Abstract
To address the priorities of the Public Healths, in particular those set by French’s Cancer Plans, it is necessary to develop spatial tools able to identify environmental risk factors. The emergence of numerous databases provides access to many environmental parameters that describe geographical living environments. However, those ones are only interesting if there are crossed with health indicators. Epidemiological databases contain spatiotemporal references but are not suited to the geographic modeling.
The EstimGRE method provides two morbid spatiotemporal indicators (m.st.i) adapted to the analysis of interactions between health and environment. It also leads to construct a third m.st.i which characterizes spaces with morbid Geographical Risk Exposures (GRE). Therefore, it enables to develop medical solutions and public policies to improve the environmental health of populations, in line with the sustainable development objectives. Propositions are applied to the LEA cohort. The EstimGRE algorithm is the name of the method proposed.
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Bourrelly, S. (2014). Modeling Morbid Geographical Risk Exposure. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8582. Springer, Cham. https://doi.org/10.1007/978-3-319-09147-1_17
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DOI: https://doi.org/10.1007/978-3-319-09147-1_17
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