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      A randomized, double-blind placebo-control study assessing the protective efficacy of an odour-based ‘push–pull’ malaria vector control strategy in reducing human-vector contact

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          Abstract

          Novel malaria vector control strategies targeting the odour-orientation of mosquitoes during host-seeking, such as ‘attract-and-kill’ or ‘push-and-pull’, have been suggested as complementary tools to indoor residual spraying and long-lasting insecticidal nets. These would be particularly beneficial if they can target vectors in the peri-domestic space where people are unprotected by traditional interventions. A randomized double-blind placebo-control study was implemented in western Kenya to evaluate: a ‘push’ intervention (spatial repellent) using transfluthrin-treated fabric strips positioned at open eave gaps of houses; a ‘pull’ intervention placing an odour-baited mosquito trap at a 5 m distance from a house; the combined ‘push–pull’ package; and the control where houses contained all elements but without active ingredients. Treatments were rotated through 12 houses in a randomized-block design. Outdoor biting was estimated using human landing catches, and indoor mosquito densities using light-traps. None of the interventions provided any protection from outdoor biting malaria vectors. The ‘push’ reduced indoor vector densities dominated by Anopheles funestus by around two thirds. The ‘pull’ device did not add any benefit. In the light of the high Anopheles arabiensis biting densities outdoors in the study location, the search for efficient outdoor protection and effective pull components needs to continue.

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          Stan: A Probabilistic Programming Language

          Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.
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            Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC

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              Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction.

              A ribosomal DNA-polymerase chain reaction (PCR) method has been developed for species identification of individuals of the five most widespread members of the Anopheles gambiae complex, a group of morphologically indistinguishable sibling mosquito species that includes the major vectors of malaria in Africa. The method, which is based on species-specific nucleotide sequences in the ribosomal DNA intergenic spacers, may be used to identify both species and interspecies hybrids, regardless of life stage, using either extracted DNA or fragments of a specimen. Intact portions of a mosquito as small as an egg or the segment of one leg may be placed directly into the PCR mixture for amplification and analysis. The method uses a cocktail of five 20-base oligonucleotides to identify An. gambiae, An. arabiensis, An. quadriannnulatus, and either An. melas in western Africa or An. melas in eastern and southern Africa.
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                Author and article information

                Contributors
                ufillinger@icipe.org
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 July 2023
                11 July 2023
                2023
                : 13
                : 11197
                Affiliations
                [1 ]GRID grid.419326.b, ISNI 0000 0004 1794 5158, International Centre of Insect Physiology and Ecology (Icipe), ; Human Health Theme, Nairobi, 00100 Kenya
                [2 ]GRID grid.416786.a, ISNI 0000 0004 0587 0574, Department of Epidemiology and Public Health, , Swiss Tropical and Public Health Institute, ; Kreuzstrasse 2, Allschwil, Switzerland
                [3 ]GRID grid.6612.3, ISNI 0000 0004 1937 0642, University of Basel, ; Petersplatz 1, Basel, Switzerland
                [4 ]GRID grid.4818.5, ISNI 0000 0001 0791 5666, Laboratory of Entomology, , Wageningen University & Research, ; P.O. Box 16, 6700 AA Wageningen, The Netherlands
                [5 ]GRID grid.414543.3, ISNI 0000 0000 9144 642X, Vector Control Product Testing Unit (VCPTU), Department of Environmental Health and Ecological Sciences, , Ifakara Health Institute, ; P.O. Box 74, Bagamoyo, Tanzania
                [6 ]GRID grid.451346.1, ISNI 0000 0004 0468 1595, The Nelson Mandela African Institution of Science and Technology (NM-AIST), ; Tengeru, P.O. Box 447, Arusha, Tanzania
                [7 ]GRID grid.414659.b, ISNI 0000 0000 8828 1230, Telethon Kids Institute, ; Perth, Australia
                [8 ]Arctech Innovation Ltd., The Cube, Londoneast-Uk Business and Technical Park, Yew Tree Avenue, Dagenham, RM10 7FN UK
                Article
                38463
                10.1038/s41598-023-38463-5
                10336143
                37433881
                27ea7b0e-8521-4c8f-8e85-04e33ce44416
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 February 2023
                : 8 July 2023
                Funding
                Funded by: Innovative Vector Control Consortium (IVCC)
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2023

                Uncategorized
                malaria,entomology
                Uncategorized
                malaria, entomology

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