作者
Livia Abdalla, Douglas A Augusto, Marcia Chame, Amanda S Dufek, Leonardo Oliveira, Eduardo Krempser
发表日期
2022/8/10
期刊
Scientific Data
卷号
9
期号
1
页码范围
489
出版商
Nature Publishing Group UK
简介
The lack of georeferencing in geospatial datasets hinders the accomplishment of scientific studies that rely on accurate data. This is particularly concerning in the field of health sciences, where georeferenced data could lead to scientific results of great relevance to society. The Brazilian health systems, especially those for Notifiable Diseases, in practice do not register georeferenced data; instead, the records indicate merely the municipality in which the event occurred. Typically in data-driven modeling, accurate disease prediction models based on occurrence requires socioenvironmental characteristics of the exact location of each event, which is often unavailable. To enrich the expressiveness of data-driven models when the municipality of the event is the best available information, we produced datasets with statistical characterization of all 5,570 Brazilian municipalities in 642 layers of thematic data that …
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