Multistakeholder Hearing on Pandemic Prevention, Preparedness and Response
The United Nations General Assembly convened a Multistakeholder Hearing as part of the preparatory process for a high-level meeting on Pandemic Prevention, Preparedness and Response. The hearing brought together governments, civil society organizations, private sector representatives, and technology innovators to examine the structural gaps in global pandemic readiness that COVID-19 so sharply exposed.
Among those identified gaps: the absence of a reliable, real-time early warning layer. By the time COVID-19 was declared a Public Health Emergency of International Concern, the virus had already crossed dozens of borders. Supply chains were collapsing. Governments were making decisions without data.
Virus Watcher participated in the hearing as a technology stakeholder, presenting AI-powered disease surveillance as a concrete solution to the detection gap that left governments and enterprises unprepared in 2020. The platform's approach to monitoring 200+ diseases across 50+ global data sources was offered as a model for how early warning intelligence can be operationalized at scale before the next outbreak becomes a crisis.
In this session, Virus Watcher presents the case for AI-driven disease surveillance as infrastructure for pandemic preparedness. The discussion covers how machine learning can compress the detection gap between when an outbreak begins and when governments receive actionable signals, the role of wastewater epidemiology and clinical data fusion in early detection, and why closing that window by even two to three weeks changes the entire response calculus.
Watch on YouTubeChris Ogbuehi recounts watching the COVID-19 pandemic unfold in real time: markets seizing, supply chains breaking, and governments making decisions in an information vacuum because no early warning system existed at the scale the moment required. He explains the decision to build Virus Watcher from scratch, the early architecture choices, and what it means to now brief at the United Nations on the same problem he set out to solve four years earlier.
Watch on YouTubeBy the time a disease is declared a Public Health Emergency of International Concern, it has typically been spreading undetected for weeks. Virus Watcher is designed to detect signals weeks earlier, before declarations and before headlines, giving decision-makers time to act rather than react.
200+ diseases monitored across 50+ data sources including wastewater epidemiology, clinical reports, emergency department feeds, and global health agency data. Machine learning correlates signals across sources to surface anomalies before they appear in official reports.
Virus Watcher was founded in direct response to the information vacuum of the COVID-19 pandemic. What began as a personal mission to build the intelligence layer that didn't exist in 2020 has grown into a platform now briefing at the United Nations on the future of pandemic preparedness.
The surveillance capabilities described at the United Nations are live and available today. Try the platform or read a real-world case study showing how early warning intelligence works in practice.
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