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  • 标题:simSALUD: A Web-based Spatial Microsimulation to Model the Health Status for Small Areas Using the Example of Smokers in Austria
  • 本地全文:下载
  • 作者:Bernhard KOSAR ; Melanie TOMINTZ
  • 期刊名称:GI_FORUM - Journal for Geographic Information Science
  • 电子版ISSN:2308-1708
  • 出版年度:2014
  • 页码:207-216
  • DOI:10.1553/giscience2014s207
  • 出版社:ÖAW Verlag, Wien
  • 摘要:The Austrian Federal Ministry of Health aims to improve the health of all people living inAustria and to decrease social inequalities in health and other areas. This leads to carefulplanning and distribution of the available health care resources to meet the targets of thegovernment. Health related data mainly exists at federal state level, which provides aninteresting overview of the current health situation, but for regional planning authorities,this data is often insufficient as they can hide pockets of high and low health prevalence incertain municipalities. The research project SALUD (SpatiAL microsimUlation forDecision support), funded by the Federal Ministry for Transport, Innovation andTechnology, and the Austrian Science Fund, focuses on building a spatial microsimulationmodel for Austria. This paper presents the use-case of a spatial analysis of estimatedsmokers for municipalities in the year 2011. This is done by combining survey and censusdata to model, in particular, the health issues of small areas (e.g. municipalities, districts)based on individuals or households where no data exists, so called missing data. Within thisproject, a first framework of simSALUD (www.simsalud.org/simsalud) is developed, whichis a web-based spatial microsimulation application (designed as wizard) for health decisionsupport, as there is currently no flexible and freely-available web mapping framework inthe area of spatial microsimulation. The application is designed for experts as well as fornon-experts to simulate their own data that can be visualized afterwards without anyprogramming skills. The results will be valuable in supporting policy decision makers byindicating where spatial health inequalities exist, so that they can distribute their resourcesmore efficiently and thus reduce health inequalities.
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