Skip to main content
Log in

Modelling can reduce contamination from mosquito population control

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

Abstract

Environmental contamination due to pest control in general, and mosquito control in particular, is an important issue expected to increase with climate change. We use a validated model for population dynamics of mosquitoes and historical environmental data to explore performance of larvicidal, adulticidal, and combined treatments. Results show that depending on treatment timing, larvicidal treatments can induce very good results, or have negative outcomes that increase overall mosquito population. Combined larvicidal and adulticidal treatments, however, exhibit much lesser dependence on timing, and therefore give the greatest chance of positive outcomes if environmental conditions are not known. Based on the results, we argue for adaptive mosquito management, in which weather data and forecasts are used to drive a model that identifies best intervals for insecticide use. Such an approach can have considerably better results than static, calendar-driven management and, therefore, considerably reduce environmental contamination. Adaptive management could consider larvicidal treatment because it gives good results if the timing is correct. Static management should, however, combine larvicidal and adulticidal treatments for the greatest chance of success.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 8
Fig. 7

Similar content being viewed by others

References

Download references

Funding

This work was conducted within the CADAPT project (Adaptation of mosquito population control measures to climate change in Croatia) funded by the European Regional Development Fund and the Environmental Protection and Energy Efficiency Fund under the contract number: KK.05.1.1.02.0008. Hardware donated by NVIDIA Applied Research Accelerator Program was used in this research. The first author has been supported by the Young Scientist Career Development grant of the Croatian Science Foundation (HRZZ-DOK-2021-02-3492).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: BKH, TD, DKH; Methodology: BKH, TD, DKH, TK; Formal analysis and investigation: TD, DKH; Visualization: TD; Writing–original draft: TD, TK, DKH, BKH; Writing–review & editing: TD, BKH; Supervision: BKH; Funding acquisition: BKH.

Corresponding author

Correspondence to Branimir K. Hackenberger.

Ethics declarations

Conflict of interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

GitHub repository containing codes used for simulating mosquito population control scenarios.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 1586 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Djerdj, T., Hackenberger, D.K., Klanjšček, T. et al. Modelling can reduce contamination from mosquito population control. Stoch Environ Res Risk Assess 37, 1007–1019 (2023). https://doi.org/10.1007/s00477-022-02326-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-022-02326-8

Keywords

Navigation