Software to Facilitate Remote Sensing Data Access for Disease Early Warning Systems.

Area of Science:

• Environmental science
• Epidemiology
• Geographic Information Systems (GIS)

Background:

• Satellite remote sensing generates vast environmental data applicable to human health studies.
• Developing effective early warning systems for mosquito-borne diseases is crucial for public health.
• Existing systems may lack automated data processing and adaptability.

Purpose of the Study:

• To develop an open-source software application, Epidemiological Applications of Spatial Technologies (EASTWeb), for utilizing satellite data in disease forecasting.
• To automate the discovery, retrieval, and processing of diverse remote sensing data.
• To create a flexible system adaptable to changing data availability and user requirements.

Main Methods:

• Implemented a client-based software application with a focus on full automation.
• Developed a software framework for efficient data downloading from multiple sources.
• Designed a scheduler to manage complex data processing task dependencies and ensure error resilience.

Main Results:

• EASTWeb successfully automates the integration of satellite remote sensing data for health applications.
• The system demonstrated resilience to external errors through its task dependency scheduler.
• Successfully applied to forecast West Nile virus outbreaks in the United States and malaria epidemics in the Ethiopian highlands.

Conclusions:

• EASTWeb provides a robust and adaptable platform for leveraging satellite data in epidemiological surveillance.
• The software facilitates the development of timely and accurate early warning systems for vector-borne diseases.
• Automation and system flexibility are key to advancing the application of spatial technologies in public health.