Imagine a world where predicting a health crisis is as straightforward as forecasting the weather. How could this change the future of public health?
Fuse diverse big data using location.
– Earth observation satellites
– demographic studies
– cultural settlements
– POIs
– landforms
– land cover
– weather and climate
– and infrastructure
Then, analyze to find patterns, hot spots, and outliers, and model using machine learning to identify critical factors and predict disease outbreaks for improved planning and immediate intervention.
We provide a comprehensive analysis workflow that adheres to strict scientific and best practices to produce confident answers.
– Data collection from diverse sources and storage
– Data analysis and machine learning predictions
– Results visualization to decision-makers
– ** Improved public health outcomes **
We identified many interesting hot and cold spots and spatial outliers for various diseases. Our machine learning model successfully infers the presence of multiple diseases weekly at the administrative district level. Machine learning feature importance uncovered critical cultural and environmental factors affecting outbreaks and variations between diseases.
