Across Africa, the effects of climate change are already evident in hospitals and clinics. Shifting rainfall patterns and rising temperatures are increasing deaths from malaria, diarrheal diseases, and respiratory illnesses. Malaria affected an estimated 263 million people in 2023, with Sub-Saharan Africa accounting for 94 percent of cases. Diarrhoeal diseases, also shaped by rainfall and temperature, cause 1.7 billion childhood infections and more than 440,000 child deaths each year.

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Behind these figures lies a challenge of coordination, not capacity: the continent already holds the pieces of the puzzle; health data, climate records, and local expertise. The task now is to fit them together quickly enough to turn warning signs into prevention.

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That opportunity is already being pursued through collaborations such as the Standards for Official Statistics on Climate–Health Interactions (SOSCHI), which support governments and researchers in turning existing data into shared intelligence that guides earlier, more targeted action.

From fragmented data to climate–health intelligence

In Rwanda’s Eastern Province, Kamaliza, a community health worker, prepares for what she calls "the season of fever.” When the rains come, mosquito breeding sites multiply, and she watches malaria and diarrhoeal cases climb. Her handwritten records capture the trend long before it appears in national databases.

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Across the continent, meteorological agencies and health systems collect valuable information, but rarely together. It is like having two halves of the same map. One showing the weather, the other showing disease but never overlaying them. Without connection, early signals stay hidden, and response efforts arrive too late.

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The challenge is not a lack of information but a lack of integration: data that can move quickly enough to become intelligence. Initiatives such as SOSCHI are testing how this can be done, aligning climate and health data, creating comparable indicators, and turning scattered observations into actionable knowledge.

Rwanda’s experience and a web of collaboration

Inside the National Institute of Statistics of Rwanda (NISR), analysts are linking rainfall and temperature records with hospital data on malaria, diarrhoea, and air pollution. Their goal is to see how patterns overlap and how that understanding can strengthen early warning systems.

This effort is part of a South–South partnership between the African Institute for Mathematical Sciences (AIMS) Research and Innovation Centre in Rwanda and the Regional Institute for Population Studies (RIPS) at the University of Ghana. By sharing expertise and data practices, they are developing tools that reflect Africa’s realities rather than importing models that overlook them.

From data gaps to everyday governance

For climate–health statistics to have meaning, they must shape everyday governance. In Rwanda, SOSCHI’s work is being integrated into NISR’s Standard Operating Procedures and the National Strategy for the Development of Statistics. The goal is not another report, but a routine: evidence that informs national planning and budgeting.

This approach also speaks to other contexts. In Angola, where Carlos, a nurse in Huambo, sees diarrhoeal cases surge after floods contaminate wells, timely data could help local authorities deploy sanitation teams before outbreaks spread. The same principle applies in Sudan, where Mohamed, a district health officer, watches malaria rise after flooding along the Nile. Their experiences highlight why systems must connect climate forecasts and health surveillance not later, but now.

Embedding these links into governance is patient work. It requires ministries that rarely share data to collaborate and statisticians and clinicians to interpret evidence together. Yet that is how transformation happens: when information becomes infrastructure.

When data moves at the speed of need

Once systems connect, data can travel as fast as the threats they track. A surge in rainfall can signal a malaria risk before clinics overflow. Rising air pollution can alert hospitals to prepare for respiratory cases. A heatwave forecast can guide local authorities to protect vulnerable groups.

This is what integrated climate–health intelligence looks like: information that enables action before a crisis. It allows governments to move from reaction to preparation and regional bodies to coordinate responses on shared evidence. The value lies not in producing indicators for their own sake, but in changing the rhythm of response from emergency relief to prevention.

A continental and collective responsibility

Africa’s climate–health challenge knows no borders. Creating a shared statistical language allows countries to see regional patterns such as malaria after floods, diarrhoea after drought, respiratory illness after wildfires and respond collectively.

In Mali, for instance, Aïssata, a nurse-midwife in Sikasso, monitors dehydration and infections among mothers and newborns during long dry spells. Her data, when connected with environmental information, could help national planners anticipate and mitigate such risks. Linking experiences like hers across countries is what will turn isolated observations into continental learning.

The partnerships behind SOSCHI—African, European, and global—show what this looks like in practice. They are building a common evidence base that belongs to everyone: a public good that improves planning, saves resources, and, most importantly, protects lives.

Counting what truly matters

When the next rains arrive, Kamaliza in Rwanda, Carlos in Angola, Mohamed in Sudan, and Aïssata in Mali will continue their daily work observing, recording, caring. The difference is that their observations can increasingly connect to wider systems capable of turning them into early action.

By learning to count what truly matters, Africa and its partners are proving that collaboration South to South and North to South can turn data into protection and evidence into care. In the face of a changing climate, that is not only scientific progress; it is social progress.

Note: The health workers named in this article are fictional, but their experiences reflect real challenges across Africa.

Dr. Dzakpa is a researcher at the African Institute for Mathematical Sciences (AIMS) Research and Innovation Centre in Rwanda, focusing on climate–health data systems. His work bridges statistics, health, and policy to advance data-driven resilience across the continent.