AEDES aims to improve public health response against dengue in the Philippines by predicting dengue cases from climate and digital data and pinpointing possible hotspots from satellite data.

The service relies on 3 data sets:

• Global Data: Satellite imaging data from Sentinel-2 Copernicus and Landsat
• Local Data: Climate data from DOST-PAGASA
• Digital Data: Google search trends for 'dengue' and related terms
• Disease Surveillance Data: Regional cases and deaths data from Department of Health

We propose to forecast dengue cases using a combination of:

• Climate Data: Average monthly temperature readings from local weather stations
• Climate Data: Average monthly rainfall (precipitation) readings from local weather stations
• Google Data: Search index for 'dengue', 'dengue symptoms', 'dengue fever', and 'dengue medicine'
• Lagged values for Climate factors, Google data, and actual dengue cases

We propose to detect likely mosquito hotspots using Satellite data readings:

• FAPAR: Fraction of Absorbed Photosynthetically Active Radiation, reference here.
• NDVI: Normalized difference vegetation index, reference here.
• NDWI: Normalized Difference Water Index, reference here.

More project resources can be found here in the AEDES Github.

Project AEDES is maintained by CirroLytix Research Services. The AEDES team consists of the following:

• Dominic Ligot, Chief Technology Officer
• Mark Toledo, Solution Architect
• Claire Tayco, Head of Research and Analytics
• Rache Melendres, Analytics Consultant
• Cricket Soong, Emerging Technologies Consultant

We welcome collaborators. Contact us via Linked-IN, or email us at support@aedesproject.org.