The Next Pandemic 2030: AI, Mutant Viruses, and Fake News
- Global health organizations and academic institutions are integrating artificial intelligence and large-scale data surveillance to transition from reactive pandemic response to a preventative model of viral threat assessment.
- A primary component of this effort is a new international collaboration involving UC Davis, UC Davis Health, the Coalition for Epidemic Preparedness Innovations (CEPI), and the Boston University-based...
- The partnership integrates the BEACON open-source disease surveillance program with the Virus Intelligence & Strategic Threat Assessment (VISTA) project, which was previously known as SpillOver 2.0.
Global health organizations and academic institutions are integrating artificial intelligence and large-scale data surveillance to transition from reactive pandemic response to a preventative model of viral threat assessment.
A primary component of this effort is a new international collaboration involving UC Davis, UC Davis Health, the Coalition for Epidemic Preparedness Innovations (CEPI), and the Boston University-based Biothreats Emergence, Analysis and Communication Network (BEACON project).
The partnership integrates the BEACON open-source disease surveillance program with the Virus Intelligence & Strategic Threat Assessment (VISTA) project, which was previously known as SpillOver 2.0.
AI-Driven Risk Assessment and Surveillance
The VISTA and BEACON collaboration utilizes AI-assisted tools and expert curation to provide risk rankings of viruses in near real time. This system is designed to identify viruses with the highest potential for spillover from animals to humans and those most likely to cause significant disease and death.
The foundation of the VISTA project is the SpillOver platform, an open database that researchers developed using public records and data from more than half a million animal samples collected across 28 countries. Using this data, researchers have ranked the spillover potential of nearly 900 wildlife viruses.
Angel Desai, principal investigator and associate professor of infectious disease at UC Davis Health
By identifying high-risk viruses and providing assessments of their pandemic risk potential, we’re not just reacting to pandemics — we’re working to prevent them.
According to Angel Desai, the integration of AI and global expert networks into these platforms represents a transformative shift in the anticipation and response to emerging infectious threats.
The Verena Research Initiative
Parallel to the UC Davis efforts, the Viral Emergence Research Initiative, known as Verena, is employing AI and team science to predict viral threats. Headquartered in the Public Health Modeling Unit at Yale University, Verena is one of the largest pandemic prevention research and training programs in the United States.
The initiative is supported by a $12.5 million grant from the National Science Foundation Biology Integration Institute, spanning from 2022 to 2027. The program has evolved into a network of eight institutions, including Yale, the University of Oklahoma, Washington State University, Colorado State University, and Tulane University.
Verena’s work builds on models of cross-species transmission developed using machine learning. To date, the initiative has produced more than 100 publications and preprints and has trained over 60 students and postdoctoral fellows.
Global Perspectives on AI and Pandemic Forecasting
The application of AI to pandemic preparedness is seeing global adoption. On March 6, 2025, scientists across Africa, America, Asia, Australia, and Europe outlined a framework in a Nature perspective paper on how artificial intelligence will facilitate the anticipation of future pandemics.
These technological advancements aim to address the uncertainties associated with mutant viruses and the potential for future outbreaks. This includes the use of AI to predict and prepare for outbreaks before they escalate into global crises.