Innovative System to Auto-Detect Infectious Disease Variants Could Revolutionize Outbreak Response: Study Reveals - Video

Researchers have come up with a new way to identify more infectious variants of viruses or bacteria that start spreading in humans - including those causing flu, COVID, whooping cough and tuberculosis.

The new approach uses samples from infected humans to allow real-time monitoring of pathogens circulating in human populations, and enable vaccine-evading bugs to be quickly and automatically identified. This could inform the development of vaccines that are more effective in preventing disease.

It can be used for a broad range of viruses and bacteria and only a small number of samples, taken from infected people, are needed to reveal the variants circulating in a population. This makes it particularly valuable for resource-poor settings.

The report is published in the journal Nature.

“Our new method provides a way to show, surprisingly quickly, whether there are new transmissible variants of pathogens circulating in populations - and it can be used for a huge range of bacteria and viruses,” said Dr Noémie Lefrancq, first author of the report, who carried out the work at the University of Cambridge’s Department of Genetics.

The researchers used their new technique to analyse samples of Bordetella pertussis, the bacteria that causes whooping cough.

“The approach will quickly show which variants of a pathogen are most worrying in terms of the potential to make people ill. This means a vaccine can be specifically targeted against these variants, to make it as effective as possible,” said Professor Henrik Salje in the University of Cambridge’s Department of Genetics, senior author of the report.

He added: “If we see a rapid expansion of an antibiotic-resistant variant, then we could change the antibiotic that’s being prescribed to people infected by it, to try and limit the spread of that variant.”

The researchers say this work is an important piece in the larger jigsaw of any public health response to infectious disease.

Ref: Lefrancq, N., Duret, L., Bouchez, V. et al. Learning the fitness dynamics of pathogens from phylogenies. Nature (2025). https://doi.org/10.1038/s41586-024-08309-9