By Our Reporter
As Nigeria intensifies efforts to eliminate malaria, the National Malaria Elimination Programme (NMEP) and Sproxil Nigeria Limited have explored the use of artificial intelligence (AI), digital technology and private sector data to strengthen the country’s malaria response.
The two organisations, alongside health experts and development partners, held a two-day strategic alignment meeting in Lagos on August 6 and 7, 2026, to examine how technology can improve malaria surveillance, diagnosis, health communication and support for health workers.
Malaria remains a major public health challenge across Africa, with Nigeria carrying a significant share of the burden. Although the country has recorded progress in recent years, stakeholders at the meeting said new approaches are needed to move from malaria control to eventual elimination.
National Coordinator of NMEP, Dr. Nnenna Chizaram Ogbulafor, said AI could help the country improve the speed and quality of its malaria response.
“Artificial Intelligence offers us an opportunity to improve how we collect data, monitor interventions and strengthen programme implementation,” she said.
“Technology enables us to work smarter and respond faster, making it a critical part of the future of malaria control in Nigeria.”
Ogbulafor, citing the 2025 Malaria Indicator Survey, said malaria prevalence in Nigeria had declined to about 15 per cent, attributing the progress to sustained investments in prevention, diagnosis and treatment.
However, the meeting noted that significant gaps remain in malaria surveillance, particularly among Nigerians who seek treatment outside government health facilities.
Millions of Nigerians obtain medicines or seek healthcare advice from community pharmacies and Patent and Proprietary Medicine Vendors (PPMVs), generating information that is often not captured by the national malaria surveillance system.
Founder and Chief Executive Officer of Sproxil, Dr. Ashifi Gogo, said integrating private sector information with government data could provide a more complete picture of malaria trends.
“Those interactions generate valuable information, yet they are largely invisible to the National Malaria Elimination Programme,” Gogo said.
He added, “If we can combine government data with insights from the private healthcare ecosystem, policymakers will have a much clearer picture of where malaria is occurring and where interventions are most urgently needed. Better information leads to better decisions.”
The meeting also examined Sproxil’s AI-assisted malaria Rapid Diagnostic Test (mRDT) reading and digital verification technology, which could help accelerate Test Positivity Rate reporting from government facilities.
Dr. Ibrahim Maikore, National Professional Officer for Malaria Surveillance at the World Health Organisation (WHO) Nigeria Country Office, said improved diagnostic accuracy could support better treatment decisions while strengthening the quality of malaria surveillance data.
Participants also explored Sproxil’s AISHA conversational AI platform and its potential use for social and behaviour change communication, malaria awareness, health worker training and continuous support.
The discussions emphasised that while technology could significantly improve malaria surveillance and response, its adoption must be supported by scientific validation, quality assurance, responsible data governance and interoperability with existing government systems.
The meeting ended with plans for further collaboration around private sector routine malaria data collection, AI-assisted test reporting, health communication and technology-enabled support for health workers.
Stakeholders said stronger partnerships between government, the private sector, researchers and technology providers would be critical to ensuring that Nigeria’s progress against malaria is sustained and accelerated.
For Nigeria, the emerging lesson is clear: eliminating malaria will require not only continued investment in prevention and treatment, but also better data, faster decision-making and the responsible use of new technologies. NNL.
