NCDC mulls social media integration to study disease patterns, strengthen health security, Pg13

Key Highlights:

• The National Centre for Disease Control (NCDC) is considering integrating social media data to improve disease pattern detection and outbreak surveillance.
• An existing AI-based event surveillance system scans millions of online news reports daily in 13 Indian languages.
• The system has processed over 300 million news articles, flagging over 95,000 health-related events.
• Metropolitan Surveillance Units (MSU) under the PM-Ayushman Bharat Health Infrastructure Mission (PM-ABHIM) have demonstrated real-time surveillance capabilities.
• A predictive model is being developed to integrate AI surveillance, laboratory intelligence, climatic data, and population movement patterns.

Detailed Insights:

• The current AI system has increased detection capacity by 150% and reduced workload for surveillance teams by 98%.
• The NCDC aims to create a future-ready public health system and enhance national readiness to manage infectious diseases and potential pandemics.
• The AI-powered systems identify unusual spikes in diseases like dengue and chikungunya, which are then verified by experts.
• The Metropolitan Surveillance Units (MSU) facilitated rapid coordination in a recent incident involving suspected Acute Encephalitis Syndrome cases.
• The predictive model aims to anticipate outbreak trajectories by integrating various data sources, including digital diagnostics.

Key Concepts Involved:

• Predictive Modeling: Using data analysis to forecast future events or trends.
• Disease Surveillance: Continuous monitoring of a population for specific diseases.
• Public Health Security: Measures to protect the population from health threats.