Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex

Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex

Abstract Background Mosquito-borne diseases, such as malaria, dengue, and Zika, continue to pose significant threats to global health, resulting in millions of cases and thousands of deaths each year. Notably, only older mosquitoes can transmit these diseases. Therefore, accurate age estimation of m...

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Main Authors: Zili Gao, Yuzhen Zhang, Laura C. Harrington, Courtney C. Murdock, Elisabeth Martin, Dalton Manbeck-Mosig, Steve Vetrone, Nicolas Tremblay, Christopher M. Barker, John M. Clark, Lili He, Wei Zhu
Format: Article
Language:English
Published: BMC 2025-06-01
Series:Parasites & Vectors
Subjects:
Mosquito classification
Age prediction
Surface-enhanced Raman spectroscopy
Artificial neural networks
Online Access:https://doi.org/10.1186/s13071-025-06831-x
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https://doi.org/10.1186/s13071-025-06831-x

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