Proactive Shield against Emerging Health Threats
Our outbreak detection system redefines public health surveillance in Nigeria by merging real-time data analytics, AI-driven pattern recognition, and community-driven reporting. Designed to address Africa’s fragmented disease monitoring systems, this feature empowers governments, healthcare providers, and citizens to act swiftly against epidemics.How It Works
Knua aggregates anonymized health data from hospitals, wearable devices, lab reports, and community symptom self-reports. Environmental sensors track air and water quality, correlating pollution spikes with disease trends like cholera. Advanced machine learning models, trained on Nigerian disease profiles, detect anomalies in symptom clusters or vital sign trends within 24–48 hours-far faster than traditional 7–10 day reporting cycles.Geospatial mapping tags outbreaks to specific locations, identifying high-risk zones using historical data and population density. Automated alerts notify healthcare providers and agencies like the Nigeria Centre for Disease Control (NCDC), while SMS/USSD warnings advise residents in affected areas to seek testing or adopt preventive measures.
Key Features
Multilingual Symptom Reporting: Supports Hausa, Yoruba, and Igbo interfaces for rural communities.Geofenced Responses: Triggers localized interventions, such as deploying mobile clinics or conducting door-to-door vaccinations in outbreak zones.
Epidemic Tracing: Anonymously tracks infection chains using contact-tracing algorithms to contain spread.