| Summary: | Disease outbreaks are difficult to detect. Some diseases appear rapidly, while others take time to gestate and become apparent over long time intervals. This research project aims to develop new technology to extend the capabilities of current GIS to improve the early detection and identification of disease outbreaks.The primary data source for outbreak detection in Australia is disease notifications.Whenever a person is diagnosed with a notifiable infectious disease, a record is made into a national surveillance database. This database tracks the number ofpeople and over 60 different diseases, including measles, mumps, HIV/AIDS,influenza, Ross River virus and hepatitis.Disease notifications and GIS provide a key link for analysing disease outbreaks.Working within a GIS framework the authors have integrated spatial/temporal algorithms which aim to detect disease outbreaks before they become widespread.The algorithms have been programmed using R and embedded within a GIS prototype. The prototype has been programmed using MapWindow components.MapWindow is an open-source programmable GIS for creating custom GIS applications.The GIS prototype enables the user to quickly display disease information by postcode. Also, the temporal and spatial algorithms allow the user the ability to scan the 60 different sets of disease notifications and detect abnormalities within these datastreams.
|
|---|