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Online GIS services for mapping and sharing disease information.

Gao S, Mioc D, Anton F, Yi X, Coleman DJ - Int J Health Geogr (2008)

Bottom Line: Disease phenomena are strongly associated with spatial and temporal factors.These challenges cause barriers in extensively sharing health data and restrain the effectiveness in understanding and responding to disease outbreaks.We have shown that the development of standard health services and spatial data infrastructure can enhance the efficiency and effectiveness of public health surveillance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Geodesy and Geomatics Engineering, University of New Brunswick, Canada. sheng.gao@unb.ca

ABSTRACT

Background: Disease data sharing is important for the collaborative preparation, response, and recovery stages of disease control. Disease phenomena are strongly associated with spatial and temporal factors. Web-based Geographical Information Systems provide a real-time and dynamic way to represent disease information on maps. However, data heterogeneities, integration, interoperability, and cartographical representation are still major challenges in the health geographic fields. These challenges cause barriers in extensively sharing health data and restrain the effectiveness in understanding and responding to disease outbreaks. To overcome these challenges in disease data mapping and sharing, the senior authors have designed an interoperable service oriented architecture based on Open Geospatial Consortium specifications to share the spatio-temporal disease information.

Results: A case study of infectious disease mapping across New Brunswick (Canada) and Maine (USA) was carried out to evaluate the proposed architecture, which uses standard Web Map Service, Styled Layer Descriptor and Web Map Context specifications. The case study shows the effectiveness of an infectious disease surveillance system and enables cross-border visualization, analysis, and sharing of infectious disease information through interactive maps and/or animation in collaboration with multiple partners via a distributed network. It enables data sharing and users' collaboration in an open and interactive manner.

Conclusion: In this project, we develop a service oriented architecture for online disease mapping that is distributed, loosely coupled, and interoperable. An implementation of this architecture has been applied to the New Brunswick and Maine infectious disease studies. We have shown that the development of standard health services and spatial data infrastructure can enhance the efficiency and effectiveness of public health surveillance.

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Spatio-temporal data model for disease data. This data model is an object-oriented model and used for the data integration.
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Figure 2: Spatio-temporal data model for disease data. This data model is an object-oriented model and used for the data integration.

Mentions: The spatio-temporal object-oriented data model can provide a uniform way to manage spatio-temporal data and support better data management and analysis. The spatio-temporal object-oriented data model used in this study is shown in Figure 2. The Disease class, which describes the disease characteristics, could be extended to its subcategories of disease such as Infectious disease and Respiratory disease. By comparision, a Disease event is a spatio-temporal object that relates to certain kind of disease. It is the activity that associates with a certain kind of disease, such as a hospital observation, training and education service to patients. It includes the patient and the time information. Time could be an instant or interval. Patient is related to the disease case location. Location could be administrative area or geo-coding point. Administrative area could be national level, provincial level, county level, etc.


Online GIS services for mapping and sharing disease information.

Gao S, Mioc D, Anton F, Yi X, Coleman DJ - Int J Health Geogr (2008)

Spatio-temporal data model for disease data. This data model is an object-oriented model and used for the data integration.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2277489&req=5

Figure 2: Spatio-temporal data model for disease data. This data model is an object-oriented model and used for the data integration.
Mentions: The spatio-temporal object-oriented data model can provide a uniform way to manage spatio-temporal data and support better data management and analysis. The spatio-temporal object-oriented data model used in this study is shown in Figure 2. The Disease class, which describes the disease characteristics, could be extended to its subcategories of disease such as Infectious disease and Respiratory disease. By comparision, a Disease event is a spatio-temporal object that relates to certain kind of disease. It is the activity that associates with a certain kind of disease, such as a hospital observation, training and education service to patients. It includes the patient and the time information. Time could be an instant or interval. Patient is related to the disease case location. Location could be administrative area or geo-coding point. Administrative area could be national level, provincial level, county level, etc.

Bottom Line: Disease phenomena are strongly associated with spatial and temporal factors.These challenges cause barriers in extensively sharing health data and restrain the effectiveness in understanding and responding to disease outbreaks.We have shown that the development of standard health services and spatial data infrastructure can enhance the efficiency and effectiveness of public health surveillance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Geodesy and Geomatics Engineering, University of New Brunswick, Canada. sheng.gao@unb.ca

ABSTRACT

Background: Disease data sharing is important for the collaborative preparation, response, and recovery stages of disease control. Disease phenomena are strongly associated with spatial and temporal factors. Web-based Geographical Information Systems provide a real-time and dynamic way to represent disease information on maps. However, data heterogeneities, integration, interoperability, and cartographical representation are still major challenges in the health geographic fields. These challenges cause barriers in extensively sharing health data and restrain the effectiveness in understanding and responding to disease outbreaks. To overcome these challenges in disease data mapping and sharing, the senior authors have designed an interoperable service oriented architecture based on Open Geospatial Consortium specifications to share the spatio-temporal disease information.

Results: A case study of infectious disease mapping across New Brunswick (Canada) and Maine (USA) was carried out to evaluate the proposed architecture, which uses standard Web Map Service, Styled Layer Descriptor and Web Map Context specifications. The case study shows the effectiveness of an infectious disease surveillance system and enables cross-border visualization, analysis, and sharing of infectious disease information through interactive maps and/or animation in collaboration with multiple partners via a distributed network. It enables data sharing and users' collaboration in an open and interactive manner.

Conclusion: In this project, we develop a service oriented architecture for online disease mapping that is distributed, loosely coupled, and interoperable. An implementation of this architecture has been applied to the New Brunswick and Maine infectious disease studies. We have shown that the development of standard health services and spatial data infrastructure can enhance the efficiency and effectiveness of public health surveillance.

Show MeSH
Related in: MedlinePlus