Limits...
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.

Show MeSH

Related in: MedlinePlus

Crude Morbidity Ratio 2000. It represents Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, all age group, influenza).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2277489&req=5

Figure 4: Crude Morbidity Ratio 2000. It represents Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, all age group, influenza).

Mentions: In the infectious disease mapping process, several mapping variables, including age group, statistical method, and gender need to be considered. However, the standard Web Map Service could not support parameters such as disease type, gender, and statistical method, among others. For the integration of web map services in the disease mapping, we developed a convention to name map layers. As to different combinations of gender, age, geographic level, disease type and statistical method variables, we assign a distinct WMS layer name to each of them through customized encoding rules. The web map service parses the infectious disease mapping parameters from the layer name. As the service is compatible with WMS, thematic disease maps could be accessed by a health portal or any OGC compatible clients. Figure 4 shows the classification map retrieved from a web map service which describes Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, Crude Morbidity Ratio, all age group, influenza). Figure 5 shows the Crude Morbidity Ratio distribution of year 2001 with the same parameters. By comparing different mapping variables at different times and geographical levels, the users can visualize the pattern and movement of the infectious disease.


Online GIS services for mapping and sharing disease information.

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

Crude Morbidity Ratio 2000. It represents Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, all age group, influenza).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Crude Morbidity Ratio 2000. It represents Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, all age group, influenza).
Mentions: In the infectious disease mapping process, several mapping variables, including age group, statistical method, and gender need to be considered. However, the standard Web Map Service could not support parameters such as disease type, gender, and statistical method, among others. For the integration of web map services in the disease mapping, we developed a convention to name map layers. As to different combinations of gender, age, geographic level, disease type and statistical method variables, we assign a distinct WMS layer name to each of them through customized encoding rules. The web map service parses the infectious disease mapping parameters from the layer name. As the service is compatible with WMS, thematic disease maps could be accessed by a health portal or any OGC compatible clients. Figure 4 shows the classification map retrieved from a web map service which describes Crude Morbidity Ratio distribution of all the cells with the parameters (Dissemination Area/Census Block Group level, year 2000, Crude Morbidity Ratio, all age group, influenza). Figure 5 shows the Crude Morbidity Ratio distribution of year 2001 with the same parameters. By comparing different mapping variables at different times and geographical levels, the users can visualize the pattern and movement of the infectious disease.

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