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Big Data and the Global Public Health Intelligence Network (GPHIN).
M Dion1, P AbdelMalik2, A Mawudeku2
1Schulich School of Family Medicine and Dentistry, University of Western Ontario, London, ON.
The Global Public Health Intelligence Network (GPHIN) uses Big Data to detect infectious disease outbreaks early. Integrating more data sources and improving analytics can further enhance global public health surveillance.
Area of Science:
- Public Health
- Epidemiology
- Data Science
Background:
- Globalization increases the risk of rapid infectious disease spread.
- Early detection and surveillance are critical for global public health.
- The Global Public Health Intelligence Network (GPHIN) was created to enhance early detection of public health events.
Purpose of the Study:
- To evaluate GPHIN's use of Big Data for early infectious disease outbreak detection.
- To identify future directions for GPHIN's capabilities.
Main Methods:
- Analysis of over 20,000 daily online news reports from 30,000+ sources in nine languages.
- Utilizing a web-based program with an algorithm to identify potential public health event signals.
- Review of potential signals by a multilingual, multidisciplinary team for risk assessment and alert issuance.
Main Results:
- GPHIN successfully identified early outbreaks, including SARS in China.
- GPHIN issued the first alert for MERS-CoV and played a key role in monitoring the Ebola outbreak.
- The system's effectiveness led to its adoption by several countries to meet International Health Regulations.
Conclusions:
- GPHIN's early adoption of Big Data has significantly improved global capacity for detecting international infectious disease outbreaks.
- Further integration of diverse Big Data sources (e.g., social media) can enhance detection capabilities.
- Advancements in analytical capacity are crucial for strengthening GPHIN's timely detection and early warning systems.
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