Imperial College London
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ProfessorThomasChurcher

Faculty of Medicine, School of Public Health

Professor of Infectious Disease Dynamics
 
 
 
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Contact

 

thomas.churcher

 
 
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Location

 

G35Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Esperanca:2018:10.1186/s13071-018-2960-z,
author = {Esperanca, PM and Blagborough, AM and Da, DF and Dowell, FE and Churcher, TS},
doi = {10.1186/s13071-018-2960-z},
journal = {Parasites and Vectors},
title = {Detection of Plasmodium berghei infected Anopheles stephensi using near-infrared spectroscopy},
url = {http://dx.doi.org/10.1186/s13071-018-2960-z},
volume = {11},
year = {2018}
}
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TY  - JOUR
AB  - BackgroundThe proportion of mosquitoes infected with malaria is an important entomological metric used to assess the intensity of transmission and the impact of vector control interventions. Currently, the prevalence of mosquitoes with salivary gland sporozoites is estimated by dissecting mosquitoes under a microscope or using molecular methods. These techniques are laborious, subjective, and require either expensive equipment or training. This study evaluates the potential of near-infrared spectroscopy (NIRS) to identify laboratory reared mosquitoes infected with rodent malaria.MethodsAnopheles stephensi mosquitoes were reared in the laboratory and fed on Plasmodium berghei infected blood. After 12 and 21 days post-feeding mosquitoes were killed, scanned and analysed using NIRS and immediately dissected by microscopy to determine the number of oocysts on the midgut wall or sporozoites in the salivary glands. A predictive classification model was used to determine parasite prevalence and intensity status from spectra.ResultsThe predictive model correctly classifies infectious and uninfectious mosquitoes with an overall accuracy of 72%. The false negative and false positive rates were 30 and 26%, respectively. While NIRS was able to differentiate between uninfectious and highly infectious mosquitoes, differentiating between mid-range infectious groups was less accurate. Multiple scans of the same specimen, with repositioning the mosquito between scans, is shown to improve accuracy. On a smaller dataset NIRS was unable to predict whether mosquitoes harboured oocysts.ConclusionsTo our knowledge, we provide the first evidence that NIRS can differentiate between infectious and uninfectious mosquitoes. Currently, distinguishing between different intensities of infection is challenging. The classification model provides a flexible framework and allows for different error rates to be optimised, enabling the sensitivity and specificity of the technique to be varied according
AU  - Esperanca,PM
AU  - Blagborough,AM
AU  - Da,DF
AU  - Dowell,FE
AU  - Churcher,TS
DO  - 10.1186/s13071-018-2960-z
PY  - 2018///
SN  - 1756-3305
TI  - Detection of Plasmodium berghei infected Anopheles stephensi using near-infrared spectroscopy
T2  - Parasites and Vectors
UR  - http://dx.doi.org/10.1186/s13071-018-2960-z
UR  - https://parasitesandvectors.biomedcentral.com/track/pdf/10.1186/s13071-018-2960-z
UR  - http://hdl.handle.net/10044/1/61911
VL  - 11
ER  -
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