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      Keeping track of mosquitoes: a review of tools to track, record and analyse mosquito flight

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          Abstract

          The health impact of mosquito-borne diseases causes a huge burden on human societies. Recent vector control campaigns have resulted in promising declines in incidence and prevalence of these diseases, notably malaria, but resistance to insecticides and drugs are on the rise, threatening to overturn these gains. Moreover, several vector-borne diseases have re-emerged, requiring prompt and effective response measures. To improve and properly implement vector control interventions, the behaviour of the vectors must be well understood with detailed examination of mosquito flight being an essential component. Current knowledge on mosquito behaviour across its life history is briefly presented, followed by an overview of recent developments in automated tracking techniques for detailed interpretation of mosquito behaviour. These techniques allow highly accurate recording and observation of mating, feeding and oviposition behaviour. Software programmes built with specific algorithms enable quantification of these behaviours. For example, the crucial role of heat on host landing and the multimodal integration of carbon dioxide (CO 2) with other host cues, has been unravelled based on three-dimensional tracking of mosquito flight behaviour. Furthermore, the behavioural processes underlying house entry and subsequent host searching and finding can be better understood by analysis of detailed flight recordings. Further potential of these technologies to solve knowledge gaps is discussed. The use of tracking techniques can support or replace existing monitoring tools and provide insights on mosquito behaviour that can lead to innovative and more effective vector-control measures.

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          Most cited references134

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          Software techniques for two- and three-dimensional kinematic measurements of biological and biomimetic systems.

          Researchers studying aspects of locomotion or movement in biological and biomimetic systems commonly use video or stereo video recordings to quantify the behaviour of the system in question, often with an emphasis on measures of position, velocity and acceleration. However, despite the apparent simplicity of video analysis, it can require substantial investment of time and effort, even when performed with adequate software tools. This paper reviews the underlying principles of video and stereo video analysis as well as its automation and is accompanied by fully functional and freely available software implementation.
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            The use of push-pull strategies in integrated pest management.

            Push-pull strategies involve the behavioral manipulation of insect pests and their natural enemies via the integration of stimuli that act to make the protected resource unattractive or unsuitable to the pests (push) while luring them toward an attractive source (pull) from where the pests are subsequently removed. The push and pull components are generally nontoxic. Therefore, the strategies are usually integrated with methods for population reduction, preferably biological control. Push-pull strategies maximize efficacy of behavior-manipulating stimuli through the additive and synergistic effects of integrating their use. By orchestrating a predictable distribution of pests, efficiency of population-reducing components can also be increased. The strategy is a useful tool for integrated pest management programs reducing pesticide input. We describe the principles of the strategy, list the potential components, and present case studies reviewing work on the development and use of push-pull strategies in each of the major areas of pest control.
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              idTracker: tracking individuals in a group by automatic identification of unmarked animals.

              Animals in groups touch each other, move in paths that cross, and interact in complex ways. Current video tracking methods sometimes switch identities of unmarked individuals during these interactions. These errors propagate and result in random assignments after a few minutes unless manually corrected. We present idTracker, a multitracking algorithm that extracts a characteristic fingerprint from each animal in a video recording of a group. It then uses these fingerprints to identify every individual throughout the video. Tracking by identification prevents propagation of errors, and the correct identities can be maintained indefinitely. idTracker distinguishes animals even when humans cannot, such as for size-matched siblings, and reidentifies animals after they temporarily disappear from view or across different videos. It is robust, easy to use and general. We tested it on fish (Danio rerio and Oryzias latipes), flies (Drosophila melanogaster), ants (Messor structor) and mice (Mus musculus).
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                Author and article information

                Contributors
                jeroen.spitzen@wur.nl
                willem.takken@wur.nl
                Journal
                Parasit Vectors
                Parasit Vectors
                Parasites & Vectors
                BioMed Central (London )
                1756-3305
                2 March 2018
                2 March 2018
                2018
                : 11
                : 123
                Affiliations
                ISNI 0000 0001 0791 5666, GRID grid.4818.5, Laboratory of Entomology, , Wageningen University and Research, ; PO Box 16, 6700 AA Wageningen, The Netherlands
                Author information
                http://orcid.org/0000-0003-0455-7511
                Article
                2735
                10.1186/s13071-018-2735-6
                5834890
                29499744
                6896bbf1-6acf-4fab-b310-67df6a74dbd2
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 October 2017
                : 21 February 2018
                Categories
                Review
                Custom metadata
                © The Author(s) 2018

                Parasitology
                flight behaviour,automated tracking,mosquito,3d analysis,infectious diseases,malaria,behavioural ecology,vector control

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