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Review Of Spatio-Temporal Models For Disease Mapping

Authors: Antonio López-Quílez; Facundo Muñoz;

Review Of Spatio-Temporal Models For Disease Mapping

Abstract

The EUROHEIS2 project (http://www.euroheis.org) is aimed at improving the analysis, reporting and dissemination of environmental health information. The project will further develop the health and environment information system for health threat analysis (the Rapid Inquiry Facility -- RIF) initiated in the previously funded EUROHEIS project. One of the specific objectives is to include spatio-temporal methods for disease mapping in the RIF. Statistical techniques for disease mapping have become very popular in public health analysis. These methods enable the smoothing of ecological health indicators accounting for the geographical structure of the units under study. As a consequence, more reliable risk estimates in less populated areas are obtained due to the sharing of information between neighbouring regions, which are assumed to share common risk factors. In this way, it becomes possible to display the geographical distribution of risk even in small areas. But disease risks are variable in space and time, and supporting risk management should ideally incorporate spatio-temporal analysis tools. Recently, several spatio-temporal disease mapping techniques have been proposed. However, the implementation of these methods is not always easy or adequate for a quick response tool. Furthermore, there is not a wide consensus on how to describe temporal and spatial evolution at the same time in a proper way. Therefore, a special effort is necessary to indentify which methods are suitable for inclusion in the RIF.

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Keywords

spatio-temporal, statistical models, disease mapping

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