Recently, our Chief Technology Officer, Thys Potgieter, was interviewed on ENCA, South Africa’s 24-hour news broadcaster. During the discussion, he highlighted how AI is revolutionising the fight against TB. One of humanity's oldest and deadliest diseases, TB continues to pose a significant threat. According to the World Health Organization (WHO), 8.2 million people were diagnosed with TB in 2023, marking the highest annual figure ever recorded. But in the face of this alarming resurgence, AI offers new hope.
The shadow of COVID-19: Setting back the clock
The COVID-19 pandemic had far-reaching effects on global health, including undoing nearly two decades of progress in the fight against TB. Vulnerable communities have been hit hardest, with many at increased risk of developing TB or remaining undiagnosed.
Potgieter explained the long-term consequences of delayed diagnosis:
“When individuals with TB are not put on treatment early enough, it increases the risk of long-term complications and further transmission. These consequences can be devastating for already struggling families.”
AI in action: Mapping the fight against TB
Potgieter stated how EPCON is leading the charge by leveraging big data and AI to tackle TB, via:
Identifying TB Hotspots
Traditional screening methods often fall short, especially in underserved areas. By integrating data sources—ranging from health facility records to socioeconomic and satellite data—AI can pinpoint communities most at risk:
This methodology has already produced remarkable results:
In Nigeria, diagnosis rates increased by 75% using AI-driven hotspot mapping.
In South Africa’s Nelson Mandela Bay, the yield of TB-positive cases increased fourfold, reducing the cost of diagnosis per person from R30,000 to R8,000.
Collaboration is key
The ENCA TV interview also covered the collaboration required between tech companies, government and health organisations. Potgieter stressed how AI tools are only as effective as the systems and partnerships that support them.
Despite its promise, integrating AI into health systems faces significant hurdles, including a lack of technological infrastructure and policy gaps. Many regions lack the basic tools—like internet access and trained personnel—needed to deploy AI solutions effectively. In addition, local governments must adopt policies that prioritise AI integration, ensuring funding and training reach every level of the health system.
Potgieter called for a global commitment to address these challenges, emphasising that increased funding and systemic change are critical to maximising AI’s potential in combating TB.