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Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission

BACKGROUND: Current strategies to control mosquito-transmitted infections use insecticides targeted at various stages of the mosquito life-cycle. Control is increasingly compromised by the evolution of insecticide resistance but there is little quantitative understanding of its impact on control eff...

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Autores principales: Barbosa, Susana, Kay, Katherine, Chitnis, Nakul, Hastings, Ian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114906/
https://www.ncbi.nlm.nih.gov/pubmed/30153869
http://dx.doi.org/10.1186/s13071-018-3025-z
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author Barbosa, Susana
Kay, Katherine
Chitnis, Nakul
Hastings, Ian M.
author_facet Barbosa, Susana
Kay, Katherine
Chitnis, Nakul
Hastings, Ian M.
author_sort Barbosa, Susana
collection PubMed
description BACKGROUND: Current strategies to control mosquito-transmitted infections use insecticides targeted at various stages of the mosquito life-cycle. Control is increasingly compromised by the evolution of insecticide resistance but there is little quantitative understanding of its impact on control effectiveness. We developed a computational approach that incorporates the stage-structured mosquito life-cycle and allows tracking of insecticide resistant genotypes. This approach makes it possible to simultaneously investigate: (i) the population dynamics of mosquitoes throughout their whole life-cycle; (ii) the impact of common vector control interventions on disease transmission; (iii) how these interventions drive the spread of insecticide resistance; and (iv) the impact of resistance once it has arisen and, in particular, whether it is sufficient for malaria transmission to resume. The model consists of a system of difference equations that tracks the immature (eggs, larvae and pupae) and adult stages, for males and females separately, and incorporates density-dependent regulation of mosquito larvae in breeding sites. RESULTS: We determined a threshold level of mosquitoes below which transmission of malaria is interrupted. It is based on a classic Ross-Macdonald derivation of the malaria basic reproductive number (R(0)) and may be used to assess the effectiveness of different control strategies in terms of whether they are likely to interrupt disease transmission. We simulated different scenarios of insecticide deployment by changing key parameters in the model to explore the comparative impact of insecticide treated nets, indoor residual spraying and larvicides. CONCLUSIONS: Our simulated results suggest that relatively low degrees of resistance (in terms of reduced mortality following insecticide contact) can induce failure of interventions, and the rate of spread of resistance is faster when insecticides target the larval stages. The optimal disease control strategy depends on vector species demography and local environmental conditions but, in our illustrative parametrisation, targeting larval stages achieved the greatest reduction of the adult population, followed by targeting of non-host-seeking females, as provided by indoor residual spraying. Our approach is designed to be flexible and easily generalizable to many scenarios using different calibrations and to diseases other than malaria. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-018-3025-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-61149062018-09-04 Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission Barbosa, Susana Kay, Katherine Chitnis, Nakul Hastings, Ian M. Parasit Vectors Research BACKGROUND: Current strategies to control mosquito-transmitted infections use insecticides targeted at various stages of the mosquito life-cycle. Control is increasingly compromised by the evolution of insecticide resistance but there is little quantitative understanding of its impact on control effectiveness. We developed a computational approach that incorporates the stage-structured mosquito life-cycle and allows tracking of insecticide resistant genotypes. This approach makes it possible to simultaneously investigate: (i) the population dynamics of mosquitoes throughout their whole life-cycle; (ii) the impact of common vector control interventions on disease transmission; (iii) how these interventions drive the spread of insecticide resistance; and (iv) the impact of resistance once it has arisen and, in particular, whether it is sufficient for malaria transmission to resume. The model consists of a system of difference equations that tracks the immature (eggs, larvae and pupae) and adult stages, for males and females separately, and incorporates density-dependent regulation of mosquito larvae in breeding sites. RESULTS: We determined a threshold level of mosquitoes below which transmission of malaria is interrupted. It is based on a classic Ross-Macdonald derivation of the malaria basic reproductive number (R(0)) and may be used to assess the effectiveness of different control strategies in terms of whether they are likely to interrupt disease transmission. We simulated different scenarios of insecticide deployment by changing key parameters in the model to explore the comparative impact of insecticide treated nets, indoor residual spraying and larvicides. CONCLUSIONS: Our simulated results suggest that relatively low degrees of resistance (in terms of reduced mortality following insecticide contact) can induce failure of interventions, and the rate of spread of resistance is faster when insecticides target the larval stages. The optimal disease control strategy depends on vector species demography and local environmental conditions but, in our illustrative parametrisation, targeting larval stages achieved the greatest reduction of the adult population, followed by targeting of non-host-seeking females, as provided by indoor residual spraying. Our approach is designed to be flexible and easily generalizable to many scenarios using different calibrations and to diseases other than malaria. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-018-3025-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-08-28 /pmc/articles/PMC6114906/ /pubmed/30153869 http://dx.doi.org/10.1186/s13071-018-3025-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Barbosa, Susana
Kay, Katherine
Chitnis, Nakul
Hastings, Ian M.
Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title_full Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title_fullStr Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title_full_unstemmed Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title_short Modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
title_sort modelling the impact of insecticide-based control interventions on the evolution of insecticide resistance and disease transmission
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6114906/
https://www.ncbi.nlm.nih.gov/pubmed/30153869
http://dx.doi.org/10.1186/s13071-018-3025-z
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