Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis

Abstract Background The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Human Blood Index (HBI), currently requires e...

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Bibliographic Details
Main Authors: Emmanuel P. Mwanga, Salum A. Mapua, Doreen J. Siria, Halfan S. Ngowo, Francis Nangacha, Joseph Mgando, Francesco Baldini, Mario González Jiménez, Heather M. Ferguson, Klaas Wynne, Prashanth Selvaraj, Simon A. Babayan, Fredros O. Okumu
Format: Article
Language:English
Published: BMC 2019-05-01
Series:Malaria Journal
Subjects:
Mid-infrared spectroscopy
Supervised machine learning
Malaria
Anopheles arabiensis
Mosquito blood meals
Ifakara
Online Access:http://link.springer.com/article/10.1186/s12936-019-2822-y

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