Motivation

Pathogens transmitted by mosquitoes cause over one million deaths each year. Low-middle income countries (LMIC) in the tropics disproportionately suffer this burden. With the lack of safe and effective vaccines against many of these pathogens, resource-intensive mosquito control is the sole actionable intervention.

Mosquito habitats are highly heterogeneously distributed, with substantial variation in abundance across a community and over a year. This variability hampers our ability to target mosquitoes effectively, with e.g., insecticides. We urgently need an ability to identify in real time, the presence and abundance of mosquitoes, within any setting, including an ability to identify specific species that could act as a disease vector. Currently public health officials rely on laborious mosquito trapping, which can only realistically be conducted in a small number of locations.

Leveraging wingbeat frequencies signatures of mosquito species, automated sensor-based technologies can offer scalable solutions to monitor species-specific mosquito abundance. This project is designed to fill in critical evidence gaps impeding decisions to adopt the technology as well as generate prototypes of resources to enable real-world implementation of the technology and solidify future directions in developing these prototypes into real-world solutions.

The Team

This project is an interdisciplinary, cross-sector collaboration between:

  • local public health officials at Na MoungPhet Municipality
  • local public health entomologists at VBDCC, Trang,
  • public health academics from SCPH,
  • computer scientists at Mahidhol University, and
  • infectious disease epidemiologists at University of Cambridge.

The Project Team

The Project

Real-world deployment. This project deployed acoustic sensors into common areas of 60 households for 3 days (~72 hours). A mosquito trap was deployed together with the acoustic sensors to lure and capture adult mosquitoes in the house. Every ~24 hours, trapped mosquitoes were retrieved from the catch bags, classified by species, and counted. These trapped counts serves as a benchmark for the mosquito species count detected via the acoustic sensors, acknowledging that mosquitoes may also fly by but not enter the traps.

Controlled recordings. On the sensor installation day, we surveyed containers within and around the houses for mosquito larvae and brought them back to the entomological unit to emerge into adulthood in a cloth cage. Individual mosquitoes were transferred to minicages to obtain 5-minutes of audio recordings of their flights. Species and sex classified by a certified entomologist was documented along with the number of days since their emergence.

Stakeholder engagement. After the conclusion of deployments in all households, the project team held a meeting with residents of the homes to acquire insights from their experience with the technologies. Insights from public health officials were obtained in all phases of the project from co-design, co-delivery, to post-delivery focus meetings.

Fund source

This project was supported by BBSRC Impact Acceleration Account (IAA) awarded to the University of Cambridge under the project titled: Accelerating the adoption of wingbeat-based sensing to quantify mosquito species abundance in the tropics