The silent emergency: why Africa's health systems are not ready for the NCD wave
I have spent the past six years helping health ministries across Sub-Saharan Africa build the digital infrastructure they need to track disease and make decisions. I have sat in rooms with programme managers in Mauritania counting malaria cases on spreadsheets. I have watched data teams in Senegal spend weeks cleaning DHIS2 records that should have taken hours. And now, quietly, a new crisis is building that those same systems are almost entirely unprepared for.
Non communicable diseases, meaning diabetes, hypertension, cardiovascular disease and chronic respiratory conditions, are rising sharply across Africa. The World Health Organization estimates that they now account for over 37% of deaths on the continent, a figure climbing every year. Yet the surveillance systems, reporting tools and analytical capacity that ministries rely on were built almost entirely around infectious disease.
What the gap looks like from the field
Across assignments in Senegal, the Democratic Republic of the Congo, Burkina Faso and elsewhere, a pattern repeats. Ministries have invested, often with significant donor support, in platforms like DHIS2, OpenMRS and eLMIS. These tools work and they are doing real good. But they were designed to answer questions such as: how many malaria cases were reported this month, how many vaccines were administered.
Chronic disease asks a different set of questions. How many people in this district have been living with undiagnosed hypertension for five years. Which communities are seeing a rise in diabetes, and why. Which patients are at highest risk of a cardiovascular event in the coming year. These are longitudinal, predictive, population level questions, and most health systems on the continent cannot currently answer them.
Where AI genuinely helps, and where it does not
I want to be precise about this. AI is not a solution to underfunded systems, understaffed facilities or fragmented data. Those are structural problems that require political will and sustained investment. But for teams that already hold data, and many do, it can make visible what is currently invisible.
Automated data quality checks are the clearest case. One of the largest barriers to NCD surveillance is unusable data: missing values, inconsistent coding, duplicate records. Models can scan datasets continuously and flag anomalies in minutes rather than weeks. Pattern detection across populations can surface geographic clusters of chronic disease risk early enough to act. Decision support can help an overstretched clinician prioritise, based on indicators already being collected. And automated drafting of routine reports gives programme managers back the hours they currently lose to them.
The hard part is context
After years of implementing digital systems across the continent, my conclusion is that the technology is rarely the problem. A model trained on data from the United States or Europe may perform poorly, or mislead, when applied to a community health post in rural Senegal. Prevalence, demographics, collection practices and care seeking behaviour are all different. Models have to be validated locally, teams have to understand their limits, and implementation has to be designed with the people who will use the tools.
This is also why data sovereignty cannot be reduced to where a server sits. A solution hosted in a national data centre does not make a country sovereign. What does is tools suited to the context and people able to carry a project into operations.
What needs to happen
Funders and ministries need to invest in NCD data infrastructure with the seriousness they applied to HIV and malaria systems. The tools exist. AI adoption has to be preceded by AI literacy: too many well funded technology projects fail because the teams meant to use them were never genuinely consulted or trained. Capacity building is not a line item, it is the work itself. And the solutions have to be built by people with local knowledge. Africa does not need imported algorithms with new branding.
Marie Ba Lacouture is the founder of Insight Santé, a health information systems consultancy based in Dakar, Senegal.