A new study published in the journal Nature on April 28, 2026, describes a safer method for identifying animal viruses that could cause the next pandemic. Researchers from the University of California, Davis, and the University of Edinburgh developed a technique that uses computational modeling and cell-based assays to assess viral spillover risk without handling live, dangerous pathogens.
The approach, called 'Pandemic Risk Assessment by Computational Analysis' (PRACA), analyzes viral genome sequences and protein structures to predict which viruses can bind to human cell receptors. This reduces the need for high-containment biosafety labs and minimizes accidental exposure risks. The team tested PRACA on over 500 bat coronaviruses, correctly identifying 90% of those known to infect human cells.
Dr. Sarah Johnson, lead author from UC Davis, stated: 'Our method allows us to screen thousands of viruses quickly and safely, prioritizing those that warrant closer study.' The World Health Organization has expressed interest in using PRACA for global surveillance. The study was funded by the U.S. National Institutes of Health and the UK Research and Innovation.
