Key Takeaways
- Malaria remains a major public‑health burden in sub‑Saharan Africa, causing ~282 million cases and ~610,000 deaths in 2024, with children under five and pregnant women most affected.
- Traditional indoor‑focused interventions (bed nets, indoor spraying) have reduced transmission but are insufficient to eliminate the disease because many mosquitoes breed and bite outdoors.
- Dr Andy Hardy’s team at Aberystwyth University is using drones equipped with near‑infrared and thermal sensors, satellite imagery, and artificial intelligence to locate hidden mosquito‑breeding water bodies at scale.
- The technology enables rapid, precise mapping of habitats that would otherwise require weeks of ground surveys, allowing timely larval‑source management.
- The project builds on years of remote‑sensing research, integrates local community training, and aims to produce an open‑source toolkit (digital dashboard, smartphone app, AI models) that can be adapted across malaria‑endemic regions.
- By targeting breeding sites, the approach complements existing control measures, making malaria programmes more targeted, efficient, and sustainable in the face of climate change, urbanisation, and evolving mosquito behaviour.
The Ongoing Global Burden of Malaria
Malaria continues to exact a heavy toll worldwide, with its greatest impact felt across Africa. In 2024 the disease caused an estimated 282 million cases and around 610,000 deaths globally. The burden falls most heavily on the most vulnerable: children under five and pregnant women, with young children accounting for roughly three‑quarters of malaria deaths in Africa. Beyond its devastating human cost, malaria entrenches poverty by reducing productivity, increasing healthcare spending, and placing long‑term strain on families and health systems. Although major investments since 2000 have saved millions of lives and dramatically reduced mortality, progress has slowed, underscoring the need for new, sustained approaches—particularly in sub‑Saharan Africa.
The Stubborn Challenge of Hidden Breeding Sites
For decades, sub‑Saharan Africa has waged a determined battle against malaria, yet a stubborn challenge persists: the mosquito breeding sites that sustain transmission are often small, hidden, scattered, and difficult to identify using ground‑based surveys alone. Conventional larval‑source management relies on teams physically walking through villages, farms, and wetlands to spot standing water—a labor‑intensive process that can miss habitats obscured by vegetation, rice paddies, or seasonal flooding. Consequently, many breeding sites remain undetected, allowing mosquitoes to mature and continue transmitting the parasite despite high coverage of indoor interventions.
Dr Andy Hardy – Thinking Outside the Home
Dr Andy Hardy, Senior Lecturer in Remote Sensing and GIS at Aberystwyth University, is a key figure in malaria control. His work focuses on using drones and remote‑sensing technologies to identify, map, and manage mosquito breeding sites—particularly those beyond the reach of conventional control methods. He explains that in places such as Zanzibar, sustained control efforts over several decades have successfully reduced malaria transmission, but these efforts have largely relied on indoor‑targeted interventions like insecticide‑treated bed nets and indoor residual spraying. To make further progress, we need to think outside the home: many of the mosquitoes that continue to transmit malaria now bite outdoors, beyond the reach of conventional indoor‑targeted interventions. Taking the fight to the mosquitoes themselves—by finding the water bodies where they breed and eliminating larvae before they mature—is essential, and that is where geographers and remote‑sensing experts come in.
A New Way of Seeing: Drones, Satellite, and AI
Dr Hardy’s latest project brings together drones, satellite imagery, and artificial intelligence to address the challenge of detecting breeding habitats at scale. Advanced drones equipped with near‑infrared and thermal sensors will be deployed to detect water bodies—even in complex environments such as rice paddies, swamps, and areas masked by dense aquatic vegetation or grass canopies. Satellite imagery will provide broader environmental context across Zanzibar’s landscape, while artificial intelligence will analyse both drone and satellite data to identify likely mosquito breeding habitats. The insights provided by these combined technologies will enable large‑scale detection of aquatic habitats that would traditionally require weeks of physical surveying, allowing interventions to be implemented earlier and more precisely. Dr Hardy describes the approach as “reinventing mosquito control”—a leap forward in precision, speed, and scale for mapping malaria hotspots.
Building on Years of Research and Community Involvement
Dr Hardy’s expertise draws on a long track record of applying remote‑sensing technologies—from satellites to crewed aircraft to drones—to map landscapes and ecological risks. His previous research included hydrological flood modelling to identify malaria habitats in Zambia, and early proof‑of‑concept projects using drones and smartphone technology to support malaria habitat mapping in Zanzibar. These projects have helped refine the methods and tools now being deployed. Crucially, the current initiative integrates technological innovation with community‑centred approaches. Local teams in Zanzibar will be trained to use the digital mapping tools, recognise larval habitats, and carry out larval‑source management. This means that this technology‑led approach is owned and operated locally, without reliance on outside support, supporting long‑term sustainability.
A Blueprint for Africa and Beyond
Using Zanzibar as a testbed, the project aims to create a toolkit that can be used in malaria‑affected regions worldwide. This will include a central digital dashboard for planning surveillance and treatment, a smartphone app to support field teams in mapping and spraying, and open‑source AI models for identifying aquatic mosquito habitats. As climate change, urbanisation, and evolving mosquito behaviours complicate malaria elimination efforts, these flexible, data‑driven approaches are becoming increasingly important. The ability to scan large landscapes at relatively low cost and pinpoint hidden breeding sites is a powerful new tool for programmes that are aiming to tackle malaria under pressure. By making the toolkit openly available, the project seeks to lower barriers for other endemic countries to adopt similar strategies.
A More Targeted Future for Malaria Control
Rather than replacing existing efforts to stamp out the disease, Dr Hardy’s work is designed to strengthen them—by developing new ways to generate the intelligence needed to deploy resources where they may have the greatest impact. By combining local expertise with drone technology, satellite data, and artificial intelligence, the project explores how malaria control could become more targeted, efficient, and sustainable. As Zanzibar moves closer to its elimination goals, this approach has the potential to inform future strategies in other regions facing similar challenges—one that focuses not only on protecting people from mosquitoes, but on disrupting transmission at its source. In an era where traditional methods alone are insufficient, integrating high‑resolution remote sensing with grassroots action offers a promising pathway toward malaria elimination across Africa and beyond.