Multi-tier cloud infrastructure support for reliable global health awareness system

Area of Science:

• Public Health
• Computer Science
• Epidemiology

Background:

• Global outbreaks like Ebola, SARS, and Zika necessitate advanced health awareness systems for early detection and prediction.
• Existing systems struggle with resource limitations, global coordination, and infrastructure challenges.
• Effective systems require scalability across regions and continents for comprehensive global coverage.

Purpose of the Study:

• To present a novel global health awareness system addressing challenges in epidemic detection and prediction.
• To leverage cloud computing for a scalable and cost-effective health awareness solution.
• To reduce the latency in detecting and responding to global health emergencies.

Main Methods:

• Development of a multi-tier cloud-based system architecture spanning four tiers.
• Implementation of a mixed integer optimization formulation to minimize outbreak detection latency.
• Utilizing global cloud computing services for large-scale data processing and sharing.

Main Results:

• The proposed multi-tier system significantly reduces the overall delay in detecting health emergencies.
• Efficient health data sharing is enabled across the distributed system.
• The cloud-based approach overcomes resource and infrastructure limitations.

Conclusions:

• The novel multi-tier cloud system offers a reliable and efficient solution for global health awareness.
• This approach facilitates early detection and prediction of epidemic outbreaks.
• It enhances global health security by enabling timely countermeasure planning and data sharing.