Nigeria Case Study: AI Diagnostics, Logistics & Public Health Innovation

Nigeria’s health ecosystem is defined by scale, complexity, and innovation. With over 220 million people and major health resource gaps, AI-powered technologies are emerging as efficient tools for diagnostics, logistics, and public health planning.

This case study highlights Nigeria’s most compelling examples in 2025.

1. ADVISER: AI Optimizing Immunization Coverage

A standout innovation is ADVISER, an AI system used to maximize childhood vaccination reach by modeling optimal household outreach in a pilot of 13,000+ families.

Impact:

• Increased vaccination uptake

• Better allocation of limited health worker resources

• Smarter micro-planning based on real data

• Strong replicability for other African mass campaigns

Source: Mathematical optimization study (2024)

2. LifeBank: AI for Critical Medical Supply Logistics

LifeBank uses AI to match hospitals to the nearest available units of blood, oxygen cylinders, or critical supplies.

Why this matters:

• Reduces maternal mortality by ensuring fast access to blood

• Supports sickle cell emergencies

• Cuts wastage of perishable medical resources

• Provides real-time routing and availability

This model has already scaled across Nigeria, Kenya, and Ethiopia.

3. AI for Emergency Response & Disease Surveillance

Nigeria’s private and government-affiliated systems increasingly deploy AI in:

• Disease outbreak predictions

• Disease surveillance dashboards

• Emergency triage

• Decision support

These tools are improving response to infectious diseases and NCD burdens.

4. Challenges to Overcome

• Infrastructure limitations

• Data quality and health information fragmentation

• Regulatory uncertainties

• Equity issues (urban vs rural access)

Strategic Lessons from Nigeria

Nigeria’s experience shows that:

• AI diagnostic systems need strong workflow integration

• Data governance and regulatory clarity accelerate adoption

• Public-private models work best in large populations

• Diagnostics and logistics are the most scalable use cases