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A climate-driven abundance model to assess mosquito control strategies

Author

Listed:
  • Cailly, Priscilla
  • Tran, Annelise
  • Balenghien, Thomas
  • L’Ambert, Grégory
  • Toty, Céline
  • Ezanno, Pauline

Abstract

As mosquitoes are vectors of major pathogens worldwide, the control of mosquito populations is one way to fight vector-borne diseases. The objectives of our study were to develop a tool to predict mosquito abundance over time, identify the main determinants of mosquito population dynamics, and assess mosquito control strategies. We developed a generic, mechanistic, climate-driven model of seasonal mosquito population dynamics that can be run over several years because it takes diapause into account. Both aquatic and adult stages are considered, resulting in 10 model compartments: eggs, larvae, and pupae for juveniles; emergent, nulliparous, and parous for adults, the latter two broken down into host-seeking, resting, and ovipositing adults. We then applied the model to Anopheles species of southern France, some of which (nulliparous adults) overwinter. We defined specific transition functions and parameter values for these species and this geographical area based on a literature review. Our model correctly predicted entomological field data. Control points in the model were related to mortality rates of adults, the sex-ratio at emergence, parameters related to development functions and the number of eggs laid by females. Lastly, we used our model to compare the efficiency of mosquito control strategies targeting larvae. We found that a larvicide spraying at regular time intervals acted as a preventive measure against mosquito emergence, and that such a strategy was more efficient than spraying only when the abundance of host-seeking females reached a given threshold. The proposed model can be applied easily to other mosquito species and geographic areas by adapting transition functions and parameter values.

Suggested Citation

  • Cailly, Priscilla & Tran, Annelise & Balenghien, Thomas & L’Ambert, Grégory & Toty, Céline & Ezanno, Pauline, 2012. "A climate-driven abundance model to assess mosquito control strategies," Ecological Modelling, Elsevier, vol. 227(C), pages 7-17.
    • Handle: RePEc:eee:ecomod:v:227:y:2012:i:c:p:7-17
    DOI: 10.1016/j.ecolmodel.2011.10.027
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    Citations

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    Cited by:

    1. Haramboure, Marion & Labbé, Pierrick & Baldet, Thierry & Damiens, David & Gouagna, Louis Clément & Bouyer, Jérémy & Tran, Annelise, 2020. "Modelling the control of Aedes albopictus mosquitoes based on sterile males release techniques in a tropical environment," Ecological Modelling, Elsevier, vol. 424(C).
    2. Giovanni Marini & Piero Poletti & Mario Giacobini & Andrea Pugliese & Stefano Merler & Roberto Rosà, 2016. "The Role of Climatic and Density Dependent Factors in Shaping Mosquito Population Dynamics: The Case of Culex pipiens in Northwestern Italy," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-15, April.
    3. Jian, Yun & Silvestri, Sonia & Belluco, Enrica & Saltarin, Andrea & Chillemi, Giovanni & Marani, Marco, 2014. "Environmental forcing and density-dependent controls of Culex pipiens abundance in a temperate climate (Northeastern Italy)," Ecological Modelling, Elsevier, vol. 272(C), pages 301-310.
    4. Lingcai Kong & Jinfeng Wang & Zhongjie Li & Shengjie Lai & Qiyong Liu & Haixia Wu & Weizhong Yang, 2018. "Modeling the Heterogeneity of Dengue Transmission in a City," IJERPH, MDPI, vol. 15(6), pages 1-21, May.
    5. Zheng, Bo & Yu, Jianshe & Xi, Zhiyong & Tang, Moxun, 2018. "The annual abundance of dengue and Zika vector Aedes albopictus and its stubbornness to suppression," Ecological Modelling, Elsevier, vol. 387(C), pages 38-48.
    6. Annelise Tran & Grégory L'Ambert & Guillaume Lacour & Romain Benoît & Marie Demarchi & Myriam Cros & Priscilla Cailly & Mélaine Aubry-Kientz & Thomas Balenghien & Pauline Ezanno, 2013. "A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations," IJERPH, MDPI, vol. 10(5), pages 1-22, April.
    7. Anwar Musah & Livia Màrcia Mosso Dutra & Aisha Aldosery & Ella Browning & Tercio Ambrizzi & Iuri Valerio Graciano Borges & Merve Tunali & Selma Başibüyük & Orhan Yenigün & Giselle Machado Magalhaes Mo, 2022. "An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities: Recife and Campina Grande," Data, MDPI, vol. 7(8), pages 1-13, July.
    8. Haocheng Wu & Chen Wu & Qinbao Lu & Zheyuan Ding & Ming Xue & Junfen Lin, 2019. "Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-16, August.

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