MALIntDrone: A Malaria Intervention Drone for Larval Source Management using Remote Sensing and Multispectral Imagery

Malaria is a life-threatening disease transmitted through bites of infected Anopheles mosquitoes and disproportionately affects marginalized populations. Despite global efforts to eradicate, malaria remains a significant public health challenge, with 249 million cases in 2022, and the geographical expansion of malaria further threatens global health security. Effective control strategies include Larval Source Management (LSM) at breeding grounds to reduce Anopheles larvae, thus reducing adult populations. However, identifying and treating Anopheles larvae habitats by land surveys is difficult and expensive. Project MALIntDrone aims to develop an automated MALaria INTervention system to detect and treat larval habitats. Anopheles larvae thrive near aquatic vegetation; this work utilizes advanced remote sensing techniques to identify Anopheles habitats: the Normalized Difference Water Index (NDWI) with Otsu thresholding and Canny edge filtering for water bodies and Normalized Difference Aquatic Vegetation Index (NDAVI) and Water Adjusted Vegetation Index (WAVI) for aquatic vegetation. MALIntDrone achieved 85% accuracy for detecting Anopheles larvae habitats and 86% for aquatic vegetation sites using ground surveyed data from the Kasungu District, Malawi. To address potential limitations of satellite imagery, an inexpensive multispectral camera was also developed using a dual-camera Raspberry Pi system to provide RGB + Near-IR imagery which is then aligned using Fourier-Based image alignment. This camera can be attached on the drone to be used to create orthomosaics of an area. To treat areas effectively, identified habitats are then targeted using a developed autonomous drone with a precision sprayer system. MALIntDrone’s multidisciplinary approach has the potential to impact the health of millions worldwide as it is easy to use and efficient. It can be critical in aiding WHO’s goal of Malaria eradication by 2030.