Project Title: HUMBUG: Developing a mosquito monitoring tool for Least Developed Countries
Project Description: Mosquito surveys are needed to identify the presence and abundance of species that can transmit diseases such as malaria, dengue, zika, and chikungunya. Millions of dollars are spent each year to control both the vectors and their vector-borne diseases and in combination, these have resulted in significant successes in recent years. However, between 2015 and 2018 malaria control was stalled. This is due, in part, to emerging insecticide resistance, behavioral avoidance of insecticide by mosquitoes,... Mosquito surveys are needed to identify the presence and abundance of species that can transmit diseases such as malaria, dengue, zika, and chikungunya. Millions of dollars are spent each year to control both the vectors and their vector-borne diseases and in combination, these have resulted in significant successes in recent years. However, between 2015 and 2018 malaria control was stalled. This is due, in part, to emerging insecticide resistance, behavioral avoidance of insecticide by mosquitoes, and inherent behavioral plasticity amongst some species that keep them out of contact with the mostly indoor-based methods of mosquito control. New mosquito survey methods that provide real-time species-specific occurrence and abundance data could revolutionize the way vector control is implemented, allowing highly effective, timely, and species-specific mosquito control as well as providing red flags where interventions are failing. Over the past four years, a multidisciplinary group at the University of Oxford have developed a novel mosquito survey tool (HumBug) that enables real-time species-specific occurrence and abundance vector data in malaria endemic regions. HumBug transforms a budget smartphone into a sensor that detects and identifies host-seeking mosquitoes using the acoustic signature of their flight tone. It can generate unprecedented levels of urgently high-quality, spatially accurate mosquito occurrence data without incurring any risk to those conducting the surveys. It is low cost, running on budget smartphones or wearable smart devices (using our MozzWear app) as well as low-energy acoustic loggers (Audiomoth). MozzWear records mosquito flight tone, and along with the time and location, sends the data to a central server where the species is identified using a suite of algorithms that distinguish between species according to their acoustic signature.
Principal Investigator : Emanuel Kaindoa
Department Name :
Time frame: (2019-07-01) - (2022-09-30)
Bill and Melinda Gates Foundation (BMGF) (Normal)
External Collaborating Partners
The Chancellor, Masters and Scholars of the University of Oxford