Using blood glucose data as an indicator for epidemic disease outbreaks

Area of Science:

• Public Health
• Biomedical Informatics
• Epidemiology

Background:

• Timely detection of infectious disease outbreaks is crucial for preventing widespread transmission.
• Current systems may not adequately identify outbreaks during incubation periods.
• Integration of patient sensor data into healthcare systems is an emerging trend.

Purpose of the Study:

• To propose and develop a system for early epidemic outbreak detection using blood glucose data.
• To investigate the potential of continuous blood glucose monitoring for identifying infectious diseases.
• To leverage electronic health records (EHR) for public health surveillance.

Main Methods:

• Collected blood glucose data from patients with diabetes.
• Developed a mobile system for automatic wireless transfer of blood glucose values (Bluetooth, GSM).
• Integrated data into an EHR system for central analysis and surveillance.

Main Results:

• Demonstrated the feasibility of using blood glucose fluctuations to indicate potential infections.
• Proposed an Epidemic Disease Detection using blood Glucose (EDDG) system.
• Highlighted the potential for early warning of outbreaks like Influenza, Ebola, and SARS.

Conclusions:

• Continuous monitoring and analysis of blood glucose data offer a novel approach for early epidemic detection.
• The EDDG system can empower health authorities to implement timely interventions.
• Integrating sensor data into EHR systems is key for future public health surveillance.