GISdevelopment.net --> Application --> Health
Deepananthan D., Renold Raj D., GuruPrasad, Manikandan I., Praveen Kartha
Student, (B.E. Geoinformatics)
Anna University, Chennai, India
deepuceg@gmail.com
Public Health Mapping using Oracle Spatial
Deepananthan D., Renold Raj D., GuruPrasad, Manikandan I., Praveen Kartha
Student, (B.E. Geoinformatics)
Anna University, Chennai, India
deepuceg@gmail.com
Abstract:
Imbalance in the distribution of human resources for health, eventually leading to inequities in health services delivery and population health outcomes, is an issue of social and political concern in many countries. Public Health Mapping is one of the best options for making better analysis of Health services especially in case of developing countries such as India to overcome this problem. Thus in order to properly plan, manage and monitor any public health programme, it is vital that up-to-date, relevant information is available to decision-makers at all levels of the public health system.
This must be done with best available data and taking into consideration of demographics, availability of and accessibility to existing health and social services as well as other geographic and environmental features.GIS technology (Oracle Spatial) provides ideal platforms for the convergence of disease specific information and their analyses in relation to population settlements, surrounding social and health services and the natural environment.
Public Health Mapping is basically a thematic mapping process, which can be done by a specific method that is commonly, used such as Choropleth mapping. It can be created by shading a bounded area with a color corresponding to a particular value that is associated with it.
The technology used for this mapping is Oracle spatial that is advantageous over other soft wares currently available in market, which uses SDO_GEOMETRY objects for fast retrieval of data and can be accessed by open source soft wares. Based on this study the Public Health map for districts of Tamil Nadu is created.
Background:
Geographic information systems and remote sensing have capabilities that are ideally suited for use in infectious disease surveillance and control, particularly for the many vector-borne neglected diseases that are often found in poor populations in remote rural areas. They are also highly relevant to meet the demands of outbreak investigation and response, where prompt location of cases, rapid communication of information, and quick mapping of the epidemic’s dynamics are vital.
However, until recently, the use of these tools in public health were largely limited in use due to two major problems: the prohibitive cost of hardware and the great complexity of GIS software that made it extremely time-consuming as well as costly to extract information relevant to the practical demands of disease prevention and control. The situation has changed dramatically over the past few years. Hardware prices have plummeted, simple new devices are now available, and a new generation of civilian satellites is in orbit, circling the world.
The Public Health Mapping, has been developed with the goal of providing greater access to simple, low-cost geographic information and related data management and mapping systems to public health administrators at all levels of the health system.
Oracle Spatial:
Oracle Spatial is part of the Enterprise Edition of Oracle Database 10g. It is a foundation for the deployment of enterprise-wide spatial information systems, and Web-based and wireless location-based applications requiring complex spatial data management. It provides a rich set of natively supported open standard data types and models, as well as a coherent and high performant SQL interface for accessing and managing such data.
In the 10g version, Oracle Spatial natively supports the following data types and models:
Vector data: All OGC simple feature geometry types and essential operators on them, including relate and aggregation. Supported since version 8.1.6, this object relational vector data model has been greatly enhanced in many aspects, including support for spatial reference/coordinate systems and linear referencing system.
Topology and Network data models: Oracle Spatial 10g natively supports topology and network data models. For example, it can manage the node/edge/face information of a topology geometry layer, and also provides a comprehensive set of functions to operate on the topology data. Based on the topology data model, Oracle Spatial also implements a network data model which manages such logical information as connectivity relationships among nodes and links, directions of links, and costs of nodes and links. Many network applications from biochemical areas to transportations can already be developed based on such information and built-in network algorithms in Spatial.
GeoRaster: Oracle Spatial 10g lets you store, index, query, analyze, and deliver georaster data, that is, raster image data and its associated Spatial vector geometry data, plus metadata. GeoRaster provides Oracle Spatial data types and an objectrelational schema for storing multidimensional grid layers and digital images that can be referenced to positions on the Earth's surface or a local coordinate system.
Another significant new capability added to Spatial 10g is the Spatial analysis and mining (SAM) package. With the SAM functions, user can effectively use the general purpose Oracle Data Mining engine while taking into account the characteristics of spatial data, such as spatial auto-correlation. SAM currently supports such functions as spatial binning, proximity and co-location analysis, as well as spatial clustering.
The fact that these spatial data types and functions are provided in the context of a general purpose database that also supports other rich data types (including multimedia and XML) and a vast array of management and analysis functions can never be over emphasized. It is the convergence of such diverse array of data types, data models and processing functions in a single environment that makes many types of complex applications possible. It also means that spatial applications built on top of Oracle Spatial can benefit directly from the scalability and high performance characteristics and mechanisms of Oracle database. Oracle Spatial 10g also comes with a new set of Java spatial access APIs, which you can use to customize or extend the functionalities already provided by Oracle Spatial.
or example, generating Thiessen polygons (or Voroni diagram) is not an existing function of Oracle Spatial. However, if you are proficient with Java, it is quite easy to write your own function that implements the Voroni diagram generation algorithm. The function’s input can be as simple as a query that selects a set of points from an existing table in the database. Basically, your function first executes the query using the server-side JDBC driver and then uses the Java spatial API to access the selected spatial objects (points in this case), before actually generating the Thiessen polygons. Once you have finished coding and debugging your function outside the database, you can then load it into the database server as a stored function, which can be invoked from any tool that can issue SQL commands to the database by other users. You can also code the function so that it writes the generated polygons into a new table, which can then be visualized by a wide range of tools, including MapViewer.
It is also worth noting that the Oracle Spatial vector data model is widely supported by GIS vendors’ software; support for the new data types and models in 10g has also been pledged by most leading GIS vendors and spatial/LBS software developers. The openness of Spatial’s data types and models is making it a de facto industry standard.
Oracle Application Server MapViewer:
MapViewer is a programmable tool for visualizing spatial data managed by Oracle Spatial. It is basically a Java servlet that runs inside a J2EE (Java Enterprise Edition) container, in this case Oracle’s Application Server. Once up and running, it acts as a map server that awaits user’s map request through HTTP, and sends back a map response after processing and generating a map. The maps generated by MapViewer are highly customizable, with all the mapping metadata such as map symbols and styling rules stored in the database and managed through a graphical user interface. MapViewer works directly with Oracle Spatial through Java JDBC.
MapViewer also supports thematic mapping where styles can be dynamically created based on the result of knowledge discovery queries. For example, you may run a Oracle Discoverer report on a large volume sales data table, and based on the aggregated sales numbers range, dynamically create a color-series style to plot each sales region in a certain color based on its associated sales number.
The map request and response are always encoded in XML. This makes it very versatilein that any computer language that can send data through HTTP is able to issue maprequests to MapViewer.
Fig1. Map Viewer Architecture
Thematic Map:
Thematic Maps show the spatial distribution of a wide variety of qualitative and quantitative information. In fact, almost any subject that can be expressed as a geographical distribution can be mapped.
Thematic maps serve three primary purposes. First, they provide specific information about particular locations. Second, they provide general information about spatial patterns. Third, they can be used to compare patterns on two or more maps.
Choropleth Mapping:
The most commonly used method of thematic mapping. Choropleth maps are particularly suited for charting phenomena that are evenly distributed within each enumeration unit (set area).
Public Health Mapper:
The Public HealthMapper is a user-friendly data management and mapping system customized specifically for public health users developed in Oracle Spatial. Public Health Mapping is basically a thematic mapping process (Choropleth mapping).
One of the main objectives of this paper is to develop spatial and non-spatial data, to identify low and high-risk, assist planning and implementation of control measures and monitor and evaluation of control measures. Health administrators, professionals and researchers need training and user support in GIS technology, data and epidemiological methods in order to use GIS properly and effectively.
The system facilitates data standardization, updating of data on epidemiology and provides immediate visualization of data in the form of maps, tables and charts. This also facilitates the easier way of selecting the areas in which a particular disease is prevalent by making simple queries. Thus it helps the public and government officials to take preventive measures and to develop methods to enhance those areas affected.
The following Picture shows the thematic map of Filarial endemic districts of TamilNadu.( Fig2).
Fig2. TamilNadu Districts Map showing the endemic areas of Filariasis.
The following Picture shows the thematic map of Malaria endemic districts of TamilNadu. (Fig3).
Fig3. TamilNadu Districts Map showing the endemic areas of Malaria
The following Picture shows the thematic map of population data of districts of TamilNadu along with the percentage of diseases prevalent in respective districts. (Fig4)
Fig4. TamilNadu Population Map along with disease prevalence
Oracle Spatial – Advantages
Imbalance in the distribution of human resources for health, eventually leading to inequities in health services delivery and population health outcomes, is an issue of social and political concern in many countries. Public Health Mapping is one of the best options for making better analysis of Health services especially in case of developing countries such as India to overcome this problem. Thus in order to properly plan, manage and monitor any public health programme, it is vital that up-to-date, relevant information is available to decision-makers at all levels of the public health system.
This must be done with best available data and taking into consideration of demographics, availability of and accessibility to existing health and social services as well as other geographic and environmental features.GIS technology (Oracle Spatial) provides ideal platforms for the convergence of disease specific information and their analyses in relation to population settlements, surrounding social and health services and the natural environment.
Public Health Mapping is basically a thematic mapping process, which can be done by a specific method that is commonly, used such as Choropleth mapping. It can be created by shading a bounded area with a color corresponding to a particular value that is associated with it.
The technology used for this mapping is Oracle spatial that is advantageous over other soft wares currently available in market, which uses SDO_GEOMETRY objects for fast retrieval of data and can be accessed by open source soft wares. Based on this study the Public Health map for districts of Tamil Nadu is created.
Background:
Geographic information systems and remote sensing have capabilities that are ideally suited for use in infectious disease surveillance and control, particularly for the many vector-borne neglected diseases that are often found in poor populations in remote rural areas. They are also highly relevant to meet the demands of outbreak investigation and response, where prompt location of cases, rapid communication of information, and quick mapping of the epidemic’s dynamics are vital.
However, until recently, the use of these tools in public health were largely limited in use due to two major problems: the prohibitive cost of hardware and the great complexity of GIS software that made it extremely time-consuming as well as costly to extract information relevant to the practical demands of disease prevention and control. The situation has changed dramatically over the past few years. Hardware prices have plummeted, simple new devices are now available, and a new generation of civilian satellites is in orbit, circling the world.
The Public Health Mapping, has been developed with the goal of providing greater access to simple, low-cost geographic information and related data management and mapping systems to public health administrators at all levels of the health system.
Oracle Spatial:
Oracle Spatial is part of the Enterprise Edition of Oracle Database 10g. It is a foundation for the deployment of enterprise-wide spatial information systems, and Web-based and wireless location-based applications requiring complex spatial data management. It provides a rich set of natively supported open standard data types and models, as well as a coherent and high performant SQL interface for accessing and managing such data.
In the 10g version, Oracle Spatial natively supports the following data types and models:
Vector data: All OGC simple feature geometry types and essential operators on them, including relate and aggregation. Supported since version 8.1.6, this object relational vector data model has been greatly enhanced in many aspects, including support for spatial reference/coordinate systems and linear referencing system.
Topology and Network data models: Oracle Spatial 10g natively supports topology and network data models. For example, it can manage the node/edge/face information of a topology geometry layer, and also provides a comprehensive set of functions to operate on the topology data. Based on the topology data model, Oracle Spatial also implements a network data model which manages such logical information as connectivity relationships among nodes and links, directions of links, and costs of nodes and links. Many network applications from biochemical areas to transportations can already be developed based on such information and built-in network algorithms in Spatial.
GeoRaster: Oracle Spatial 10g lets you store, index, query, analyze, and deliver georaster data, that is, raster image data and its associated Spatial vector geometry data, plus metadata. GeoRaster provides Oracle Spatial data types and an objectrelational schema for storing multidimensional grid layers and digital images that can be referenced to positions on the Earth's surface or a local coordinate system.
Another significant new capability added to Spatial 10g is the Spatial analysis and mining (SAM) package. With the SAM functions, user can effectively use the general purpose Oracle Data Mining engine while taking into account the characteristics of spatial data, such as spatial auto-correlation. SAM currently supports such functions as spatial binning, proximity and co-location analysis, as well as spatial clustering.
The fact that these spatial data types and functions are provided in the context of a general purpose database that also supports other rich data types (including multimedia and XML) and a vast array of management and analysis functions can never be over emphasized. It is the convergence of such diverse array of data types, data models and processing functions in a single environment that makes many types of complex applications possible. It also means that spatial applications built on top of Oracle Spatial can benefit directly from the scalability and high performance characteristics and mechanisms of Oracle database. Oracle Spatial 10g also comes with a new set of Java spatial access APIs, which you can use to customize or extend the functionalities already provided by Oracle Spatial.
or example, generating Thiessen polygons (or Voroni diagram) is not an existing function of Oracle Spatial. However, if you are proficient with Java, it is quite easy to write your own function that implements the Voroni diagram generation algorithm. The function’s input can be as simple as a query that selects a set of points from an existing table in the database. Basically, your function first executes the query using the server-side JDBC driver and then uses the Java spatial API to access the selected spatial objects (points in this case), before actually generating the Thiessen polygons. Once you have finished coding and debugging your function outside the database, you can then load it into the database server as a stored function, which can be invoked from any tool that can issue SQL commands to the database by other users. You can also code the function so that it writes the generated polygons into a new table, which can then be visualized by a wide range of tools, including MapViewer.
It is also worth noting that the Oracle Spatial vector data model is widely supported by GIS vendors’ software; support for the new data types and models in 10g has also been pledged by most leading GIS vendors and spatial/LBS software developers. The openness of Spatial’s data types and models is making it a de facto industry standard.
Oracle Application Server MapViewer:
MapViewer is a programmable tool for visualizing spatial data managed by Oracle Spatial. It is basically a Java servlet that runs inside a J2EE (Java Enterprise Edition) container, in this case Oracle’s Application Server. Once up and running, it acts as a map server that awaits user’s map request through HTTP, and sends back a map response after processing and generating a map. The maps generated by MapViewer are highly customizable, with all the mapping metadata such as map symbols and styling rules stored in the database and managed through a graphical user interface. MapViewer works directly with Oracle Spatial through Java JDBC.
MapViewer also supports thematic mapping where styles can be dynamically created based on the result of knowledge discovery queries. For example, you may run a Oracle Discoverer report on a large volume sales data table, and based on the aggregated sales numbers range, dynamically create a color-series style to plot each sales region in a certain color based on its associated sales number.
The map request and response are always encoded in XML. This makes it very versatilein that any computer language that can send data through HTTP is able to issue maprequests to MapViewer.
Fig1. Map Viewer Architecture
Thematic Map:
Thematic Maps show the spatial distribution of a wide variety of qualitative and quantitative information. In fact, almost any subject that can be expressed as a geographical distribution can be mapped.
Thematic maps serve three primary purposes. First, they provide specific information about particular locations. Second, they provide general information about spatial patterns. Third, they can be used to compare patterns on two or more maps.
Choropleth Mapping:
The most commonly used method of thematic mapping. Choropleth maps are particularly suited for charting phenomena that are evenly distributed within each enumeration unit (set area).
Public Health Mapper:
The Public HealthMapper is a user-friendly data management and mapping system customized specifically for public health users developed in Oracle Spatial. Public Health Mapping is basically a thematic mapping process (Choropleth mapping).
One of the main objectives of this paper is to develop spatial and non-spatial data, to identify low and high-risk, assist planning and implementation of control measures and monitor and evaluation of control measures. Health administrators, professionals and researchers need training and user support in GIS technology, data and epidemiological methods in order to use GIS properly and effectively.
The system facilitates data standardization, updating of data on epidemiology and provides immediate visualization of data in the form of maps, tables and charts. This also facilitates the easier way of selecting the areas in which a particular disease is prevalent by making simple queries. Thus it helps the public and government officials to take preventive measures and to develop methods to enhance those areas affected.
The following Picture shows the thematic map of Filarial endemic districts of TamilNadu.( Fig2).
Fig2. TamilNadu Districts Map showing the endemic areas of Filariasis.
The following Picture shows the thematic map of Malaria endemic districts of TamilNadu. (Fig3).
Fig3. TamilNadu Districts Map showing the endemic areas of Malaria
The following Picture shows the thematic map of population data of districts of TamilNadu along with the percentage of diseases prevalent in respective districts. (Fig4)
Fig4. TamilNadu Population Map along with disease prevalence
Oracle Spatial – Advantages
- Store & manage all data in a 'standard‘ way
- Integral part of oracle rdbms - not an additional package or middleware.
- ?Enterprise grade, multi user, scalable, robust, secure
- ?Mature, reliable product with a wealth of functionality.
- ?Open standards based (OGC).
- ?Imposes very few data modeling restrictions compared to other GIS.
- ?Access to the full Oracle technology stack.
- Cost effective - not expensive.
- Oracle Locator and Spatial can add real value to our applications
- It’s easier than people think – if you are an Oracle DBA and developer you can easily be a spatial DBA and developer
- Many tools exist to help rapidly deliver spatially enabled applications
- It’s an ever-growing trend!
- Mapdata: http://www.tnhealth.org/
- http://www.who.int/
- Oracle Spatial : http://otn.oracle.com/products/spatial/index.html
- MapViewer: http://otn.oracle.com/products/mapviewer/index.html
- General Oracle technical resources: http://otn.oracle.com/