WebGIS Platform for Detecting Spatio-Temporal Hotspots of Oto-Laryngo-Pharyngeal Diseases

Abstract

This paper is a natural prosecution of two previous works. We present a web geospatial framework for analyzing and monitoring the spatio-temporal evolution of disease hotspots. In order to detect the hotspots, we adopt Extended Fuzzy C-Means method which has been adapted for calculating spatial areas with high concentrations of events in a Geographic Information System and tested to study the spatial and temporal evolution of hotspot areas. 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 by using geo-coding services for locating the event. The events can be grouped for time intervals for studying the temporal evolution of the phenomenon. Other services allow the analyst to study the spatio-temporal evolution of the hotspot areas. In our experiments, the data consist of georeferenced patterns corresponding to the residence of patients in the district of Naples (Italy) to whom a surgical intervention to the oto-laryngo-pharyngeal apparatus was carried out between the years 2008 -2012. The results show the presence of two major hotspots for every type of oto-laryngo-pharyngeal disease, the former covering a geographical area that affects the city of Naples, the latter covering various towns around Vesuvius. Both hotspots are significantly increased in recent years.

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“…Finally, EFCM preserves the advantages of the FCM algorithm in terms of linearity and computational complexity with respect to the data input dimension. In the paper by Di Martino et al, [21][22][23][24][25] EFCM is applied to detect hotspots in spatial analysis. The authors show that EFCM DI MARTINO ET AL.…”