Mosquito-borne diseases are a major challenge for human health, affecting 700 million people every year and resulting in over one million deaths. In animals, mosquitoes also transmit a number of diseases that have major effects on animal health and welfare, and cause significant economic losses. The burden of disease attributable to malaria in sub-Saharan Africa alone, has stalled and elimination is threatened by the rise of vector resistance to pyrethroids using in IRS and LLINs. There is a need for additional interventions, including novel vector surveillance and control tools to further reduce the burden of malaria, and other vector-borne diseases, towards elimination. Reliable information on population and fine-scale spatial distribution of key vector mosquito species is of major importance for surveillance and implementation of appropriate control methods and development of eco-epidemiologic models. Current mosquito monitoring methods rely heavily on traps and are hindered by laborious procedures where each insect has to be counted and identified by hand, or by PCR which is expensive.
Recent advances in communications technologies offer a unique opportunity for exploitation in vector-borne disease surveillance. Combined with our understanding of mosquito wing beat patterns and frequencies, an automated method of detecting mosquitoes through a microphone could be a reality. Mosquito wing beat patterns have been shown to differ significantly between species and, therefore, could be used to identify mosquito species and sex (which is important for surveillance). They could also be used further to determine whether mosquitoes are infected with a pathogen or resistant to insecticides, but this has never been investigated. Fundamental mosquito behavioural and computational studies are needed before sound can be used as a reliable predictor for identification of mosquitoes in practice.
This is a unique and exciting studentship, bringing together several disciplines, with opportunities to gain experience in academic research and industry in the UK and overseas in a developing country.
The project will investigate the wing beat patterns of mosquitoes of medical and veterinary importance to determine whether species, sex, resistance status and malaria infection status can be detected. The studentship will be a collaborative project, supported by the London School of Hygiene and Tropical Medicine, the Royal veterinary College and Rentokil Initial plc.
The objectives of the project are to: 1. Investigate mosquito flight patterns and wing kinematic patterns of three different mosquito species (Anopheles gambiae, Culex quinquefasciatus and Aedes aegypti), in olfactometer behavioural and electrophysiology studies, and use image and acoustic processing to determine whether these patterns can be used as predictors to speciate mosquitoes 2. Investigate wing kinematics of a) insecticide susceptible and resistant strains of Anopheles gambiae, and b) malaria-infected or uninfected females to determine whether there are distinct patterns that can be used as a predictor of resistance and infection status 3. Develop a detection system, incorporating miniature microphone technology, and an algorithm that can be used to detect specific wing beat patterns 4. Design and build a prototype trap using a lure (during a placement with Rentokil), containing a prototype detection device and algorithm that can be trialled with mosquitoes in small-scale behavioural olfactometer assays, followed by larger scale free flight rooms at LSHTM 5. Test the new surveillance trap and detection device prototype in a small scale pilot field trial in Kenya (at an operational Rentokil site), and compare with conventional trapping and identification methods
This project will provide a greater understanding of mosquito behaviour, evolution and speciation. The novel fundamental research on understanding the fundamental biomechanics of mosquito flight is likely to be of high impact could lead to the development of a trapping system that would allow automated and real-time surveillance of vector populations. In the longer term, it could provide a fully automated operational system to detect mosquito vectors via microphones located on several devices including mobile phones, smart watches, mosquito traps, the entrances of houses and dedicated monitoring stations positioned strategically within at-risk communities. Such a system could completely revolutionise our approach to the elimination of vector-borne diseases.
Applications must be complete, including both references, by 11th January 2019 at 5pm
Fully funded place including home (UK) tuition fees and a tax-free stipend in the region of £16,553. Students from the EU are welcome to submit an application for funding, any offers will be subject to BBSRC approval and criteria.