Malaria is one of the deadliest yet preventable diseases in the world. In 2024, it was estimated to claim about 610,000 lives, according to the World Health Organization. Africa bears the brunt of this burden, accounting for 95% of global cases and deaths. Children under five are especially affected, with roughly one child dying every minute. The disease is estimated to cost Africa around US$12 billion per year in lost GDP.
Malaria is caused by Plasmodium parasites that are spread through the bites of infected Anopheles mosquitoes. It poses a serious threat to lives but is also preventable. Despite this, it continues to hurt communities across sub-Saharan Africa, especially in the Sahel region. In this region, climate shocks, mass displacement, and the disruption of conflict have made an already formidable disease harder than ever to fight.
A study published in Nature warns that climate change could significantly worsen the situation, resulting in 123 million additional malaria cases and up to half a million more deaths in Africa. Rising temperatures, extreme weather events, and shifting rainfall patterns are expected to disrupt treatment programmes and increase transmission risks, especially in already vulnerable regions.
World Malaria Day, observed on April 25, highlights the global fight to end a preventable yet deadly mosquito-borne disease. It also serves as a reminder that malaria remains a serious challenge in many countries. Under the theme ‘Driven to End Malaria: Now We Can. Now We Must‘, the global health community is being called not only to acknowledge progress, but to act with far greater urgency to protect it. The United Nations has set a target to end malaria epidemics by 2030 under Sustainable Development Goal 3.3. That goal remains within reach – but only just.
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Progress is also being made in eliminating malaria.
Globally, an estimated 2.3 billion malaria cases and 14 million malaria deaths have been averted since 2000. There has been continued movement towards global elimination goals, with 47 countries and one territory now officially certified as malaria-free by WHO. Cabo Verde and Egypt were certified malaria-free in 2024.
However, persistent challenges like insecticide resistance, climate-driven transmission shifts, and funding gaps threaten to stall this momentum.
Yet even as these challenges grow, new tools are reshaping what is possible. A new generation of tools is reshaping what is possible in the fight against malaria. AI-powered surveillance systems are tracking mosquito populations in near-real time. Digital reporting platforms are closing the data gaps that allow outbreaks to go undetected. And malaria vaccines, long considered a distant prospect, are now reaching children under five across the region.
In an interview, Dr Ngozi Erondu, Technical Director at the Global Institute for Disease Elimination, shares insights on how these breakthroughs can be translated into lasting protection for the most at-risk communities, particularly young children in the Sahel.
Drawing on your extensive malaria research, how would you describe the current malaria status in SSA, and what does a realistic path to reduction of prevalence and elimination look like for the region?
I would say the current malaria situation in sub-Saharan Africa is concerning. To be in 2026 and see the global malaria burden starting to rise again is frustrating. Yes, there has been progress over time, but when we look at cases and deaths, the trend is moving in the wrong direction. According to the World Malaria Report 2025, there were an estimated 608,000 deaths in 2024, up from 597,000 in 2023, and around 282 million cases, compared to 263 million the year before. Sub-Saharan Africa still accounts for roughly 95% of cases and deaths globally, and about three-quarters of malaria deaths are among children under five. That alone should give us pause.
I think these setbacks reflect a combination of pressures. Funding has plateaued at a time when needs are increasing. At the same time, we are seeing the gradual loss of efficacy of key tools – both artemisinin-based combination therapies (ACTs) and insecticides – because mosquitoes and malaria-causing parasites are becoming less sensitive to these chemicals over time. Add to that population growth, climate variability, and health systems that are still uneven in their ability to detect and respond, and it becomes clearer why progress is stalling.
What this points to, for me, is that the current approach is not fully keeping pace with the complexity of transmission, but that does not mean we are without options. There are some genuinely promising developments: new antimalarial medicines designed to address emerging resistance, breakthrough malaria vaccines to boost protection for children under five, and a growing pipeline of next-generation vector control tools that are showing encouraging results in trials. The issue is less about the absence of innovation and more about whether we are investing early and consistently enough to bring these tools to scale.
So alongside strengthening surveillance systems and improving cross-border coordination, we need to be more deliberate about backing these innovations through financing, evidence generation, and country-led implementation. If we get that right, there is still a real opportunity to regain momentum rather than accept stagnation as the norm.
How can stronger cross‑border data integration help countries better anticipate and manage seasonal malaria surges?
Malaria-spreading mosquitoes thrive wherever the weather is warm and wet. They are not concerned with maps or country borders. So when health leaders make decisions using isolated national datasets, we can miss important signals about how the disease is spreading, including shifts in transmission trends, patterns of importation, and border-area hotspots. That is especially important because many of the forces shaping malaria risk, including human mobility, climate variability, and vector dynamics, affect multiple countries at the same time. For that reason, efforts to collect, coordinate, and use data to predict malaria risk and guide outbreak response need to happen not only within countries, but across them.
GLIDE has long supported cross-border malaria initiatives, including the Sahel Malaria Elimination Initiative (SaME). The initiative established a regional platform bringing together eight Sahel countries to coordinate efforts toward malaria elimination by 2030, while strengthening the monitoring of subregional trends and policy implementation. At its core, SaME reflects the reality that malaria transmission does not respect borders, and progress depends on how well countries align their approaches. Beyond coordination, these types of cross-border platforms enable more practical functions: sharing epidemiological data, strengthening joint surveillance, and supporting coordinated responses in border areas where transmission is often highest and most difficult to control. Through partnerships with institutions such as the West African Health Organization and the Africa Leaders Malaria Alliance, SaME has also supported the development of scorecards for malaria and other neglected tropical diseases (NTDs). These tools help standardize data, track progress across countries, and strengthen accountability for results at both national and regional levels.
Many researchers have also argued for a stronger regional and subregional surveillance architecture across Africa, particularly with regard to integrated malaria molecular surveillance (iMMS). A recent analysis makes the case that linking routine epidemiological surveillance with genomic and molecular data can help countries detect and respond to antimalarial drug resistance and other emerging threats. Africa CDC has likewise called for stronger cross-border surveillance, coordination, and information sharing among Member States, and its malaria genomic surveillance roadmap explicitly refers to regional hubs and centres of excellence as part of a continent-wide approach.
I think that if such systems were more fully in place, they could have a real impact by allowing neighbouring countries to track resistance patterns earlier, compare trends across transmission zones, and align prevention and treatment strategies more effectively. In practice, that could help countries better target interventions such as seasonal malaria chemoprevention and adjust first-line antimalarial policies based on more timely evidence.
AI‑based mosquito identification tools are emerging as powerful aids for entomologists; can you explain what they are and how they are being used to complement existing tools. What is needed to accelerate their adoption across the African region?
I am quite excited about the use of AI for very practical, targeted needs in malaria control, particularly as a complementary tool for entomology. One of the less visible challenges in malaria programmes is something quite basic: identifying which mosquito species are present. This is not straightforward work. Mosquitoes are collected in the field, sorted, and then examined under a microscope using identification guides that rely on small differences in their physical features. Some of the most important malaria vectors look almost identical, so even experienced entomologists can only identify them to a group level without additional laboratory testing, such as PCR. All of this takes time, training, and access to specialised expertise – which is in short supply in many settings. This is further compounded by a persistent shortage of trained entomologists across many malaria-endemic settings, limiting both the speed and scale of surveillance.
AI-based tools are starting to help with this bottleneck. Using image recognition or even sound, these systems can identify mosquito species from a photograph or recording taken in the field. For example, a study in South Korea showed that AI-powered programs could accurately identify disease-transmitting mosquitoes under controlled conditions. Similar work in the United States and Europe has shown strong performance using both image-based and acoustic (wingbeat) data. Importantly, these tools can produce results in seconds. In practical terms, that means frontline workers can process more samples, more quickly, and share results in near real time. Tools like VectorCam, which has been piloted in Uganda, are designed to allow non-specialists to capture images of mosquitoes and automatically classify them, helping to reduce delays and expand surveillance coverage.
To scale these tools across Africa, the challenge is less about the technology itself and more about the enabling conditions. The systems need to be trained on local data so they can accurately recognise African mosquito species. They need to be integrated into national surveillance systems, rather than used as stand-alone pilots. And they require investment both in the tools themselves and in the people and systems that will use them. If those pieces are in place, AI has real potential to strengthen entomology capacity not by replacing experts, but by extending their reach and making surveillance faster and more actionable.
In the last two years, six countries in the Sahel region have introduced malaria vaccines. What have these early rollouts revealed about health system readiness to adopt and deploy new cost-effective tools? How might Mali’s vaccine delivery model inform approaches in other conflict‑affected or high‑burden settings?
I think the early rollout of malaria vaccines across the Sahel has shown us two things at the same time. On the one hand, countries can move quickly to adopt new tools. On the other hand, it has really highlighted that health system readiness is uneven.
Where routine immunisation systems are strong, uptake has been good, and countries have been able to introduce the vaccine without disrupting other services. We saw that clearly with the introduction of the RTS,S vaccine in places like Ghana, Kenya, and Malawi. Early data on subnational rollout have been promising. For example, the Ghana Health Service recorded an 86% reduction in malaria deaths in children under 5, compared to the year before the vaccine was introduced. That impact, in part, is due to the close coordination between leaders in Ghana’s Expanded Programme on Immunisation and its National Malaria Control Programme.
But the rollout has also exposed some persistent gaps. Reaching children in remote or insecure areas is still difficult, and because this is a multi-dose vaccine, you do see drop-off between doses. There is also more to do on community engagement to make sure families understand the schedule and come back.
Mali is an interesting example. They came in later, introducing the R21/Matrix-M vaccine in April 2025, so they were able to learn from what had already happened elsewhere. What stands out is how they adapted delivery to deal with the drop-off issue. The first three doses are given through routine immunisation, but then the booster doses are delivered alongside seasonal malaria chemoprevention (SMC) campaigns, so during the months that have the highest malaria transmission. This approach is practical and effective because those campaigns are already reaching children during the highest risk period.
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For me, the takeaway is simple, and it can be translated to more difficult settings. It is not just about introducing a new tool; it is about how you deliver it as part of a package of interventions and plan for continued access. Countries that build on existing systems, such as routine immunisation or seasonal campaigns, tend to do better – meaning more children are protected by the best available tools. And with recent reductions in the list prices for both vaccines, this approach to comprehensive malaria prevention is becoming more cost-effective, at a time when it is absolutely imperative to make smart choices with limited financing. But delivering those tools at scale still requires governments and partners to continue investing in health systems, in health workers, and in community engagement. Otherwise, even the best tools will not reach the people who need them most.
As countries scale up digital platforms such as the WHO’s DHIS2 malaria modules, how can technical partners, industry and funders support governments in strengthening and sustaining surveillance systems? What complementary approaches are needed to improve data quality and ensure that real‑time insights guide planning in high‑burden areas?
I think it is good that there is a lot of enthusiasm right now, around supporting malaria-endemic countries to use tools like AI, especially from partners in higher-income countries. But I would be quite clear that AI is just a tool. If poor-quality data goes in, then poor information for decision-making will come out. So, the real issue is not just about introducing more advanced tools; it is about strengthening the underlying systems that generate the data in the first place.
We have made progress with platforms like DHIS2, which are now widely used at the district level across many countries. But the reality is that data quality challenges sit below that level, at the point where patient data is first recorded. That is where there is still a lot of variability, and where errors, delays, and gaps are introduced. So there is a real opportunity for partners to support more complete and sustainable digitisation at the frontline, better tools for health workers, and stronger systems for data capture and validation.
Finally, I think we need to move away from supporting only disease-specific approaches. Surveillance systems should be integrated, because that is how health systems actually function. And importantly, all of this has to be designed with sustainability in mind. It is not about pilots or short-term innovation; it is about building systems that countries can maintain, use, and rely on over time. That also means working with countries to strengthen primary healthcare systems that can increasingly finance and sustain themselves. Development funding is critical right now, but it should not be a forever solution. We should be supporting a transition toward more durable, country-owned systems.