Odds are that the next mass contagion will jump to humans from animals. But which species?
What’s new: Virus hunters are using learning algorithms to learn which animals are likely to carry microbes that pose a danger to humans, The New York Times reported.
How it works: Several systems trained on biological, ecological, and genetic data have shown promise in identifying sources of interspecies infection.
- In 2022, researchers at nearly a dozen institutions trained an ensemble of eight models to classify bat species that are likely to host coronaviruses similar to the one that causes Covid-19. The architectures included k-nearest neighbors and a gradient boosted machine. The training data included a database of bat traits and a graph dataset of 710 animal species and viruses they carry. The system identified 400 bat species as carriers of pathogens that might infect humans.
- Last year, researchers at the University of Glasgow trained a gradient boosted machine to identify animal viruses with high risk of infecting humans. The model considered the proportion of human-infecting variants in a given virus family, features of carrier species, and features of viral genomes. It identified 313 potentially dangerous animal viruses.
- Those studies build on 2015 work at Princeton and University of Georgia, where researchers trained a gradient boosted machine to classify whether a given rodent species is likely to carry pathogens that can infect humans. The data included a dataset that detailed 86 traits of rodent species and another that cataloged rodent-borne viruses known to infect humans. The model pointed to 58 species previously not considered threatening that may harbor dangerous diseases and 159 likely to carry multiple diseases that previously were believed to carry just one.
Behind the news: The AI community isn’t just working to predict future pandemics, it’s also fighting the current one.
- Covid Moonshot, a global collaboration of over 150 scientists and machine learning engineers, designed multiple antiviral drugs to target the virus that causes Covid-19. Clinical trials are expected to begin this year.
- Researchers at MIT trained a language model to predict genetic mutations that would increase the infectiousness of the virus that causes Covid-19.
- Pharmaceutical giant Pfizer accelerated development of its Covid-19 vaccine by a month by using a machine learning tool called Smart Data Query to analyze clinical trial data.
- Despite efforts to build models capable of diagnosing and prognosticating Covid-19 from medical images, a 2021 survey found that none of the proposed models was clinically useful owing to biases or flaws in methodology.
Why it matters: Ebola, HIV, swine flu — many dire human diseases evolved in animals. Using AI to identify viruses likely to cross the species barrier could give scientists a jump on whatever comes next. Medical researchers could develop vaccines and treatments ahead of time, and officials could mitigate the spread of potentially dangerous disease by managing animal populations and limiting trade in disease-carrying species.
We’re thinking: Whether an animal virus can infect a human is one question. Whether it can cause a pandemic is another. Machine learning engineers have an opportunity to help answer that one as well.