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International Journal of Health Geographics

, 10:62

First Online: 29 November 2011Received: 04 October 2011Accepted: 29 November 2011DOI: 10.1186-1476-072X-10-62

Cite this article as: Dominkovics, P., Granell, C., Pérez-Navarro, A. et al. Int J Health Geogr 2011 10: 62. doi:10.1186-1476-072X-10-62

Abstract

BackgroundHealth 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.

MethodsData 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.

ResultsThe 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.

ConclusionsIn 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.

List of abbreviationsGiSTGeneralized Search Tree

HIVHuman Immunodeficiency Virus

HTMLHypertext Markup Language

HTTPHypertext Transfer Protocol

JSONJavaScript Object Notation

OGCOpen Geospatial Consortium

RESTRepresentational State Transfer

TBTuberculosis

MDR-TBMultidrug-Resistant Tuberculosis: UTM: Universal Transverse Mercator

URIUniform Resource Identifier

WHOWorld Health Organization

WMSWeb Map Service

XMLExtensible Markup Language.

Electronic supplementary materialThe online version of this article doi:10.1186-1476-072X-10-62 contains supplementary material, which is available to authorized users.

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Autor: Pau Dominkovics - Carlos Granell - Antoni Pérez-Navarro - Martí Casals - Àngels Orcau - Joan A Caylà

Fuente: https://link.springer.com/







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