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Arbovirus Detection in Vectors

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Genetically Modified and other Innovative Vector Control Technologies

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Abstract

Detection of arthropod-borne (arbo)viruses is a fundamental element of mosquito surveillance programmes. Moreover, recent advances in modifying mosquitoes for managing arbovirus vector populations rely on sensitive arbovirus detection methods, which are applied at various stages of development, evaluation and production of modified mosquitoes. An increasingly wide range of mosquito trapping, sampling and testing options are available. Although virus culture will remain important for isolating viruses for research and reference purposes, the widespread use and application of real-time reverse transcription polymerase chain reaction (RT-PCR) offers rapid and cost-effective workflows for detecting arbovirus nucleic acid. Advances in next-generation sequencing (NGS) techniques and bioinformatics approaches have also enabled increasingly rapid, accurate and inexpensive arbovirus genome sequencing that can be employed following virus detection using conventional methods or used independently as a stand-alone platform. Unbiased NGS is also a powerful tool for arbovirus discovery and metagenomics. Continued advances in arbovirus detection methods and approaches are expected to provide ever more sophisticated tools for controlling and responding to the threat of pathogenic arboviruses.

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Authors and Affiliations

  1. CSIRO, Australian Centre for Disease Preparedness, Geelong, VIC, Australia

    David T. Williams & Prasad Paradkar

  2. Australian Institute of Tropical Health and Medicine, James Cook University, Smithfield, QLD, Australia

    Stephan Karl

  3. Vector-Borne Diseases Unit, PNG Institute of Medical Research, Madang, Madang Province, Papua New Guinea

    Stephan Karl

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  1. David T. Williams
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  2. Prasad Paradkar
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  3. Stephan Karl
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Correspondence to David T. Williams .

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  1. VIT University, Vellore, Tamil Nadu, India

    Brij Kishore Tyagi

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Williams, D.T., Paradkar, P., Karl, S. (2021). Arbovirus Detection in Vectors. In: Tyagi, B.K. (eds) Genetically Modified and other Innovative Vector Control Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-16-2964-8_14

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