@article{ghenassia_generic_2017,
	title = {A generic method for improving the spatial interoperability of medical and ecological databases},
	volume = {16},
	issn = {1476-072X},
	url = {https://doi.org/10.1186/s12942-017-0109-5},
	doi = {10.1186/s12942-017-0109-5},
	abstract = {The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution.},
	language = {en},
	number = {1},
	urldate = {2025-03-26},
	journal = {International Journal of Health Geographics},
	author = {Ghenassia, A. and Beuscart, J. B. and Ficheur, G. and Occelli, F. and Babykina, E. and Chazard, E. and Genin, M.},
	month = oct,
	year = {2017},
	keywords = {Change-of-support problem, Data reuse, Interoperability, Spatial analysis},
	pages = {36},
}

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