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COVID-19 Geographical Maps and Clinical Data Warehouse PREDIMED
Svetlana Artemova1,2, Alban Caporossi1,2,3, Christophe Cancé2,3
1CHU Grenoble Alpes, F-38000, Grenoble, France.
Studies in Health Technology and Informatics
|June 8, 2022
Summary
PREDIMED uses spatial and chronological analysis of geographical maps for daily COVID-19 epidemic monitoring. This helps detect clusters and identify vulnerable populations both inside and outside the hospital.
Area of Science:
- Epidemiology
- Public Health
- Geographic Information Systems (GIS)
Background:
- The COVID-19 pandemic necessitates continuous monitoring of disease spread.
- Understanding geographical patterns is crucial for effective public health interventions.
- Clinical data warehouses can support real-time epidemic surveillance.
Purpose of the Study:
- To implement daily COVID-19 epidemic follow-up using spatial and chronological analysis.
- To detect disease clusters and identify vulnerable populations.
- To provide real-time geographical tracking of the epidemic within and outside a hospital setting.
Main Methods:
- Utilizing the PREDIMED Clinical Data Warehouse.
- Employing spatial and chronological analysis of geographical maps.
- Developing real-time geographical representations for epidemic monitoring.
Main Results:
- Daily monitoring of the COVID-19 epidemic is established.
- Spatial and chronological analysis facilitates cluster detection.
- Vulnerable populations can be identified through geographical mapping.
Conclusions:
- Real-time geographical representations are effective for tracking the COVID-19 epidemic.
- The PREDIMED system supports dynamic surveillance of infectious diseases.
- This approach aids in targeted public health responses during epidemics.
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