Pub Date : 2020-01-01DOI: 10.1515/openhe-2020-0005
E. Osuteye, Braima Koroma, J. Macarthy, Sulaiman Foday Kamara, A. Conteh
Abstract As the COVID-19 pandemic spreads in Africa, attention is increasingly shifting to the potential and ongoing impact on informal settlements, which face considerable challenges around the implementation of conventional control measures of social distancing, hand washing and self-isolation. In Freetown, Sierra Leone, residents of informal settlements have relied on local community organisations and groups, and their resourcefulness to provide essential preparedness, response and on-going support to alleviate the public health and economic risks associated with the effects of the COVID-19 outbreak. This is also premised on lessons drawn from dealing with previous epidemics, notably the Ebola virus disease in 2014–2015. This paper will explain the nature and form of community organisation that can be galvanised and leveraged for COVID-19 preparedness and responses that are suited for informal settlements. Secondly, it highlights the critical contribution of community organisations in social protection measures that tackle deeply entrenched inequalities in rapidly urbanising contexts. Finally, the cases examined seek to provide evidence of the value of processes of continuous learning within community organisation that are essential for both humanitarian assistance and emergency management. Although situated in Freetown, the broad lessons drawn are relevant for urban-poor communities and informal settlements in many urban African centres.
{"title":"Fighting COVID-19 in Freetown, Sierra Leone: the critical role of community organisations in a growing pandemic","authors":"E. Osuteye, Braima Koroma, J. Macarthy, Sulaiman Foday Kamara, A. Conteh","doi":"10.1515/openhe-2020-0005","DOIUrl":"https://doi.org/10.1515/openhe-2020-0005","url":null,"abstract":"Abstract As the COVID-19 pandemic spreads in Africa, attention is increasingly shifting to the potential and ongoing impact on informal settlements, which face considerable challenges around the implementation of conventional control measures of social distancing, hand washing and self-isolation. In Freetown, Sierra Leone, residents of informal settlements have relied on local community organisations and groups, and their resourcefulness to provide essential preparedness, response and on-going support to alleviate the public health and economic risks associated with the effects of the COVID-19 outbreak. This is also premised on lessons drawn from dealing with previous epidemics, notably the Ebola virus disease in 2014–2015. This paper will explain the nature and form of community organisation that can be galvanised and leveraged for COVID-19 preparedness and responses that are suited for informal settlements. Secondly, it highlights the critical contribution of community organisations in social protection measures that tackle deeply entrenched inequalities in rapidly urbanising contexts. Finally, the cases examined seek to provide evidence of the value of processes of continuous learning within community organisation that are essential for both humanitarian assistance and emergency management. Although situated in Freetown, the broad lessons drawn are relevant for urban-poor communities and informal settlements in many urban African centres.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73929096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1515/openhe-2020-0002
W. Hantrakul, Wittaya Wangsomboonsiri, Chutintorn Sriphrapradang
Abstract Objective: We aimed to determine the prevalence of depression and to find factors associated with depression in admitted medical patients. The differences in the pattern of depression between a university hospital (UH) and a regional hospital (RH) were determined as well. Methods: This is a cross-sectional study. The Patient Health Questionnaire-9 (PHQ-9) was administered among hospitalized patients in medical wards. PHQ-9 could not differentiate between the type of depressive disorder that could be from medical conditions, adjustment disorder with depressed mood, major depressive disorder, or dysthymia. Results: A total of 343 patients (191 in UH, 152 in RH group) with age of 52.1 ± 16.9 years were included. Timing of interview was 4.3 ± 1.4 days after admission. The prevalence of depression (PHQ-9 score ≥ 9) was 12% (7.3% in UH vs 17.8% in RH, p < 0.005). According to PHQ-9 scoring, the prevalence of moderate-to-severe depression was 3.8%. Mean PHQ-9 score in RH was significantly higher than in UH (p < 0.001). Multiple baseline characteristics were analyzed by logistic regression and found no factors associated with depression. There was no difference in baseline characteristics of UH patients with depression compared to RH, except for universal health coverage plan. Conclusions: The prevalence of depression was 1 in 10 patients and was found to be more frequent and severe in RH than UH. All patients were at equal risk to develop depression during admission.
{"title":"Depression among patients admitted to medical wards: comparison between a university hospital and regional hospital","authors":"W. Hantrakul, Wittaya Wangsomboonsiri, Chutintorn Sriphrapradang","doi":"10.1515/openhe-2020-0002","DOIUrl":"https://doi.org/10.1515/openhe-2020-0002","url":null,"abstract":"Abstract Objective: We aimed to determine the prevalence of depression and to find factors associated with depression in admitted medical patients. The differences in the pattern of depression between a university hospital (UH) and a regional hospital (RH) were determined as well. Methods: This is a cross-sectional study. The Patient Health Questionnaire-9 (PHQ-9) was administered among hospitalized patients in medical wards. PHQ-9 could not differentiate between the type of depressive disorder that could be from medical conditions, adjustment disorder with depressed mood, major depressive disorder, or dysthymia. Results: A total of 343 patients (191 in UH, 152 in RH group) with age of 52.1 ± 16.9 years were included. Timing of interview was 4.3 ± 1.4 days after admission. The prevalence of depression (PHQ-9 score ≥ 9) was 12% (7.3% in UH vs 17.8% in RH, p < 0.005). According to PHQ-9 scoring, the prevalence of moderate-to-severe depression was 3.8%. Mean PHQ-9 score in RH was significantly higher than in UH (p < 0.001). Multiple baseline characteristics were analyzed by logistic regression and found no factors associated with depression. There was no difference in baseline characteristics of UH patients with depression compared to RH, except for universal health coverage plan. Conclusions: The prevalence of depression was 1 in 10 patients and was found to be more frequent and severe in RH than UH. All patients were at equal risk to develop depression during admission.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81956378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1515/openhe-2020-0004
D. Gope, Aditya Gope, P. C. Gope
Abstract COVID-19 viruses are primarily transmitted between people via respiratory droplets generated from an infected person while coughing, sneezing, exhaling or close contact. Hence, the use of masks are part of prevention and control measures to limit the spread of COVID-19. A comprehensive study on various materials used in masks is required. The filtration efficiency of cotton masks increases with increase in thread count and number of layers, but breathability is affected and therefore a risk for longer durations. Cotton-based masks have filtration efficiency ranging from 5% to 80% depending on the number of layers. Combinations of different hybrid fabric materials and design have an efficiency ranging from 37% to 97%. Bio-cellulose, which is derived from cellulosic biomass by synthesis techniques involving various physical and chemical processes followed by refining techniques, possesses remarkable properties including biodegradability, biocompatibility, low toxicity, etc., making it the most suitable mask material. Masks made of bio-cellulose have an important property of hydrophilicity which makes it adhere to the face tightly, giving a cooling effect to the face. Use of nanocellulose masks can help attaining filtration efficiency up to 99.9980–99.9995% along with other desirable properties. Hence, there is an immediate need to address the issues and challenges of mask materials and work towards the design and development of low cost masks to overcome these shortcomings by the researchers and manufacturers.
{"title":"Mask material: challenges and virucidal properties as an effective solution against coronavirus SARS-CoV-2","authors":"D. Gope, Aditya Gope, P. C. Gope","doi":"10.1515/openhe-2020-0004","DOIUrl":"https://doi.org/10.1515/openhe-2020-0004","url":null,"abstract":"Abstract COVID-19 viruses are primarily transmitted between people via respiratory droplets generated from an infected person while coughing, sneezing, exhaling or close contact. Hence, the use of masks are part of prevention and control measures to limit the spread of COVID-19. A comprehensive study on various materials used in masks is required. The filtration efficiency of cotton masks increases with increase in thread count and number of layers, but breathability is affected and therefore a risk for longer durations. Cotton-based masks have filtration efficiency ranging from 5% to 80% depending on the number of layers. Combinations of different hybrid fabric materials and design have an efficiency ranging from 37% to 97%. Bio-cellulose, which is derived from cellulosic biomass by synthesis techniques involving various physical and chemical processes followed by refining techniques, possesses remarkable properties including biodegradability, biocompatibility, low toxicity, etc., making it the most suitable mask material. Masks made of bio-cellulose have an important property of hydrophilicity which makes it adhere to the face tightly, giving a cooling effect to the face. Use of nanocellulose masks can help attaining filtration efficiency up to 99.9980–99.9995% along with other desirable properties. Hence, there is an immediate need to address the issues and challenges of mask materials and work towards the design and development of low cost masks to overcome these shortcomings by the researchers and manufacturers.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80198338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brian Karl Finch, Audrey Beck, D Brian Burghart, Richard Johnson, David Klinger, Kyla Thomas
Objectives: We evaluated the Fatal Encounters (FE) database as an open-source surveillance system for tracking police-related deaths (PRDs).
Methods: We compared the coverage of FE data to several known government sources of police-related deaths and police homicide data. We also replicated incident selection from a recent review of the National Violent Death Reporting System.
Results: FE collected data on n = 23,578 PRDs from 2000-2017. A pilot study and ongoing data integration suggest greater coverage than extant data sets. Advantages of the FE data include circumstance of death specificity, incident geo-locations, identification of involved police-agencies, and near immediate availability of data. Disadvantages include a high rate of missingness for decedent race/ethnicity, potentially higher rates of missing incidents in older data, and the exclusion of more comprehensive police use-of-force and nonlethal use-of-force data-a critique applicable to all extant data sets.
Conclusions: FE is the largest collection of PRDs in the United States and remains as the most likely source for historical trend comparisons and police-department level analyses of the causes of PRDs.
{"title":"\"Using Crowd-Sourced Data to Explore Police-Related-Deaths in the United States (2000-2017): The Case of Fatal Encounters\".","authors":"Brian Karl Finch, Audrey Beck, D Brian Burghart, Richard Johnson, David Klinger, Kyla Thomas","doi":"10.5334/ohd.30","DOIUrl":"https://doi.org/10.5334/ohd.30","url":null,"abstract":"<p><strong>Objectives: </strong>We evaluated the Fatal Encounters (FE) database as an open-source surveillance system for tracking police-related deaths (PRDs).</p><p><strong>Methods: </strong>We compared the coverage of FE data to several known government sources of police-related deaths and police homicide data. We also replicated incident selection from a recent review of the National Violent Death Reporting System.</p><p><strong>Results: </strong>FE collected data on <i>n = 23,578</i> PRDs from 2000-2017. A pilot study and ongoing data integration suggest greater coverage than extant data sets. Advantages of the FE data include circumstance of death specificity, incident geo-locations, identification of involved police-agencies, and near immediate availability of data. Disadvantages include a high rate of missingness for decedent race/ethnicity, potentially higher rates of missing incidents in older data, and the exclusion of more comprehensive police use-of-force and nonlethal use-of-force data-a critique applicable to all extant data sets.</p><p><strong>Conclusions: </strong>FE is the largest collection of PRDs in the United States and remains as the most likely source for historical trend comparisons and police-department level analyses of the causes of PRDs.</p>","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10109543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9382961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Here we provide seasonal data on the concentrations of total coliform, Escherichia coli and Enterococcus spp. and six opportunistic pathogens (Acanthamoeba spp., Legionella spp., Legionella pneumophila, Mycobacterium avium, Mycobacterium intracellulare, and Pseudomonas aeruginosa) of public health significance in 24 tank water samples over six monthly sampling events from August 2015 to March 2006. Quantitative PCR (qPCR) assays were chosen for the quantification of six opportunistic pathogens and culture-based methods were used for the enumeration of fecal indicators. The data fle has been stored in a publicly available repository. The data on concentrations of opportunistic pathogens in RHRW will provide information for rainwater users regarding potential seasonality of risks. Quantitative data presented in this study can be used to perform quantitative microbial risk assessment (QMRA) of RHRW for various potable and nonpotable uses. Data can be used by health regulators to develop guidelines related to RHRW. Funding statement: This research was undertaken and funded as part of a Fulbright-CSIRO Postgraduate Scholarship sponsored by the CSIRO Land and Water Flagship.
{"title":"Seasonal Abundance of Fecal Indicators and Opportunistic Pathogens in Roof-Harvested Rainwater Tanks","authors":"W. Ahmed, K. Hamilton, S. Toze, C. Haas","doi":"10.5334/OHD.29","DOIUrl":"https://doi.org/10.5334/OHD.29","url":null,"abstract":"Here we provide seasonal data on the concentrations of total coliform, Escherichia coli and Enterococcus spp. and six opportunistic pathogens (Acanthamoeba spp., Legionella spp., Legionella pneumophila, Mycobacterium avium, Mycobacterium intracellulare, and Pseudomonas aeruginosa) of public health significance in 24 tank water samples over six monthly sampling events from August 2015 to March 2006. Quantitative PCR (qPCR) assays were chosen for the quantification of six opportunistic pathogens and culture-based methods were used for the enumeration of fecal indicators. The data fle has been stored in a publicly available repository. The data on concentrations of opportunistic pathogens in RHRW will provide information for rainwater users regarding potential seasonality of risks. Quantitative data presented in this study can be used to perform quantitative microbial risk assessment (QMRA) of RHRW for various potable and nonpotable uses. Data can be used by health regulators to develop guidelines related to RHRW. Funding statement: This research was undertaken and funded as part of a Fulbright-CSIRO Postgraduate Scholarship sponsored by the CSIRO Land and Water Flagship.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41707283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Schaffner, V. Versteirt, W. Bortel, H. Zeller, W. Wint, N. Alexander
This is the first of a number of planned data papers presenting modelled vector distributions, the models in this paper were produced during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. This data paper contains the sand fly model outputs produced as part of the VBORNET project. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models. The data package described here includes those sand fly species first modelled in 2013 and 2014 as part of the VBORNET gap analysis work which aimed to identify areas of potential species distribution in areas lacking records. It comprises four species models together with suitability masks based on land class and environmental limits. The species included within this paper are Phlebotomus ariasi, Phlebotomus papatasi, Phlebotomus perniciosus and Phlebotomus tobbi. The known distributions of these species within the project area (Europe, the Mediterranean Basin, North Africa, and Eurasia) are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a) assistance in targeting surveys to collect distribution data for those areas with no field validated information, and b) a first indication of project wide distributions.
{"title":"VBORNET gap analysis: Mosquito vector distribution models utilised to identify areas of potential species distribution in areas lacking records.","authors":"F. Schaffner, V. Versteirt, W. Bortel, H. Zeller, W. Wint, N. Alexander","doi":"10.5334/OHD.27","DOIUrl":"https://doi.org/10.5334/OHD.27","url":null,"abstract":"This is the first of a number of planned data papers presenting modelled vector distributions, the models in this paper were produced during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. This data paper contains the sand fly model outputs produced as part of the VBORNET project. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models. The data package described here includes those sand fly species first modelled in 2013 and 2014 as part of the VBORNET gap analysis work which aimed to identify areas of potential species distribution in areas lacking records. It comprises four species models together with suitability masks based on land class and environmental limits. The species included within this paper are Phlebotomus ariasi, Phlebotomus papatasi, Phlebotomus perniciosus and Phlebotomus tobbi. The known distributions of these species within the project area (Europe, the Mediterranean Basin, North Africa, and Eurasia) are currently incomplete to a greater or lesser degree. The models are designed to fill the gaps with predicted distributions, to provide a) assistance in targeting surveys to collect distribution data for those areas with no field validated information, and b) a first indication of project wide distributions.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70692214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Orme, D. Esliger, A. Kingsnorth, M. Steiner, Sally J. Singh, D. Malcolm, M. Morgan, L. Sherar
The dataset consists of a densely phenotyped sample of adults collected from March to August 2014. The dataset captures behavioural, physical, physiological and psychosocial characteristics of individuals with and without a General Practitioner diagnosis of chronic obstructive pulmonary disease (COPD). Data were collected at Glenfield Hospital on 436 individuals (139 COPD patients and 297 apparently healthy adults) aged 40–75 years, residing in Leicestershire and Rutland, United Kingdom. The dataset includes seven days of raw wrist-worn accelerometry, venous blood biomarkers, non-invasive point-of-care cardio-metabolic risk profiles, physical measures and questionnaire data.
{"title":"Physical Activity and Respiratory Health (PhARaoH): Data from a Cross-Sectional Study","authors":"M. Orme, D. Esliger, A. Kingsnorth, M. Steiner, Sally J. Singh, D. Malcolm, M. Morgan, L. Sherar","doi":"10.5334/OHD.28","DOIUrl":"https://doi.org/10.5334/OHD.28","url":null,"abstract":"The dataset consists of a densely phenotyped sample of adults collected from March to August 2014. The dataset captures behavioural, physical, physiological and psychosocial characteristics of individuals with and without a General Practitioner diagnosis of chronic obstructive pulmonary disease (COPD). Data were collected at Glenfield Hospital on 436 individuals (139 COPD patients and 297 apparently healthy adults) aged 40–75 years, residing in Leicestershire and Rutland, United Kingdom. The dataset includes seven days of raw wrist-worn accelerometry, venous blood biomarkers, non-invasive point-of-care cardio-metabolic risk profiles, physical measures and questionnaire data.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70692406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This dataset contains the full text transcripts from 15 semi-structured interviews (approximately 44,100 words) conducted during November and December 2014 with participants involved in various aspects of the process of health-related comics production. These participants are authors and publishers and their work is publicly recognised in the comics community. The dataset has been deposited in the Open Health Data Dataverse repository as a zipped folder containing 15 individual simple text files corresponding to each interview and a ReadMe file containing contextual information and other metadata. An initial domain analysis of the interviews was published as Farthing, A., & Priego, E. (2016). ‘Graphic Medicine’ as a Mental Health Information Resource: Insights from Comics Producers. The Comics Grid: Journal of Comics Scholarship, 6(1), 3. DOI: http://doi.org/10.16995/cg.74
本数据集包含2014年11月至12月期间进行的15次半结构化访谈(约44,100字)的全文记录，参与者涉及与健康相关的漫画制作过程的各个方面。这些参与者是作者和出版商，他们的工作在漫画界得到公开认可。数据集以压缩文件夹的形式存储在Open Health Data Dataverse存储库中，其中包含15个单独的简单文本文件，对应于每个访谈和一个包含上下文信息和其他元数据的ReadMe文件。对访谈的初步领域分析发表在Farthing, A.和Priego, E.(2016)上。“图形医学”作为心理健康信息资源:来自漫画制作人的见解。漫画网格:漫画学术杂志，6(1)，3。DOI: http://doi.org/10.16995/cg.74
{"title":"Data from ‘Graphic Medicine’ as a Mental Health Information Resource: Insights from Comics Producers","authors":"A. Farthing, Ernesto Priego","doi":"10.5334/OHD.25","DOIUrl":"https://doi.org/10.5334/OHD.25","url":null,"abstract":"This dataset contains the full text transcripts from 15 semi-structured interviews (approximately 44,100 words) conducted during November and December 2014 with participants involved in various aspects of the process of health-related comics production. These participants are authors and publishers and their work is publicly recognised in the comics community. The dataset has been deposited in the Open Health Data Dataverse repository as a zipped folder containing 15 individual simple text files corresponding to each interview and a ReadMe file containing contextual information and other metadata. An initial domain analysis of the interviews was published as Farthing, A., & Priego, E. (2016). ‘Graphic Medicine’ as a Mental Health Information Resource: Insights from Comics Producers. The Comics Grid: Journal of Comics Scholarship, 6(1), 3. DOI: http://doi.org/10.16995/cg.74","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70691965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Next Steps (formerly known as the Longitudinal Study of Young People in England – LSYPE) is a longitudinal study which follows a sample of around 16,000 people born in 1989/1990. Study members were recruited via schools in England when they were aged 13–14 in 2004. They were interviewed annually for seven waves until they were aged 19/20 in 2010. Co-resident parents were also interviewed in the first four waves of the study.
{"title":"Next Steps (formerly known as the Longitudinal Study of Young People in England)","authors":"L. Calderwood, C. Sanchez","doi":"10.5334/OHD.16","DOIUrl":"https://doi.org/10.5334/OHD.16","url":null,"abstract":"Next Steps (formerly known as the Longitudinal Study of Young People in England – LSYPE) is a longitudinal study which follows a sample of around 16,000 people born in 1989/1990. Study members were recruited via schools in England when they were aged 13–14 in 2004. They were interviewed annually for seven waves until they were aged 19/20 in 2010. Co-resident parents were also interviewed in the first four waves of the study.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70691686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wild boar is a host of a number of arthropod-vectored diseases and its numbers are on the rise in mainland Europe. The species potentially impacts ecosystems, humans and farming practices and so its distribution is of interest to policy makers in a number of fields beyond that of the primarily epidemiological goal of this study. Three statistical model outputs describing the distribution and abundance of the species Sus scrofa (Wild boar) are included in this data package. The extent of this dataset covers continental Europe. These data were presented as a poster [1] at the conference Genes, Ecosystems and Risk of Infection (GERI 2015). The first of the three models provide a European map presenting the probability of presence of Sus scrofa, which can be used to describe the likely geographical distribution of the species. The second and third models provide indices to help describe the likely abundance across the continent. The two indices include “the proportion of suitable habitat where presence is estimated” and a simple classification of boar abundance across Europe using quantiles of existing abundance data and proxies.
{"title":"The European Distribution of Sus Scrofa . Model Outputs from the Project Described within the Poster – Where are All the Boars? An Attempt to Gain a Continental Perspective","authors":"N. Alexander, G. Massei, W. Wint","doi":"10.5334/OHD.24","DOIUrl":"https://doi.org/10.5334/OHD.24","url":null,"abstract":"Wild boar is a host of a number of arthropod-vectored diseases and its numbers are on the rise in mainland Europe. The species potentially impacts ecosystems, humans and farming practices and so its distribution is of interest to policy makers in a number of fields beyond that of the primarily epidemiological goal of this study. Three statistical model outputs describing the distribution and abundance of the species Sus scrofa (Wild boar) are included in this data package. The extent of this dataset covers continental Europe. These data were presented as a poster [1] at the conference Genes, Ecosystems and Risk of Infection (GERI 2015). The first of the three models provide a European map presenting the probability of presence of Sus scrofa, which can be used to describe the likely geographical distribution of the species. The second and third models provide indices to help describe the likely abundance across the continent. The two indices include “the proportion of suitable habitat where presence is estimated” and a simple classification of boar abundance across Europe using quantiles of existing abundance data and proxies.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70691766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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