دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Rapid age-grading and species identification of natural mosquitoes for malaria surveillance.
المؤلفون: Siria DJ; Environmental Health & Ecological Sciences Department, Ifakara Health Institute, Off Mlabani Passage, PO Box 53, Ifakara, Tanzania., Sanou R; Institut de Recherche en Sciences de la Santé (IRSS)/Centre Muraz, Bobo-Dioulasso, Burkina Faso., Mitton J; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK.; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK.; School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK., Mwanga EP; Environmental Health & Ecological Sciences Department, Ifakara Health Institute, Off Mlabani Passage, PO Box 53, Ifakara, Tanzania.; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Niang A; Institut de Recherche en Sciences de la Santé (IRSS)/Centre Muraz, Bobo-Dioulasso, Burkina Faso., Sare I; Institut de Recherche en Sciences de la Santé (IRSS)/Centre Muraz, Bobo-Dioulasso, Burkina Faso., Johnson PCD; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Foster GM; Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK., Belem AMG; Université Nazi Boni de Bobo-Dioulasso, Bobo-Dioulasso, PO 1091, Burkina Faso., Wynne K; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK., Murray-Smith R; School of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK., Ferguson HM; Environmental Health & Ecological Sciences Department, Ifakara Health Institute, Off Mlabani Passage, PO Box 53, Ifakara, Tanzania.; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., González-Jiménez M; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK. Mario.GonzalezJimenez@glasgow.ac.uk., Babayan SA; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK. Simon.Babayan@glasgow.ac.uk., Diabaté A; Institut de Recherche en Sciences de la Santé (IRSS)/Centre Muraz, Bobo-Dioulasso, Burkina Faso., Okumu FO; Environmental Health & Ecological Sciences Department, Ifakara Health Institute, Off Mlabani Passage, PO Box 53, Ifakara, Tanzania.; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Baldini F; Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK. Francesco.Baldini@glasgow.ac.uk.
المصدر: Nature communications [Nat Commun] 2022 Mar 21; Vol. 13 (1), pp. 1501. Date of Electronic Publication: 2022 Mar 21.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE
أسماء مطبوعة: Original Publication: [London] : Nature Pub. Group
مواضيع طبية MeSH: Anopheles*/parasitology , Malaria*/epidemiology , Malaria*/parasitology , Malaria*/prevention & control, Animals ; Burkina Faso/epidemiology ; Female ; Humans ; Longevity ; Mosquito Control/methods ; Mosquito Vectors/parasitology
مستخلص: 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.
(© 2022. The Author(s).)
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معلومات مُعتمدة: MR/P025501/1 United Kingdom MRC_ Medical Research Council; United Kingdom WT_ Wellcome Trust; WT102350/Z/13 United Kingdom WT_ Wellcome Trust
تواريخ الأحداث: Date Created: 20220322 Date Completed: 20220412 Latest Revision: 20220512
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC8938457
DOI: 10.1038/s41467-022-28980-8
PMID: 35314683
قاعدة البيانات: MEDLINE
الوصف
تدمد:2041-1723
DOI:10.1038/s41467-022-28980-8