This project seeks support to develop a new laser-based methodology to monitor mosquitoes acting as vectors for infectious diseases. For diseases with no effective cure, such as Dengue and Zika fever, vector control remains the most effective way to protect human populations. However, the spatial distribution of mosquito species is currently tedious to monitor as it relies mostly on unpractical physical traps. Lack of reliable data on the spatial distribution and population dynamics of key mosquito species has become a major obstacle to the development of predictive spatial models for risk of exposure to key vectors. The proposed research goal is to develop and test in laboratory a dual-wavelength polarization sensitive lidar system to count and identify in real-time the species and gender of flying mosquitoes over large range (> 100 m) directly in their natural habitat.
Aim 1 is to test the capability of this novel methodology to retrieve optical properties and wing beat frequency of flying mosquitoes transiting through the laser beam in a controlled environment. Measurements in the near infrared (NIR) and short-wave infrared (SWIR) spectral range will be carried out over a distance of 5 to 10 meters on 4 mosquito species related to infectious diseases. We hypothesize that the light backscattering coefficients and light depolarization ratios of the insect?s body and wings can be remotely retrieved as well as the wing beat frequency, which is supported by our preliminary results.
Aim 2 is to define whether the retrieved information can be used as a unique signature to identify the mosquito species and sex-group. Wing beat frequency has been demonstrated in previous studies as an effective mean to identify the insect family and gender for mosquitoes, also confirmed by our preliminary results. We hypothesize that individuals from a same species will present relatively similar optical properties when compared to individuals from another species. Body and wing colors, degree of melanization and roughness vary from a species to another. Therefore, we expect to observe differences when measuring optical properties from different species. Detection limits and sensibility of the laboratory setup will be evaluated in light of aim 1 and 2 outcomes and compared with our existing numerical model. Upon completion, this project will have validated a new methodology to monitor in real time mosquitoes transmitting infectious diseases with a potential to transform our ability to collect data on infectious disease vectors. With global warming changing their possible habitat, this methodology allows much faster detection of key insect species, identifying thousands of mosquitoes in a few hours compared to weeks with current techniques. The instrument will be used to improve the effectiveness of vector control strategy from public authorities, as well as studying the impact of new and existing mosquito control methodologies (biocontrol, pesticides, trapping). The results of this feasibility study will provide strong preliminary data to guide the design of a larger system for actual field measurements that will be proposed to the R21 program.
Mosquito-borne diseases are a major challenge for Human health as they affect nearly 700 million people every year and result in over one million deaths; however, lack of reliable data on the spatial distribution and population dynamics of key mosquito species has become a major obstacle to the development of predictive spatial models for risk of exposure to key vectors. The propose study will develop and test a new methodology based on applied optics (Lidar) to remotely count and identify in real-time the species, sex group and position of flying mosquitoes in their natural habitat. The results of this feasibility study will provide strong preliminary data to guide the design of a larger system for actual field measurements.
| Genoud, Adrien P; Basistyy, Roman; Williams, Gregory M et al. (2018) Optical remote sensing for monitoring flying mosquitoes, gender identification and discussion on species identification. Appl Phys B 124: |
