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Rapid age-grading and species identification of natural mosquitoes for malaria surveillance.

Siria, Doreen J, Sanou, Roger, Mitton, Joshua, Mwanga, Emmanuel P, Niang, Abdoulaye, Sare, Issiaka, Johnson, Paul C D, Foster, Geraldine ORCID:, Belem, Adrien M G, Wynne, Klaas, Murray-Smith, Roderick, Ferguson, Heather M, González-Jiménez, Mario, Babayan, Simon A, Diabaté, Abdoulaye, Okumu, Fredros O and Baldini, Francesco (2022) 'Rapid age-grading and species identification of natural mosquitoes for malaria surveillance.'. Nature Communications, Vol 13, Issue 1, p. 1501.

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The malaria parasite, which is transmitted by several Anopheles mosquito species, requires more time to reach its human-transmissible stage than the average lifespan of mosquito vectors. Monitoring the species-specific age structure of mosquito populations is critical to evaluating the impact of vector control interventions on malaria risk. We present a rapid, cost-effective surveillance method based on deep learning of mid-infrared spectra of mosquito cuticle that simultaneously identifies the species and age class of three main malaria vectors in natural populations. Using spectra from over 40, 000 ecologically and genetically diverse An. gambiae, An. arabiensis, and An. coluzzii females, we develop a deep transfer learning model that learns and predicts the age of new wild populations in Tanzania and Burkina Faso with minimal sampling effort. Additionally, the model is able to detect the impact of simulated control interventions on mosquito populations, measured as a shift in their age structures. In the future, we anticipate our method can be applied to other arthropod vector-borne diseases.

Item Type: Article
Subjects: QX Parasitology > QX 15 Classification. Terminology
QX Parasitology > Insects. Other Parasites > QX 510 Mosquitoes
QX Parasitology > Insects. Other Parasites > QX 515 Anopheles
QX Parasitology > Insects. Other Parasites > QX 650 Insect vectors
WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria
Faculty: Department: Biological Sciences > Vector Biology Department
Digital Object Identifer (DOI):
SWORD Depositor: JISC Pubrouter
Depositing User: JISC Pubrouter
Date Deposited: 21 Jul 2022 10:34
Last Modified: 15 Jun 2023 13:36


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