Sense
Monitoring data, social listening, expert input, and repeatable search branches surface emerging health misinformation signals.
Bringing the forecast into view…
Loading the latest available early-warning signals.
Infodemic Meter
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Early-warning intelligence · 22 MENA countries
See the next infodemic forming.
Infodemic Meter is an AI-powered weather forecast for misinformation during the next pandemic. It combines outbreak evidence, expert input, and monitoring signals so health organisations can prepare before misleading narratives spread.
traceable signals time-series context human review ready
Forecast field active
22
MENA countries in the Atlas
Signal sequencemonitoring
Interpretationpotential leads
Scroll to trace the signal
The infodemic problem
Claims travel fast.
See it sooner.
Infodemic Meter is designed to make the change visible earlier: what is appearing, where it is branching, how quickly it is moving, and which evidence supports the signal.
Atlas / live signal field
See the signal move.
Country context, narrative branches, source signals, and time buckets sit together so analysts can see what is changing before a misleading claim becomes the only story in the room.
Potential leads are for review, not verdicts.
Change over time
Track the rise.
The Atlas prioritises trend movement over a single headline number. This illustrative view shows how a rising signal can be noticed before it becomes a dominant narrative.
Early warning, not automated truth.
Every lead remains a candidate for human review, with source and processing provenance visible beside it.
30 days agotoday
A reliable signal workflow
From noise to readiness.
LLMs can help normalize language, but the platform does not ask stochastic generation to carry the burden of measurement. Collection, normalization, statistics, and provenance keep the signal reproducible.
01
Narrative sensing
Find the keywords and branches that may become health misinformation narratives across 22 MENA countries.
Deterministic collection first02
Outbreak evidence memory
Bring thousands of COVID-19 and outbreak fact-checks into the context layer that helps teams anticipate what may return in a new crisis.
Evidence remains traceable03
Signal triangulation
Compare source activity, narrative abundance, trend change, and reliability without turning one stochastic model output into a verdict.
Signals are not prevalence04
Response readiness
Move from a rising signal to a prepared response with leads, provenance, and the surrounding time sequence in view.
Built for health organisationsFor health organisations
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