To reduce and guard against health risks of environmental origin requires easy and rapid access to high quality statistics which must be analyzed in a useful manner to support decisions and interventions. In this aim and to attain their management objectives, several public health organizations wish to acquire a Geographic Information Systems (GIS) application.
In spite of this recent coordination of medicine, environment, and geomatics is of major importance, it remains that the sole use of a GIS is only at first step. It is widely acknowledged that traditional GIS are limited in multi-scale analysis (e.g. local vs. regional), spatial statistics, handling temporal indices (historical and predictive) as they were not conceived initially for such operations. Such functions require considerable statistical manipulation and development of complex programming with a GIS. Thus, it is currently impossible for a non specialist in GIS to rapidly and easily analyze nor navigate through environmental health data, especially when such usage requires the comprehension of a phenomenon’s development over a given period and to compare several themes of great complexity.
This project focuses on maximal exploitation of the Data Marts, OLAP and Data Mining tools in conjunction with GIS, will facilitate temporal and multi-level treatment of spatial statistics thanks to the multidimensional data base approach used in Data Marts. It will also allow rapid and simple data processing assisted by a SOLAP-type (Spatial OLAP) cartographic interface. Results obtained will lead to a solution closer to the desired one; that is, to have an efficient information system for the description and analysis of complex environmental health data. Finally, to make this tool available to several users located in various regions, at a reasonable cost, the use of an Intranet as a developmental support will be favoured.
This applied research project includes the development of new knowledge introduced by the participation of the University of McMaster team that will permit access to high tech expertise and to Ontario data bases on atmospheric pollution, morbidity, and medicine usages related to asthma and other respiratory diseases, as well as expertise concerning environmental health indicators.
The focus of this paper is to describe (1) the problematic concerns of this project and our research objectives, (2) the means used to reach in terms of human resources coming from three universities, the technologies applied, and the data collected from various different sources, (3) the research method proposed and (4) a simulation of results expected.