A "holy grail" method of quickly and cheaply identifying the ageing mosquitoes that cause malaria has been developed.
Scientists at the University of Glasgow, UK, and partner institutes have revealed the method in the latest edition of Nature Communications. They describe it as a “step change” in ability to accurately identify the age and species of malaria mosquitoes in wild populations.
The team, led by University of Glasgow-Institute of Biodiversity Animal Health and Comparative Medicine (IBAHCM) and School of Chemistry and also including the Ifakara Health Instititute (IHI) in Tanzania and the Institut de Recherche en Sciences de la Santé (IRSS) in Burkina Faso, used infrared spectroscopy and artificial intelligence (AI).
They were able to quickly identify the chemical changes of ageing mosquitoes using an AI algorithm and validate their age predictions on wild mosquitoes by shining infrared light on individual insects.
The study used a large dataset of 40,000 genetically and ecologically different individual mosquitoes from East and West Africa and it measured mid-infrared spectroscopy signatures, reflecting the biochemical signatures of each of these mosquitoes. It also used AI to correctly identify both age and species of new mosquitoes.
The AI-driven infrared light technology requires a spectrometer, which costs about $20,000 and can be used as part of existing, routine malaria vector surveillance, said lead author Roger Sanou, of IRSS. He added that it provides a quick way to establish if intervention measures to reduce mosquito numbers in the wild are working.
Lead author Mrs Doreen Siria, from IHI, said: “Only mosquitoes that live long enough to develop malaria – around 10 days – can transmit the disease, so knowing the age of a mosquito can help inform the risk of disease.
“Until now, the only way to know the age of a mosquito was via complex dissection to gauge the age of female mosquitoes’ ovaries, a process which is expensive, time-consuming and can’t be done at scale.”
Dr Francesco Baldini, from the IBAHCM, added: “We believe this new method is greatly needed in the fight against malaria. While there are vector controls in place across the globe in areas of high mosquito populations, it’s difficult to measure whether these controls are working effectively.
“With this infrared technology, we have developed a tool which could be adopted within current mosquito control plans; has the potential to be scaled up for use across different areas; and would greatly help in testing new products and solutions against diseases transmitted by mosquitoes.”
The computer models can be adapted and implemented in the field for vector surveillance.
Simon Babayan, from the IBAHCM, said: “The versatility of AI combined with the power of infrared spectroscopy opens huge opportunities for disease surveillance and rapid response.”
Siria DJ, Sanou R, Mitton J et al. Rapid age-grading and species identification of natural mosquitoes for malaria surveillance. Nature Communications 21 March 2022
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