Skip to main content
ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » Stored Product Insect and Engineering Research » Research » Publications at this Location » Publication #332467

Research Project: Impacting Quality through Preservation, Enhancement, and Measurement of Grain and Plant Traits

Location: Stored Product Insect and Engineering Research

Title: Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae

Author
item KRAJACICH, BENJAMIN - Colorado State University
item MEYERS, JACOB - Colorado State University
item ALOUT, HAOUES - Colorado State University
item DABIRE, ROCH - Institut De Recherche En Sciencies De La Sante
item Dowell, Floyd
item FOY, BRIAN - Colorado State University

Submitted to: Parasites & Vectors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/27/2017
Publication Date: 11/7/2017
Publication URL: https://handle.nal.usda.gov/10113/5855275
Citation: Krajacich, B.J., Meyers, J.I., Alout, H., Dabire, R.K., Dowell, F.E., Foy, B.D. 2017. Analysis of near infrared spectra for age-grading of wild populations of Anopheles gambiae. Parasites & Vectors. 10:552. doi: 10.1186/s13071-017-2501-1.
DOI: https://doi.org/10.1186/s13071-017-2501-1

Interpretive Summary: A greater understanding of the age-structure of mosquito populations is important for assessing the risk of infectious mosquitoes, and how control interventions may affect this structure. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes. We developed models using NIRS calibrated to wild mosquitoes reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been collected from villages where a malaria transmission control intervention was being tested. We found that accuracy for predicting <7.5 or >7.5 days of age correctly varied from 67.0-82.5%, and mosquito strains that have been colonized for longer periods tend to have higher predictive ability. Models generated from multiple lab and field sources were stronger, being able to correctly predict wild-caught young mosquitoes as being younger than both middle to old age and old mosquitoes by 1.7 and 3.8 days, respectively. The best model was then tested on mosquitoes collected from 2 villages in Burkina Faso, one of which received mass drug administration (MDA), and it detected 20.8% drop in the mean age of mosquitoes collected from the treatment village the first week post-MDA. With extensive calibration models developed from multiple, locale-matched field locations, this technique can be used to investigate mosquito age structure and determine how it changes in response to mosquito control measures.

Technical Abstract: A greater understanding of the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may affect this structure. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed models using NIRS calibrated to wild An. gambiae s.l. reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites, and that had been collected from villages where a malaria transmission control intervention, ivermectin mass drug administration (MDA), was being tested. We found that intramodel accuracy for predicting <7.5 or >7.5 days of age correctly varied from 67.0-82.5%, and mosquito strains that have been colonized for longer periods tend to have higher predictive ability with cross-validation and validation sets. However, all single-source models, whether calibrated from lab or field samples, failed at accurately predicting the age of wild-caught adult mosquitoes. Models generated from multiple lab and field sources were stronger, being able to correctly predict wild-caught nulliparous (young) mosquitoes as being younger than both parous (middle to old age) and sporozoite positive (old) mosquitoes by 1.7 and 3.8 days, respectively. The best multi-source model was then tested on mosquitoes collected simultaneously from 2 villages in Burkina Faso over a 6-week period, one of which received an MDA, and it detected 20.8% drop in the mean age of mosquitoes collected from the treatment village the first week post-MDA. National variations in NIRS data, likely from diet, genetic background, and other factors limits the accuracy of this technique with wild-caught mosquitoes. However, with extensive calibration models developed from multiple, locale-matched field locations, this technique can be used to investigate mosquito age structure in wild An. gambiae, and determine how it changes in response to vector control measures.