospheric acidity), has attracted particular attention and concern

scholarly journals ANALYZING LONG-TERM AVAILABILITY OF URBAN GREEN SPACE BY SOCIOECONOMIC STATUS IN MEDELLIN, COLOMBIA, USING OPEN DATA AND TOOLS

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 539-544
Author(s):  
J. E. Patiño
Keyword(s):  
Socioeconomic Status ◽  
Green Space ◽  
Open Data ◽  
Well Being ◽  
Green Spaces ◽  
Population Groups ◽  
Urban Green ◽  
Urban Green Spaces ◽  
Long Term Trends

Abstract. The availability of green spaces is an important issue for urban populations worldwide, given the benefits that the green spaces provide for health, well-being, and quality of life. But urban green spaces are not always distributed equally for different population groups within cities. Latin America is the second most urbanized region of the world, but there are few published studies analysing the green space availability for different urban population groups, and less so analysing the long-term trends. This work presents an analysis of long-term availability of urban green spaces by different socioeconomic status population groups in Medellin city, Colombia, using open geospatial data and open software tools. The results indicate that disparities between different groups have been decreasing in the last years, but there are still efforts to do. Showing this kind of analysis based on open data and tools is essential as it opens the possibility for replicating it in other cities with scarce budgets.

scholarly journals Competitiveness of the European Automobile Industry in the Global Context

2017 ◽  
Vol 13 (1) ◽  
pp. 69-86 ◽  
Author(s):  
Milan Vošta ◽  
Aleš Kocourek
Keyword(s):  
Automobile Industry ◽  
Structural Changes ◽  
Action Plan ◽  
National Level ◽  
Global Context ◽  
Eu Member States ◽  
The Usa ◽  
Long Term Trends ◽  
The Eu

Abstract The automobile industry is one of the most rapidly growing industries, a significant employer and investor in research and development, and also one of the most important sectors of the EU economy. Nevertheless, even this sector has gone through a series of structural changes and territorial transfers, recently. Exactly for this reason, it seems crucial to examine the competitiveness of the automobile industry on the national level, analyze the long-term trends throughout the whole EU, and put them in a global context. The article uses standard methods of statistical analysis of indices of revealed symmetrical comparative advantage to detect the trends characterizing the shape and long-term development of the automobile industry in Europe. The authors point out the substantial shift s in production and exports from traditional Western European car makers in favor of the new EU member states, but also from the USA and Canada in favor of new, fast-growing developing countries in the South and Southeast Asia and in Latin America. A brief outline of the European Commission’s response to these changes in the European automobile industry in the form of an Action Plan CARS 2020 can be found in the final part of the article.

Long-term trends in stream chemistry and biology in North-East Scotland: Evidence for recovery

1995 ◽  
Vol 85 (2) ◽  
pp. 689-694 ◽  
Author(s):  
C. Soulsby ◽  
D. Turnbull ◽  
S. J. Langan ◽  
R. Owen ◽  
D. Hirst
Keyword(s):  
Stream Chemistry ◽  
North East ◽  
Long Term Trends

scholarly journals GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia

BMJ Open ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. e018324 ◽  
Author(s):  
Mireia Obón-Santacana ◽  
Mireia Vilardell ◽  
Anna Carreras ◽  
Xavier Duran ◽  
Juan Velasco ◽  
...  
Keyword(s):  
Cohort Study ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
White Blood Cells ◽  
Public Healthcare ◽  
North East ◽  
East Region ◽  
Education Levels

PurposeThe prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north-east region of Spain.ParticipantsAt the end of 2017, the GCAT Study will have recruited 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants will be followed biannually at least 20 years after recruitment.Findings to dateAmong all GCAT participants, 59.2% are women and 83.3% of the cohort identified themselves as Caucasian/white. More than half of the participants have higher education levels, 72.2% are current workers and 42.1% are classified as overweight (body mass index ≥25 and <30 kg/m2). We have genotyped 5459 participants, of which 5000 have metabolome data. Further, the whole genome of 808 participants will be sequenced by the end of 2017.Future plansThe first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites.

scholarly journals Tool for supporting local energy strategies: forecasting energy plans with Artificial Neural Network in Umbria Region

2021 ◽  
Vol 312 ◽  
pp. 02016
Author(s):  
Domenico Palladino ◽  
Iole Nardi
Keyword(s):  
Neural Network ◽  
Energy Efficiency ◽  
Artificial Neural Network ◽  
National Level ◽  
Support Tool ◽  
Umbria Region ◽  
Building Systems ◽  
Artificial Neural ◽  
Forecasting Analysis

In order to reduce the greenhouse gas emission and to improve the energy efficiency of buildings, European Member States have to plan medium-to-long term strategies as reliable as possible. In this context, the present work aims to discuss the potentiality of Artificial Neural Network (ANN) as a support tool for medium-to-long term forecasting analysis of energy efficiency strategies in Umbria Region (central Italy) chosen as case study. Parametric energy simulations of several archetypes buildings were carried out in compliance with the current Italian regulations by changing the form, thermal properties, boundary conditions, and technical building systems. An ANN able to forecast primary energy need was trained to forecast the energy need of building-stock of Umbria Region and to evaluate the effectiveness of several potential energy actions (such as thermal coat or technical building systems replacement) over the years. Results confirm the potential of use of ANN as a support tool in energy forecasting analysis for local Authorities. ANN is capable of forecasting different future scenarios allowing correctly planning energy actions to be implemented as well as their priority. The results open to several scenarios of interest, such as the application of the same approach at national level.

scholarly journals Trends of particulate matter (PM<sub>2.5</sub>) and chemical composition at a regional background site in the Western Mediterranean over the last nine years (2002–2010)

2012 ◽  
Vol 12 (4) ◽  
pp. 10995-11033 ◽  
Author(s):  
M. Cusack ◽  
A. Alastuey ◽  
N. Pérez ◽  
J. Pey ◽  
X. Querol
Keyword(s):  
Particulate Matter ◽  
Chemical Composition ◽  
Saharan Dust ◽  
Sea Spray ◽  
Crustal Material ◽  
North East ◽  
Regional Background ◽  
Long Term Trends ◽  
The Mean

Abstract. The time variability and long term trends of PM2.5 (particulate matter of diameter <2.5 μm) at various regional background (RB) sites across Europe are studied and interpreted in this work. Long-term trends of PM2.5 concentrations are relatively scarce across Europe, with few studies outlining the changes measured in PM2.5 concentrations over a significant period of time. To this end, data on mean annual levels of PM2.5 measured at Montseny (MSY, North East Spain) and various RB sites in Spain and Europe are evaluated and compared, and subsequently analysed for statistically significant trends. The MSY site registered higher average PM2.5 levels than those measured at a selection of other RB sites across Spain, Portugal, Germany and Scandinavia, but lower than those measured in Switzerland, Italy and Austria. Reductions in PM2.5 were observed across all stations in Spain and Europe to varying degrees. MSY underwent a statistically significant reduction since measurements began, indicating a year-on-year gradual decrease (−3.7 μg m−3, calculated from the final year of data compared to the mean). Similar trends were observed in other RB sites across Spain (−1.9 μg m−3). Reductions recorded in PM2.5 across Europe were varied, with many experiencing gradual, year-on-year decreases (−1.8 μg m−3). These reductions have been attributed to various causes: the introduction and implementation of pollution abatement strategies in EU member states, the effect of the current economic crisis on emissions of PM2.5 and the influence of anomalous meteorology observed during the winters of 2009 and 2010. The North Atlantic Oscillation (NAO), a large scale meteorological phenomenon most prevalent during winter, was observed to influence the frequency of Saharan dust intrusions across the Iberian Peninsula. Chemical composition of PM2.5 at MSY is characterised by high levels of organic matter (OM) and sulphate, followed by crustal material, nitrate and ammonia. Sea Spray and finally elemental carbon (EC) comprised a minor part of the total PM2.5 mass. Statistical trend analysis was performed on the various chemical components of PM2.5 recorded at MSY to determine which components were accountable for the decrease in PM2.5 concentration. It is shown that OM underwent the largest decrease over the time period with a statistically significant trend (−1.3 μg m−3 of the mean), followed by sulphate (−0.8 μg m−3), ammonium (−0.5 μg m−3) and nitrate (−0.4 μg m−3). Conversely, sea spray, EC and crustal material reductions were found to be negligible.

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