What is the name of your organization?
SORA Technology
What is the name of your solution?
SORA Malaria Control
Provide a one-line summary or tagline for your solution.
AI-powered drone system enabling communities to proactively control malaria by identifying mosquito breeding sites with precision
In what city, town, or region is your solution team headquartered?
日本、東京都
In what country is your solution team headquartered?
Japan
What type of organization is your solution team?
For-profit, including B-Corp or similar models
Film your elevator pitch.
What specific problem are you solving?
Malaria remains one of the deadliest diseases globally, with an estimated 249 million cases and 608,000 deaths in 2022—94% of which occurred in Africa. Despite widespread use of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS), transmission persists, especially in peri-urban and rural areas where mosquito breeding sites are difficult to locate and manage. One of the most pressing emerging threats is Anopheles stephensi, an invasive malaria vector originally endemic to Asia that is now spreading rapidly across African cities. Unlike traditional vectors, it thrives in artificial urban water containers, making surveillance and intervention even more complex. Current larval source management (LSM) strategies often fail to detect these cryptic breeding sites due to lack of precise, scalable data. Manual surveys are time-consuming, inconsistent, and impractical over large or flooded areas. Without reliable environmental surveillance tools, governments and health partners are unable to efficiently target resources—wasting larvicide and labor, and risking outbreaks, especially in the aftermath of floods. Our solution addresses this urgent need for smarter, faster, and more adaptive malaria vector surveillance and control.
What is your solution?
SORA Malaria Control is an AI-powered drone surveillance platform that identifies and classifies mosquito breeding habitats with high spatial and ecological accuracy. Using fixed-wing drones, we collect high-resolution aerial imagery across large, often inaccessible areas. These images are analyzed by our proprietary deep learning models, which detect waterbodies and assess their suitability for Anopheles mosquito breeding.
Our AI model has been validated in real-world deployments in Ghana, where it demonstrated over 80% accuracy in both waterbody detection and breeding risk classification, including the ability to distinguish between temporary puddles and stable aquatic habitats preferred by malaria vectors. This accuracy significantly outperforms manual field surveys in both consistency and coverage.
The result is a more focused and cost-effective Larval Source Management (LSM) strategy. Field operations using our system have achieved up to 80% reduction in required labor and a 50% or greater decrease in larvicide use, without compromising impact. We are also collaborating with Gavi, the Vaccine Alliance, to apply this technology to flood-induced outbreak forecasting, enabling proactive immunization planning and integrated disease prevention strategies. Our platform also connects to the broader SORA Health Intelligence Room for ongoing risk monitoring and multi-hazard response.
Who does your solution serve, and in what ways will the solution impact their lives?
SORA Malaria Control serves health authorities, malaria program teams, and communities in malaria-endemic regions—especially in sub-Saharan Africa—by strengthening their ability to implement proactive, data-driven vector control. Our primary beneficiaries are families and children in high-risk areas, as well as public health officers who often work with limited resources across vast or flood-prone regions.
In Ghana and Sierra Leone, our solution has already helped local actors plan and execute more efficient Larval Source Management campaigns. We are working with the Japan International Cooperation Agency (JICA) to support field implementation and training. With the Gates Foundation, we are aligning our technology with global strategies for innovation in malaria control. In Nairobi, we are piloting the platform through a joint initiative between the Tokyo Metropolitan Government and Nairobi City County Government to integrate vector control with flood and disease risk management.
Our collaboration with Gavi, the Vaccine Alliance, is expanding the platform’s reach to include outbreak forecasting triggered by extreme weather, helping optimize vaccine preparedness. Across these settings, SORA Malaria Control is not only reducing malaria burden but also enhancing local capacity for surveillance, planning, and sustainable disease prevention.
