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Artificial intelligence is opening new possibilities for understanding infectious diseases and anticipating emerging health threats. An award-winning South African research team is developing approaches that could strengthen disease surveillance and public health responses in Africa and beyond.

A multidisciplinary research team at the Centre for Epidemic Response and Innovation (CERI) at Stellenbosch University has won the Health and Life Sciences category of the Nature Awards AI for Discovery, recognising its innovative application of artificial intelligence (AI) to some of the world's most pressing infectious disease challenges.

Led by Prof Houriiyah Tegally, the team is developing and applying machine learning approaches to analyse pathogen genomes, investigate how infectious diseases evolve and spread, and identify environmental conditions that may increase the risk of outbreaks.

By combining expertise in genomics, epidemiology, evolutionary biology, environmental science, and computational research, the team is finding new ways to extract meaningful information from complex datasets. Its work could make genomic analysis faster and more accessible, improve understanding of disease transmission, and ultimately support earlier identification of emerging public health threats.

"I believe AI gives us an opportunity to ask bigger questions and tackle health challenges in ways we couldn't before," says Prof Tegally. "For us, it's about using that opportunity to push the boundaries of scientific discovery and, ultimately, make a difference to people's lives. I'm incredibly proud of what our team is building, and I know this is just the beginning."

The Nature Awards AI for Discovery recognise research teams using AI to advance scientific discovery and address major societal challenges. Prof Tegally will travel to London to receive the award on behalf of the team.

African Leadership in AI and Health Discovery

Prof Tulio de Oliveira, Director of CERI, says the award reflects a strategic decision to invest in AI research and build the expertise needed to develop new computational approaches.

"Four years ago, well before the breakthrough of ChatGPT brought artificial intelligence into the global spotlight, we made a bold decision to embrace AI in our research. It took years of hard work to build a world-class team capable not only of using AI, but of developing entirely new AI models to track and predict epidemics."

The team's research builds on CERI's established expertise in infectious disease genomics and large-scale genomic surveillance, including its contributions during the COVID-19 pandemic. Although that surveillance was not itself AI-driven, it helped establish the scientific foundation, data expertise, and collaborative networks now supporting the development of new AI approaches.

The work also reflects the importance of developing AI technologies within Africa, where infectious diseases remain a substantial public health challenge. Rather than relying exclusively on technologies developed elsewhere, African researchers are contributing to how these tools are designed, trained, and applied to address regional health priorities.

Central to this effort is a multidisciplinary team combining biological understanding, computational expertise, and public health experience. The collaboration is helping strengthen African scientific capacity in a rapidly developing field with growing importance for infectious disease research.

New Approaches to Infectious Disease Research

For the CERI researchers, AI is not a replacement for established scientific methods, but a way to investigate biological and environmental relationships that would be difficult to analyse using conventional approaches alone.

One area of research focuses on making pathogen genomic analysis faster and more accessible. Identifying and classifying viruses using conventional methods can require substantial computational resources and specialist expertise. The team is developing machine learning approaches that analyse genomic sequences using alternative representations of genetic information, potentially bypassing some of the computationally intensive steps involved in traditional analysis.

These approaches could make genomic research more scalable, particularly in settings with limited computational resources.

Another focus is understanding where infectious diseases are more likely to circulate and spread. The researchers are using deep learning to investigate how environmental and geographical conditions influence diseases such as dengue. By examining broader spatial patterns, these approaches can capture complex relationships between climate, landscape, and disease suitability that conventional methods may overlook.

The team is also combining machine learning with phylogenetics and phylodynamics to investigate pathogen evolution and transmission. Integrating genomic, geographical, and environmental information could provide new insights into how pathogens move between populations and the factors influencing their spread.

Graeme Dor, a member of the research team, explains how AI is expanding the possibilities for analysing these complex relationships.

"In my experience, AI-based approaches, particularly deep learning methods, are enabling us to develop models that integrate and explore high-dimensional datasets, including genomic, environmental and epidemiological information, in ways that were previously difficult to achieve," he says.

"These models have the potential to better capture the complexity of real-world transmission dynamics across different spatial and temporal scales, ultimately improving our understanding of pathogen spread and supporting more informed public health responses."

Together, these research areas contribute to CERI's longer-term ambition of developing predictive epidemic intelligence. By integrating genomic, epidemiological, climate, and environmental data, the researchers hope to identify where and when infectious disease risks may increase, helping public health authorities anticipate emerging threats and respond earlier.

"By combining vast datasets from satellites, human mobility, climate and the environment, we are moving beyond understanding how epidemics spread to predicting where new pathogens may emerge, how they will spread, and which populations will be most affected," says Prof de Oliveira.

"Our ambition is to move from reacting to epidemics to anticipating and preventing them. This award is a wonderful recognition of our team's dedication and demonstrates how cutting-edge science developed in Africa can help make the entire world safer."

For Prof Tegally, the recognition also highlights the potential of African scientists to contribute to advances in AI-driven health discovery.

"There is extraordinary scientific talent and potential in Africa. I hope our work shows what is possible when we combine that expertise with new technologies like AI, and create solutions that can make a difference far beyond our own borders."

 

 

About the Nature Awards AI for Discovery
The Nature Awards AI for Discovery recognise research teams applying artificial intelligence to advance scientific discovery across different fields, including health and the life sciences. More information: https://www.nature.com/immersive/aifordiscovery/index.html

About CERI at Stellenbosch University
The Centre for Epidemic Response and Innovation (CERI), based at Stellenbosch University’s School for Data Science and Computational Thinking, works to strengthen Africa’s capacity to detect, understand and respond to epidemic threats through genomics, data science and innovation.

Media Contact
Maambele Khosa
Head: Communications and Marketing (CERI)
Maambele@sun.ac.za
+27 79 592 9174

News date: 2026-11-05

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