Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain
Identifieur interne : 000705 ( Main/Merge ); précédent : 000704; suivant : 000706Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain
Auteurs : Pau Dominkovics [Espagne] ; Carlos Granell [Espagne] ; Antoni Pérez-Navarro [Espagne] ; Martí Casals [Espagne] ; Àngels Orcau [Espagne] ; Joan A. Caylà [Espagne]Source :
- International Journal of Health Geographics [ 1476-072X ] ; 2011.
Abstract
Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information.
Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database.
The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts.
In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.
Url:
DOI: 10.1186/1476-072X-10-62
PubMed: 22126392
PubMed Central: 3251534
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PMC:3251534Le document en format XML
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Caylà</name><affiliation wicri:level="3"><nlm:aff id="I3">Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona</wicri:regionArea><placeName><settlement type="city">Barcelone</settlement><region nuts="2" type="region">Catalogne</region></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22126392</idno><idno type="pmc">3251534</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3251534</idno><idno type="RBID">PMC:3251534</idno><idno type="doi">10.1186/1476-072X-10-62</idno><date when="2011">2011</date><idno 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type="region">Catalogne</region></placeName></affiliation></author><author><name sortKey="Casals, Marti" sort="Casals, Marti" uniqKey="Casals M" first="Martí" last="Casals">Martí Casals</name><affiliation wicri:level="3"><nlm:aff id="I3">Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona</wicri:regionArea><placeName><settlement type="city">Barcelone</settlement><region nuts="2" type="region">Catalogne</region></placeName></affiliation></author><author><name sortKey="Orcau, Angels" sort="Orcau, Angels" uniqKey="Orcau A" first="Àngels" last="Orcau">Àngels Orcau</name><affiliation wicri:level="3"><nlm:aff id="I3">Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona</wicri:regionArea><placeName><settlement type="city">Barcelone</settlement><region nuts="2" type="region">Catalogne</region></placeName></affiliation></author><author><name sortKey="Cayla, Joan A" sort="Cayla, Joan A" uniqKey="Cayla J" first="Joan A" last="Caylà">Joan A. Caylà</name><affiliation wicri:level="3"><nlm:aff id="I3">Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain</nlm:aff><country xml:lang="fr">Espagne</country><wicri:regionArea>Programa de Prevenció i Control de la Tuberculosi de Barcelona, Servei d'Epidemiologia, Agència de Salut Pública de Barcelona, CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona</wicri:regionArea><placeName><settlement type="city">Barcelone</settlement><region nuts="2" type="region">Catalogne</region></placeName></affiliation></author></analytic><series><title level="j">International Journal of Health Geographics</title><idno type="eISSN">1476-072X</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information.</p></sec><sec><title>Methods</title><p>Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database.</p></sec><sec><title>Results</title><p>The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts.</p></sec><sec><title>Conclusions</title><p>In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Orcau, A" uniqKey="Orcau A">A Orcau</name></author><author><name sortKey="Cayla, Ja" uniqKey="Cayla J">JA Caylà</name></author><author><name sortKey="Martinez, Ja" uniqKey="Martinez J">JA Martínez</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rodrigo, T" uniqKey="Rodrigo T">T Rodrigo</name></author><author><name sortKey="Cayla, Ja" uniqKey="Cayla J">JA Caylà</name></author><author><name sortKey="Gald S Tanguis, H" uniqKey="Gald S Tanguis H">H Galdós-Tangüis</name></author><author><name sortKey="Garcia De Olalla, P" uniqKey="Garcia De Olalla P">P García de Olalla</name></author><author><name 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Zimmerman</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Wood, J" uniqKey="Wood J">J Wood</name></author><author><name sortKey="Dykes, J" uniqKey="Dykes J">J Dykes</name></author><author><name sortKey="Slingsby, A" uniqKey="Slingsby A">A Slingsby</name></author><author><name sortKey="Clarke, K" uniqKey="Clarke K">K Clarke</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kiffer, Crv" uniqKey="Kiffer C">CRV Kiffer</name></author><author><name sortKey="Camargo, Ecg" uniqKey="Camargo E">ECG Camargo</name></author><author><name sortKey="Shimakura, Se" uniqKey="Shimakura S">SE Shimakura</name></author><author><name sortKey="Ribeiro, Pj" uniqKey="Ribeiro P">PJ Ribeiro</name></author><author><name sortKey="Bailey, Tc" uniqKey="Bailey T">TC Bailey</name></author><author><name sortKey="Pignatari, Acc" uniqKey="Pignatari A">ACC Pignatari</name></author><author><name sortKey="Monteiro, Amv" uniqKey="Monteiro A">AMV Monteiro</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Orcau, A" uniqKey="Orcau A">A Orcau</name></author><author><name sortKey="Garcia De Olalla, P" uniqKey="Garcia De Olalla P">P García de Olalla</name></author><author><name sortKey="Cayla, Ja" uniqKey="Cayla J">JA Caylà</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chaix, B" uniqKey="Chaix B">B Chaix</name></author><author><name sortKey="Merlo, J" uniqKey="Merlo J">J Merlo</name></author><author><name sortKey="Evans, D" uniqKey="Evans D">D Evans</name></author><author><name sortKey="Leal, C" uniqKey="Leal C">C Leal</name></author><author><name sortKey="Havard, S" uniqKey="Havard S">S Havard</name></author></analytic></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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