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dc.contributor.editorLees, Rosemary S.
dc.date.accessioned2023-03-07T16:35:02Z
dc.date.available2023-03-07T16:35:02Z
dc.date.issued2023
dc.identifierONIX_20230307_9783036565927_129
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/98119
dc.description.abstractThe eradication of vector-borne diseases is threatened by the limited range of available insecticides, leading, inevitably, to the development of resistance. This is particularly concerning for malaria control, which relies heavily on insecticide-treated nets (ITNs) and indoor residual sprays (IRS). New chemistries are being developed, and innovative deployment of insecticides may play a role in overcoming resistance, either through new types of tools or new means of distribution. A variety of novel product types and vector control strategies are under development and evaluation, which is to be celebrated, but a strong evidence base is needed to guide effective operational deployment decisions. Novel approaches should be supported by robust data collected using appropriate and validated methods to monitor efficacy, durability, and any emerging resistance. This reprint presents original research into developing and characterizing new vector control products, as well as understanding and monitoring insecticide resistance. Review articles explore the impact of insecticide resistance and offer guidance on insecticide choice in the face of pyrethroid resistance. Consensus methodologies are presented, in the form of standard operating procedures (SOPs) designed to be adopted and used to generate reproducible data that can be compared and interpreted across and between studies. It is hoped that this collection of articles offers inspiration and guidance on how consistent data can be generated to inform more effective development, evaluation, and use of new and existing vector control tools.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Scienceen_US
dc.subject.otherprallethrin
dc.subject.otherinsecticide
dc.subject.otherspatial treatment
dc.subject.othermosquito fitness
dc.subject.otherprotection
dc.subject.otherpyrethroids
dc.subject.otherAedes albopictus
dc.subject.otherCulex pipiens
dc.subject.otherlife tables
dc.subject.othermosquito
dc.subject.otherbite-proof garment
dc.subject.othermodel
dc.subject.othertextile
dc.subject.othernon-insecticidal
dc.subject.otherphysical barrier
dc.subject.otherinsecticide selection
dc.subject.otherout-crossing
dc.subject.otherstrain authentication
dc.subject.otherlaboratory screening
dc.subject.otherpyrethroid
dc.subject.otherpyrethroid resistance
dc.subject.otherinsecticide resistance
dc.subject.otherinsecticide resistance management
dc.subject.othervector control
dc.subject.othermalaria
dc.subject.othermalaria control
dc.subject.otherAnopheles
dc.subject.otherhost-seeking behavior
dc.subject.otherinsecticide exposure
dc.subject.otherpathogen transmission
dc.subject.otherAedes aegypti
dc.subject.otherAnopheles gambiae
dc.subject.otherATSB
dc.subject.otherCulex quinquefasciatus
dc.subject.otherIroquois
dc.subject.otherRNAi
dc.subject.otherSaccharomyces cerevisiae
dc.subject.otheryeast
dc.subject.otherAnopheles mosquito
dc.subject.otherfertility
dc.subject.otherovary development
dc.subject.otherpyriproxyfen (PPF)
dc.subject.otherside-effects
dc.subject.othermachine learning
dc.subject.otherimage classification
dc.subject.otherautomated identification
dc.subject.otherconvolutional neural network
dc.subject.otherinsecticide-treated net (ITN)
dc.subject.otherPBO ITN
dc.subject.othersynergist ITN
dc.subject.otherdual-AI ITN
dc.subject.otherinsecticide resistance management (IRM)
dc.subject.othermethod validation
dc.subject.otherdurability monitoring
dc.subject.otherbioinsecticide
dc.subject.otherdisease transmission
dc.subject.otherinsecticide-resistance
dc.subject.othermosquito-borne disease
dc.subject.othermosquito control
dc.subject.othernatural compounds
dc.subject.otherphytochemical
dc.subject.othermalaria vector
dc.subject.otherinsecticide treated nets
dc.subject.othercytochrome P450s
dc.subject.otherkdr
dc.subject.othercuticular resistance
dc.subject.otherdeltamethrin
dc.subject.otherimidacloprid
dc.subject.otherbifenthrin
dc.subject.otherβ-cyfluthrin
dc.subject.otheretofenprox
dc.subject.otherα-cypermethrin
dc.subject.otherλ-cyhalothrin
dc.subject.otherthiacloprid
dc.subject.othermosquitoes
dc.subject.otherAttractive Toxic Sugar Bait (ATSB)
dc.subject.otherAttractive Targeted Sugar Bait (ATSB)
dc.subject.otherdiagnostic bioassay
dc.subject.otherresistance monitoring
dc.subject.otherinsecticide-treated nets (ITN)
dc.subject.otherstrain characterisation
dc.subject.othermethod development
dc.subject.otherproduct evaluation
dc.subject.otherquality control (QC)
dc.subject.otherdual active ingredients (dual-AI)
dc.subject.otherbioefficacy
dc.subject.otherIRS
dc.subject.otherapplication technology
dc.subject.otherbroflanilide
dc.subject.otherclothianidin
dc.subject.otherpirimiphos-methyl
dc.subject.otherWHO tube
dc.subject.otherWHO tunnel test
dc.subject.otherITNs
dc.subject.otherinterceptor
dc.subject.otherinterceptor G2
dc.subject.othermembrane
dc.subject.otherhuman arm
dc.subject.otherrabbit
dc.subject.otherbioassay
dc.subject.otherbio-efficacy
dc.subject.othern/a
dc.titleInsecticides for Mosquito Control: Strengthening the Evidence Base
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-6593-4
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036565927
oapen.relation.isbn9783036565934
oapen.pages338
oapen.place.publicationBasel


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