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Title:

MedSat: A Public Health Dataset for England Featuring Medical Prescriptions and Satellite Imagery

Document type:
Forschungsdaten
Publication date:
03.11.2023
Responsible:
Obadic, Ivica
Authors:
Sanja*,Šćepanović; Ivica*, Obadic; Sagar, Joglekar; Laura, Giustarini; Christiano, Nattero; Daniele, Quercia; Xiaoxiang, Zhu
Author affiliation:
Technical University of Munich: Obadic Ivica, Zhu Xiaoxiang
Nokia Bell Labs: Šćepanović Sanja, Quercia Daniele, Joglekar Sagar
WASDI: Giustarini Laura, Nattero Cristiano
Publisher:
TUM
Identifier:
doi:10.14459/2023mp1714817
End date of data production:
14.06.2023
Subject area:
DAT Datenverarbeitung, Informatik; MED Medizin
Other subject areas:
Public and Population Health
Resource type:
Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
Data type:
Bilder / images; Tabellen / tables
Description:
As extreme weather events become more frequent, understanding their impact on human health becomes increasingly crucial. However, the utilization of Earth Observation to effectively analyze the environmental context in relation to health remains limited. This limitation is primarily due to the lack of fine-grained spatial and temporal data in public and population health studies, hindering a comprehensive understanding of health outcomes. For the years 2019 (pre-COVID) and 2020 (COVID), we colle...     »
Method of data assessment:
The environmental variables were collected using the Google Earth Engine platform. The sociodemographic features were derived from the latest UK census in 2021. The Sentinel-2 image tiles were collected from the WASDI platform. The prescription data was provided by the UK National Health Service and we used the DrugBank database to match the prescriptions to specific medical conditions.
Key words:
prescription prediction; public health modelling; environmental impact on health
Technical remarks:
Representative Dataset: View and download (25 GB total, 35 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1714817.rep):
rsync rsync://m1714817.rep@dataserv.ub.tum.de/m1714817.rep/

Entire Dataset: View (1,01 TB total, 309 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1714817):
rsync rsync://m1714817@dataserv.ub.tum.de/m1714817/
Language:
en
Rights:
by-sa, http://creativecommons.org/licenses/by-sa/4.0
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