The mechanisms underlying associations between rodent diversity and the spread of rodent borne diseases are still unclear. The number of potential host species may influence a disease by either spreading the pathogen (or vectors) more rapidly or conversely by reducing contact with other hosts through the effects of dilution. In either case the number of potential hosts may impact on the distribution of a disease or its vectors. Four spatially modelled indices of rodent species richness have been generated to support distribution modelling of rodent borne diseases specifically initially focussing on Hantaviruses and tick borne diseases.
{"title":"Four Rodent and Vole Biodiversity Models for Europe","authors":"W. Wint, D. Morley, N. Alexander","doi":"10.5334/JOPHD.AC","DOIUrl":"https://doi.org/10.5334/JOPHD.AC","url":null,"abstract":"The mechanisms underlying associations between rodent diversity and the spread of rodent borne diseases are still unclear. The number of potential host species may influence a disease by either spreading the pathogen (or vectors) more rapidly or conversely by reducing contact with other hosts through the effects of dilution. In either case the number of potential hosts may impact on the distribution of a disease or its vectors. Four spatially modelled indices of rodent species richness have been generated to support distribution modelling of rodent borne diseases specifically initially focussing on Hantaviruses and tick borne diseases.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70679171","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 data package includes nine population proximity index layers for 2005, 2030 and 2050, for rural, urban and total populations. The layers are distributed as 1km GeoTIFFs and GeoJPGss at 1km. The aim of these layers is to describe the population which may be likely to visit a specific locality where access is determined by Euclidean distance. By using the layers alongside other geographic datasets relating to disease risk it may help identify where people may come into contact with a disease. Human population layers are often used in models to identify risk areas where humans and viruses interact, however most pathogens are not restricted to areas of human habitation: many are found in lesser populated areas such as forests. This dataset will help identify less populated areas that may well still receive high visitor numbers. The layers have been projected to 2030 and 2050 to enable projections of human/disease interfaces in the medium-term which are required to inform policy makers at country and continental level. Urban and rural populations have been separated into individual layers as in some cases it is useful to distinguish between the behaviour and associated risks attributed to the different population segments. There may be a different risk of contacting diseases in rural habitats for rural workers than for than urban visitors.
{"title":"Projected Population Proximity Indices (30km) for 2005, 2030 & 2050","authors":"N. Alexander, W. Wint","doi":"10.5334/JOPHD.AB","DOIUrl":"https://doi.org/10.5334/JOPHD.AB","url":null,"abstract":"This data package includes nine population proximity index layers for 2005, 2030 and 2050, for rural, urban and total populations. The layers are distributed as 1km GeoTIFFs and GeoJPGss at 1km. The aim of these layers is to describe the population which may be likely to visit a specific locality where access is determined by Euclidean distance. By using the layers alongside other geographic datasets relating to disease risk it may help identify where people may come into contact with a disease. Human population layers are often used in models to identify risk areas where humans and viruses interact, however most pathogens are not restricted to areas of human habitation: many are found in lesser populated areas such as forests. This dataset will help identify less populated areas that may well still receive high visitor numbers. The layers have been projected to 2030 and 2050 to enable projections of human/disease interfaces in the medium-term which are required to inform policy makers at country and continental level. Urban and rural populations have been separated into individual layers as in some cases it is useful to distinguish between the behaviour and associated risks attributed to the different population segments. There may be a different risk of contacting diseases in rural habitats for rural workers than for than urban visitors.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70679142","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}
To explore current challenges surrounding the development and application of PROMs/PREMs in paediatric healthcare 1 , a workshop was held for healthcare professionals and parent representatives from University College London (UCL) Institute of Child Health (ICH) and two clinical partners, Great Ormond Street Hospital and Moorfields Eye Hospital. The workshop aimed to establish an academic-clinical-service user collaborative network to support local development and translation into clinical practice of paediatric PROMs/PREMs. The workshop report summarises invited presentations, small group discussions and key local issues. The report is permanently archived at UCL Discovery and publicly available.
{"title":"Data from the Multiprofessional Workshop: ‘Paediatric Patient-Reported Outcome and Experience Measures (PROMS and PREMS) in Routine Clinical Practice.’","authors":"V. Tadić, R. Knowles, J. Rahi","doi":"10.5334/JOPHD.AD","DOIUrl":"https://doi.org/10.5334/JOPHD.AD","url":null,"abstract":"To explore current challenges surrounding the development and application of PROMs/PREMs in paediatric healthcare 1 , a workshop was held for healthcare professionals and parent representatives from University College London (UCL) Institute of Child Health (ICH) and two clinical partners, Great Ormond Street Hospital and Moorfields Eye Hospital. The workshop aimed to establish an academic-clinical-service user collaborative network to support local development and translation into clinical practice of paediatric PROMs/PREMs. The workshop report summarises invited presentations, small group discussions and key local issues. The report is permanently archived at UCL Discovery and publicly available.","PeriodicalId":74349,"journal":{"name":"Open health data","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70679061","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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