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Risk-Based Mapping Tools for Surveillance and Control of the Invasive Mosquito Aedes albopictus in Switzerland

Author

Listed:
  • Damiana Ravasi

    (Department for Environment Constructions and Design, Institute of Microbiology (IM), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6850 Mendrisio, Switzerland)

  • Francesca Mangili

    (Department of Innovative Technologies, Dalle Molle Institute for Artificial Intelligence Studies (IDSIA), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6962 Lugano-Viganello, Switzerland)

  • David Huber

    (Department of Innovative Technologies, Dalle Molle Institute for Artificial Intelligence Studies (IDSIA), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6962 Lugano-Viganello, Switzerland)

  • Laura Azzimonti

    (Department of Innovative Technologies, Dalle Molle Institute for Artificial Intelligence Studies (IDSIA), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6962 Lugano-Viganello, Switzerland)

  • Lukas Engeler

    (Department for Environment Constructions and Design, Institute of Microbiology (IM), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6850 Mendrisio, Switzerland)

  • Nicola Vermes

    (Department of Innovative Technologies, Dalle Molle Institute for Artificial Intelligence Studies (IDSIA), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6962 Lugano-Viganello, Switzerland)

  • Giacomo Del Rio

    (Department of Innovative Technologies, Dalle Molle Institute for Artificial Intelligence Studies (IDSIA), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6962 Lugano-Viganello, Switzerland)

  • Valeria Guidi

    (Department for Environment Constructions and Design, Institute of Microbiology (IM), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6850 Mendrisio, Switzerland)

  • Mauro Tonolla

    (Department for Environment Constructions and Design, Institute of Microbiology (IM), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6850 Mendrisio, Switzerland)

  • Eleonora Flacio

    (Department for Environment Constructions and Design, Institute of Microbiology (IM), University of Applied Sciences and Arts of Southern Switzerland (SUPSI), 6850 Mendrisio, Switzerland)

Abstract

Background: In Switzerland, Aedes albopictus is well established in Ticino, south of the Alps, where surveillance and control are implemented. The mosquito has also been observed in Swiss cities north of the Alps. Decision-making tools are urgently needed by the local authorities in order to optimize surveillance and control. Methods: A regularized logistic regression was used to link the long-term dataset of Ae. albopictus occurrence in Ticino with socioenvironmental predictors. The probability of establishment of Ae. albopictus was extrapolated to Switzerland and more finely to the cities of Basel and Zurich. Results: The model performed well, with an AUC of 0.86. Ten socio-environmental predictors were selected as informative, including the road-based distance in minutes of travel by car from the nearest cell established in the previous year. The risk maps showed high suitability for Ae. albopictus establishment in the Central Plateau, the area of Basel, and the lower Rhone Valley in the Canton of Valais. Conclusions: The areas identified as suitable for Ae. albopictus establishment are consistent with the actual current findings of tiger mosquito. Our approach provides a useful tool to prompt authorities’ intervention in the areas where there is higher risk of introduction and establishment of Ae. albopictus .

Suggested Citation

  • Damiana Ravasi & Francesca Mangili & David Huber & Laura Azzimonti & Lukas Engeler & Nicola Vermes & Giacomo Del Rio & Valeria Guidi & Mauro Tonolla & Eleonora Flacio, 2022. "Risk-Based Mapping Tools for Surveillance and Control of the Invasive Mosquito Aedes albopictus in Switzerland," IJERPH, MDPI, vol. 19(6), pages 1-22, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3220-:d:767456
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    References listed on IDEAS

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    1. Melo-Merino, Sara M. & Reyes-Bonilla, Héctor & Lira-Noriega, Andrés, 2020. "Ecological niche models and species distribution models in marine environments: A literature review and spatial analysis of evidence," Ecological Modelling, Elsevier, vol. 415(C).
    2. Früh, Linus & Kampen, Helge & Kerkow, Antje & Schaub, Günter A. & Walther, Doreen & Wieland, Ralf, 2018. "Modelling the potential distribution of an invasive mosquito species: comparative evaluation of four machine learning methods and their combinations," Ecological Modelling, Elsevier, vol. 388(C), pages 136-144.
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