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Detection of Plasmodium falciparum infected Anopheles gambiae using near‑infrared spectroscopy

Maia, M. F. and Kapulu, M. and Muthui, M. and Wagah, M. G. and Ferguson, H. M. and Dowell, F. E. and Baldini, F. and Cartwright, L. R.. (2019) Detection of Plasmodium falciparum infected Anopheles gambiae using near‑infrared spectroscopy. Malaria journal, 18. p. 85.

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Abstract

BACKGROUND: Large-scale surveillance of mosquito populations is crucial to assess the intensity of vector-borne disease transmission and the impact of control interventions. However, there is a lack of accurate, cost-effective and high-throughput tools for mass-screening of vectors. METHODS: A total of 750 Anopheles gambiae (Keele strain) mosquitoes were fed Plasmodium falciparum NF54 gametocytes through standard membrane feeding assay (SMFA) and afterwards maintained in insectary conditions to allow for oocyst (8 days) and sporozoite development (14 days). Thereupon, each mosquito was scanned using near infra-red spectroscopy (NIRS) and processed by quantitative polymerase chain reaction (qPCR) to determine the presence of infection and infection load. The spectra collected were randomly assigned to either a training dataset, used to develop calibrations for predicting oocyst- or sporozoite-infection through partial least square regressions (PLS); or to a test dataset, used for validating the calibration's prediction accuracy. RESULTS: NIRS detected oocyst- and sporozoite-stage P. falciparum infections with 88% and 95% accuracy, respectively. This study demonstrates proof-of-concept that NIRS is capable of rapidly identifying laboratory strains of human malaria infection in African mosquito vectors. CONCLUSIONS: Accurate, low-cost, reagent-free screening of mosquito populations enabled by NIRS could revolutionize surveillance and elimination strategies for the most important human malaria parasite in its primary African vector species. Further research is needed to evaluate how the method performs in the field following adjustments in the training datasets to include data from wild-caught infected and uninfected mosquitoes.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Health Interventions > Malaria Interventions (Lengeler)
UniBasel Contributors:Ferreira Maia, Marta
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:BioMed Central
ISSN:1475-2875
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
Identification Number:
Last Modified:01 Apr 2019 09:25
Deposited On:01 Apr 2019 09:25

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