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Cited by 445

The DOI matches its Crossref record; 128 of the 128 references it cites were found in a registry or an index.

Biological Control of Mosquito Vectors: Past, Present, and Future

Open access
Benelli, Giovanni, Jeffries, Claire, Walker, Thomas·2016·Insects

Abstract

Mosquitoes represent the major arthropod vectors of human disease worldwide transmitting malaria, lymphatic filariasis, and arboviruses such as dengue virus and Zika virus. Unfortunately, no treatment (in the form of vaccines or drugs) is available for most of these diseases and vector control is still the main form of prevention. The limitations of traditional insecticide-based strategies, particularly the development of insecticide resistance, have resulted in significant efforts to develop alternative eco-friendly methods. Biocontrol strategies aim to be sustainable and target a range of different mosquito species to reduce the current reliance on insecticide-based mosquito control. In this review, we outline non-insecticide based strategies that have been implemented or are currently being tested. We also highlight the use of mosquito behavioural knowledge that can be exploited for control strategies.

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Crossref · 10.3390/insects7040052

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Metadata

Authors
Benelli, G., Jeffries, C., & Walker, T.
Venue
Insects
Publisher
MDPI AG
Published
2016-10-03
Volume
7
Issue
4
Pages
52
ISSN
2075-4450 (ISSN-L)
OpenAlex
W2527916419
Cited by
445
References
128
FWCI
27.51
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Biological Control of Mosquito Vectors: Past, Present, and Future. https://app.cochat.ai/papers/10.3390/insects7040052
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Benelli, G., Jeffries, C., & Walker, T. (2016). Biological Control of Mosquito Vectors: Past, Present, and Future. Insects. https://doi.org/10.3390/insects7040052

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.