We present a web geo-spatial framework for analyzing and continuously monitoring the spatio-temporal evolution of disease hot spots for detecting spatial areas with high concentrations of events in a geographic information system (GIS). To detect the hot spots, we adopt Extended Fuzzy C-Means algorithm. Each event is given by the geo-positional coordinates of the place of residence of the patient. The analyst can insert event data directly on the map or digitizing the address of the residence of the patient and using geo-coding services for locating the event. In our experiments, the data consist of geo-referenced patterns corresponding to the residence of patients in the district of Naples (Italy) submitted to a surgical intervention concerning the oto-laryngo-pharyngeal apparatus between the years 2008 and 2012. The results show the presence of two greatest hot spots: the first covers a geographical area that affects the city of Naples, the second covers parts of various towns around the famous vulcan Vesuvius, respectively.
We present a web geo-spatial framework for analyzing and continuously monitoring the spatio-temporal evolution of disease hot spots for detecting spatial areas with high concentrations of events in a geographic information system (GIS). To detect the hot spots, we adopt Extended Fuzzy C-Means algorithm. Each event is given by the geo-positional coordinates of the place of residence of the patient. The analyst can insert event data directly on the map or digitizing the address of the residence of the patient and using geo-coding services for locating the event. In our experiments, the data consist of geo-referenced patterns corresponding to the residence of patients in the district of Naples (Italy) submitted to a surgical intervention concerning the oto-laryngo-pharyngeal apparatus between the years 2008 and 2012. The results show the presence of two greatest hot spots: the first covers a geographical area that affects the city of Naples, the second covers parts of various towns around the famous vulcan Vesuvius, respectively.
WebGIS based on spatio-temporal hot spots: an application to oto-laryngo-pharyngeal diseases
BARILLARI, Umberto E.S.;Barillari, M. R.
2016
Abstract
We present a web geo-spatial framework for analyzing and continuously monitoring the spatio-temporal evolution of disease hot spots for detecting spatial areas with high concentrations of events in a geographic information system (GIS). To detect the hot spots, we adopt Extended Fuzzy C-Means algorithm. Each event is given by the geo-positional coordinates of the place of residence of the patient. The analyst can insert event data directly on the map or digitizing the address of the residence of the patient and using geo-coding services for locating the event. In our experiments, the data consist of geo-referenced patterns corresponding to the residence of patients in the district of Naples (Italy) submitted to a surgical intervention concerning the oto-laryngo-pharyngeal apparatus between the years 2008 and 2012. The results show the presence of two greatest hot spots: the first covers a geographical area that affects the city of Naples, the second covers parts of various towns around the famous vulcan Vesuvius, respectively.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
