Kenyan Scientist Wins Sh187 Million Gates Grant to Build AI Tool for Early Disease Outbreak Detection

By Linda Olendo

Kenyan scientist Dr Samuel Oyola has secured a Sh187 million grant from the Gates Foundation to develop an artificial intelligence-powered public health tool designed to predict disease outbreaks and track drug-resistant pathogens.

Dr Oyola, a senior scientist and Head of Genomic Science at the International Livestock Research Institute, received the $1.45 million funding to advance wastewater-based disease surveillance in Kenya. The project will involve two PhD students who will help analyse data using artificial intelligence.

The researchers will collect wastewater samples from 30 sites—18 in Kisumu and 12 in Mombasa—as part of a follow-up study that began during the Covid-19 pandemic.

Kisumu and Mombasa were selected because Nairobi already has a similar wastewater surveillance programme, while the two cities have some of the country’s other well-connected sewer networks.

Dr Oyola said the team established during the Covid-19 pandemic that wastewater can be used to detect pathogens and estimate the disease burden circulating within a community.

“In Africa, generally, our health-seeking behaviour is very poor. People can get ill and stay at home even when the disease they have could cause an outbreak,” he said.

He noted that wastewater surveillance can bridge this gap because nearly everyone uses a toilet, whether or not they seek treatment at a health facility.

“If they are infected, they can shed the pathogen in the wastewater. Environmental surveillance is then able to detect the pathogens that have been shed by a given population,” he added.

According to Dr Oyola, every wastewater sample provides a snapshot of the pathogens circulating among people living in areas served by a particular sewer line.

The researchers have already analysed data and generated pathogen profiles from different populations over time. Their next step is to develop the wastewater environmental surveillance platform into an early-warning system for public health authorities.

“This project is concerned with using wastewater data, overlaying it with clinical data or clinical cases, and then using that to model disease burden and transmission dynamics within populations,” Dr Oyola explained.

Once developed, the tool will use digital dashboards to relay information to public health officials. The dashboards will enable authorities to identify diseases circulating within communities, determine areas with the highest disease burden and prioritise interventions before outbreaks spread widely.

Beyond identifying pathogens, the system will also help scientists track antimicrobial resistance. Dr Oyola said researchers extract and sequence genetic material from wastewater samples, allowing them to identify pathogens carrying antimicrobial-resistant genes.

He said the project could strengthen Kenya’s ability to detect outbreaks earlier, improve public health response and enhance preparedness for future pandemics.

The initiative comes as Kenya and other African countries increasingly turn to data, genomics and artificial intelligence to strengthen disease surveillance and respond faster to emerging public health threats.

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