Georeferenced data in epidemiologic research
This paper reviews some conceptual and practical issues regarding the application of georeferenced data in epidemiologic research. Starting with the disease mapping tradition of geographical medicine, topics such as types of georeferenced data, implications for data analysis, spatial autocorrelation and main analytical approaches are heuristically discussed, relying on examples from the epidemiologic literature, most of them concerning mapping disease distribution, detection of disease spatial clustering, evaluation of exposure in environmental health investigation and ecological correlation studies. As for concluding remarks, special topics that deserve further development, including the misuses of the concept of space in epidemiologic research, issues related to data quality and confidentiality, the role of epidemiologic designs for spatial research, sensitivity analysis and spatiotemporal modeling, are presented.
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| Format: | Digital revista |
| Language: | English |
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ABRASCO - Associação Brasileira de Saúde Coletiva
2008
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1413-81232008000600010 |
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| Summary: | This paper reviews some conceptual and practical issues regarding the application of georeferenced data in epidemiologic research. Starting with the disease mapping tradition of geographical medicine, topics such as types of georeferenced data, implications for data analysis, spatial autocorrelation and main analytical approaches are heuristically discussed, relying on examples from the epidemiologic literature, most of them concerning mapping disease distribution, detection of disease spatial clustering, evaluation of exposure in environmental health investigation and ecological correlation studies. As for concluding remarks, special topics that deserve further development, including the misuses of the concept of space in epidemiologic research, issues related to data quality and confidentiality, the role of epidemiologic designs for spatial research, sensitivity analysis and spatiotemporal modeling, are presented. |
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