The Information Systems Technology Centre of ISTI-CNR uses GIS technology for the management of epidemiological and environmental data, mainly about air quality topics. This work uses data from epidemiological surveys based on a standardized interviewer-administered questionnaire referring to respiratory symptoms and diseases, life style and personal habits. This study aims to apply geostatistical methods in order to obtain a respiratory health risk map. A variable representing population respiratory health status was created from information about presence/absence of respiratory symptoms/diseases derived from the epidemiological questionnaire. Exploratory Spatial Data Analysis (ESDA) tools assured a deep understanding of spatial and structural properties of dataset. Inverse Distance Weighted interpolation technique was used to create continuous surfaces from sample points. To assess the resulting map population was classified according to it. Classical statistical analyses were performed. Results show that interpolation gives a good representation of the distribution of symptoms/diseases over land.
Application of geostatistical methods for public health risk mapping
Fresco R;Maio S;Baldacci S;Angino A;Martini F;Borbotti M;Viegi G;Della Maggiore R
2005
Abstract
The Information Systems Technology Centre of ISTI-CNR uses GIS technology for the management of epidemiological and environmental data, mainly about air quality topics. This work uses data from epidemiological surveys based on a standardized interviewer-administered questionnaire referring to respiratory symptoms and diseases, life style and personal habits. This study aims to apply geostatistical methods in order to obtain a respiratory health risk map. A variable representing population respiratory health status was created from information about presence/absence of respiratory symptoms/diseases derived from the epidemiological questionnaire. Exploratory Spatial Data Analysis (ESDA) tools assured a deep understanding of spatial and structural properties of dataset. Inverse Distance Weighted interpolation technique was used to create continuous surfaces from sample points. To assess the resulting map population was classified according to it. Classical statistical analyses were performed. Results show that interpolation gives a good representation of the distribution of symptoms/diseases over land.File | Dimensione | Formato | |
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