ArticleParasites & vectors2018
Detection of Plasmodium berghei infected Anopheles stephensi using near-infrared spectroscopy.
Article in Parasites & vectors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- The application of spectroscopy techniques for diagnosis of malaria parasites and arboviruses and surveillance of mosquito vectors: A systematic review and critical appraisal of evidence.PLoS neglected tropical diseases · 2021Pooled it
- Assessment of automated loop-mediated isothermal amplification-(LAMP-)based xenomonitoring for Plasmodium spp. in Anopheles mosquitoes.Malaria journal · 2026Article
- Artificial intelligence-powered microscopy: Transforming the landscape of parasitology.Journal of microscopy · 2026Review
- Age structure of cohorts of mosquitoes from the field using shortwave infrared spectroscopy before and after ULV adulticide treatment.Parasites & vectors · 2025Article
- OocystMeter, a machine-learning algorithm to count and measurebioRxiv : the preprint server for biology · 2025Article
- Reagent-free detection of Plasmodium falciparum malaria infections in field-collected mosquitoes using mid-infrared spectroscopy and machine learning.Scientific reports · 2024Article
- Age, sex, and mating status discrimination in the sand fly Lutzomyia longipalpis using near infra-red spectroscopy (NIRS).Parasites & vectors · 2024Article
- Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis.Malaria journal · 2023Review
- Nondestructive Methods of Pathogen Detection: Importance of Mosquito Integrity in Studies of Disease Transmission and Control.Pathogens (Basel, Switzerland) · 2023Review
- Rapid and Non-Invasive Detection ofViruses · 2022Article
- Adapting field-mosquito collection techniques in a perspective of near-infrared spectroscopy implementation.Parasites & vectors · 2022Article
- Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.Scientific reports · 2021Article
- A non-destructive sugar-feeding assay for parasite detection and estimating the extrinsic incubation period of Plasmodium falciparum in individual mosquito vectors.Scientific reports · 2021Article
- Emergence of Arboviruses in the United States: The Boom and Bust of Funding, Innovation, and Capacity.Tropical medicine and infectious disease · 2020Article
- Artificial Intelligence in Intracoronary Imaging.Current cardiology reports · 2020Review
- Ability of near-infrared spectroscopy and chemometrics to predict the age of mosquitoes reared under different conditions.Parasites & vectors · 2020Article
- Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis.Malaria journal · 2019Article
- Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.Malaria journal · 2019Article
- Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy.Malaria journal · 2019Article
- Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning.Wellcome open research · 2019Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
Abstract
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 to requirements.
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