“Stellenbosch University’s Houriiyah Tegally has been recognised in the inaugural AI for Discovery awards for research combining artificial intelligence with genomic, epidemiological and climate data to improve infectious-disease monitoring and outbreak forecasting. The recognition highlights South Africa’s contribution to emerging computational approaches in biomedical research, although it does not represent the discovery of a new treatment or a confirmed outbreak prediction.”
Stellenbosch University’s AI-driven infectious disease research earns international recognition
South African biotechnology and genomics research gains global attention as scientists combine artificial intelligence, pathogen sequencing and environmental information to strengthen epidemic intelligence.
South Africa’s biotechnology research sector has received fresh international attention following recognition of a Stellenbosch University research team for its work applying artificial intelligence to infectious-disease research. The achievement highlights the growing relationship between biotechnology, genomic science and computational innovation, particularly as researchers seek better ways to understand pathogens and anticipate public-health risks.
The research team, operating through the Centre for Epidemic Response and Innovation (CERI) at Stellenbosch University, received recognition in the Health and Life Sciences category of the Nature Awards AI for Discovery. The award acknowledges scientific teams using artificial intelligence to advance research and address major challenges affecting society.
Professor Houriiyah Tegally leads the team’s work on computational approaches to infectious diseases. Its research combines pathogen genomic information with epidemiological, environmental and climate-related datasets to investigate how infectious diseases evolve, circulate and potentially emerge in new locations.
The recognition was reported by South African media on 10 November and featured in a biotechnology-related report published on 11 November 2026.
Biotechnology meets artificial intelligence
Biotechnology increasingly depends on advanced computational systems capable of analysing enormous volumes of biological information. Genomic sequencing can reveal the genetic composition of pathogens, but interpreting those sequences and connecting them with epidemiological developments requires substantial analytical capacity.
Artificial intelligence offers researchers additional ways to investigate these complex relationships.
At Stellenbosch University’s CERI, scientists are developing machine-learning approaches that analyse pathogen genomes and investigate patterns associated with infectious-disease evolution and transmission. Their work also incorporates environmental and geographical information to improve understanding of the conditions that influence disease circulation.
According to the research team, AI can connect datasets that were not originally designed to work together. These may include genomic sequences, population information, climate observations, geographical characteristics and epidemiological records.
By combining these sources, researchers can investigate relationships that conventional analytical approaches might struggle to identify efficiently.
The broader objective is to improve scientific understanding of infectious diseases and develop tools that could eventually support more informed public-health decisions.
Understanding pathogens through genomic research
Genomics is a central component of the team’s scientific approach.
Pathogen genomes contain information about the biological characteristics and evolutionary history of infectious organisms. Comparing genomic sequences collected at different locations and times can help researchers investigate how pathogens change and move between populations.
However, genomic information alone does not necessarily explain the complete picture of disease transmission.
Researchers must also consider factors such as human mobility, environmental conditions, population distribution and the circumstances under which pathogens encounter susceptible populations.
The Stellenbosch team is working to integrate these different information sources into computational models that can provide broader insights into disease behaviour.
This approach builds on South Africa’s established experience in infectious-disease genomic surveillance, particularly during the COVID-19 pandemic.
The pandemic demonstrated the importance of rapidly collecting, analysing and sharing pathogen genomic information. South African scientists contributed significantly to international understanding of SARS-CoV-2 evolution, including the identification and investigation of important variants.
The scientific infrastructure, expertise and collaborations developed during that period have helped create a foundation for subsequent research involving artificial intelligence and genomic epidemiology.
Improving the analysis of infectious diseases
One important research direction involves making pathogen genomic analysis faster and potentially more accessible.
Traditional genomic workflows can require considerable computing resources and specialised expertise. These requirements may limit the ability of institutions with smaller research budgets to conduct large-scale analyses.
Machine-learning techniques could help simplify certain analytical processes and make it easier to examine extensive collections of genomic sequences.
The researchers are investigating alternative ways of representing and analysing genetic information, with the intention of reducing some computational barriers.
Such developments could be particularly valuable for African research institutions, where infectious diseases frequently create substantial public-health challenges and where scientific resources are unevenly distributed.
Nevertheless, computational efficiency alone is insufficient. Researchers must ensure that analytical methods remain scientifically reliable and that results can be independently evaluated.
The value of AI in biotechnology therefore depends not only on speed but also on accuracy, reproducibility and appropriate interpretation.
Climate and environmental information become increasingly important
A further dimension of the Stellenbosch research involves examining the relationship between environmental change and infectious diseases.
Climate conditions, rainfall patterns, temperature, flooding and changes in human settlement can influence the geographical distribution of certain pathogens and disease vectors.
For example, mosquito-borne diseases may be affected by environmental conditions that influence mosquito populations and their ability to survive and reproduce.
The research team is exploring ways to combine climate observations, environmental information and geographical datasets with genomic and epidemiological evidence.
This can help researchers investigate where conditions may become more favourable for particular infectious diseases and how those conditions change over time.
Diseases such as dengue, chikungunya and cholera are among the climate-sensitive infections discussed in connection with this research.
The objective is not to claim that environmental change automatically produces an outbreak. Rather, researchers are attempting to identify combinations of conditions that may increase disease risks and improve the information available to public-health authorities.
According to Professor Tegally, integrating diverse datasets can help researchers identify patterns that might otherwise remain difficult to detect.
Moving towards predictive epidemic intelligence
The longer-term ambition behind this work is to strengthen predictive epidemic intelligence.
Conventional disease surveillance frequently focuses on identifying infections after they have occurred. Although this remains essential, researchers increasingly want to understand whether available information can help anticipate emerging risks before outbreaks become widespread.
Predictive systems could potentially combine genomic surveillance, environmental monitoring, epidemiological information and human mobility patterns.
Such systems may help identify locations requiring additional surveillance, support investigations into disease introduction and provide information for planning public-health interventions.
However, forecasting infectious diseases remains scientifically challenging.
Pathogens behave differently, populations have varying levels of immunity, and outbreaks are influenced by many interconnected factors. Incomplete information, changing human behaviour and limitations in surveillance can also affect predictive accuracy.
Consequently, AI-generated forecasts must be treated as research outputs requiring validation rather than definitive predictions.
The Stellenbosch initiative represents a contribution towards developing more sophisticated analytical capabilities, not evidence that future epidemics can already be predicted with certainty.
South Africa’s contribution to African biotechnology
The recognition also carries significance for South Africa’s broader biotechnology ambitions.
The country has established research institutions, universities, scientific laboratories and public-health networks that support advanced biomedical investigations.
Stellenbosch University’s work illustrates how these capabilities can be extended through collaboration between biological scientists, computational researchers and epidemiologists.
Developing AI research capacity within African institutions is particularly important because disease patterns, environmental conditions and public-health priorities can differ substantially across regions.
Locally developed scientific approaches can help researchers investigate questions relevant to African populations while contributing knowledge that may benefit international research.
The award therefore highlights more than an individual research achievement. It draws attention to the importance of sustained investment in scientific infrastructure, specialist training and interdisciplinary collaboration.
CERI’s work also demonstrates how expertise developed during earlier epidemic responses can be adapted to new research challenges.
The importance of scientific collaboration and training
Advanced biotechnology depends on teams with diverse skills.
Genomic scientists must work alongside bioinformaticians, epidemiologists, environmental researchers and public-health specialists. The combination allows research teams to interpret biological findings within broader scientific and social contexts.
Training is equally important.
Researchers require expertise in genomic analysis, computational modelling, machine learning and the interpretation of complex datasets.
South Africa’s universities can contribute to building this workforce through postgraduate programmes, research fellowships and international partnerships.
At the same time, developing and maintaining advanced research systems requires dependable funding and access to computing infrastructure.
Long-term scientific investment can help institutions retain experienced researchers and create opportunities for younger scientists to participate in innovative biotechnology projects.
The Stellenbosch research recognition provides an example of how interdisciplinary scientific work can attract international visibility.
Responsible use of artificial intelligence in biotechnology
Despite its potential, artificial intelligence introduces important scientific and ethical considerations.
Models may produce inaccurate conclusions when datasets are incomplete, biased or poorly representative of the populations being studied.
Disease surveillance systems also involve sensitive information. Researchers must protect privacy, maintain appropriate data governance and ensure that scientific outputs are not misinterpreted.
In public-health applications, transparency is especially important.
Authorities should understand the limitations of predictive systems and avoid treating algorithmic outputs as substitutes for expert judgement.
The researchers’ ambition to improve epidemic intelligence therefore requires continued validation, careful evaluation and responsible collaboration with public-health institutions.
The ultimate objective is to develop useful scientific tools while maintaining public confidence in the research process.
Implications for future biomedical innovation
The award-winning research sits within a wider transformation in biotechnology.
Scientists increasingly use computational tools to investigate biological systems, identify patterns in genomic information and develop new approaches to understanding diseases.
These developments could eventually influence infectious-disease surveillance, biomedical research, clinical investigations and the design of public-health interventions.
For South Africa, they also create opportunities to strengthen the connection between scientific discovery and practical applications.
Nevertheless, translating research into operational public-health systems requires additional work.
Research findings must be validated, analytical tools tested under real-world conditions and institutional partnerships established before reliable implementation can occur.
The current recognition should therefore be understood as an important research milestone rather than the completion of a predictive disease-control system.
Conclusion
Stellenbosch University’s recognition in the Nature Awards AI for Discovery programme underscores South Africa’s growing contribution to the intersection of biotechnology, genomics and artificial intelligence.
Professor Houriiyah Tegally and her colleagues are developing computational approaches that combine pathogen genomic information with epidemiological, climate and environmental datasets to investigate infectious diseases.
Their work builds on South Africa’s experience in genomic surveillance and reflects the increasing importance of interdisciplinary research in addressing global health challenges.
Although substantial scientific validation and implementation work remains, the initiative demonstrates how African research institutions can contribute to developing advanced technologies for infectious-disease research.
As biotechnology continues to evolve, combining genomic science with artificial intelligence may become increasingly important in strengthening disease surveillance, expanding scientific knowledge and supporting more informed public-health responses.
For South Africa, the achievement represents a meaningful example of scientific innovation with potential regional and international significance.
