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Evaluation of different deployment strategies for larviciding to control malaria: a simulation study

BACKGROUND: Larviciding against malaria vectors in Africa has been limited to indoor residual spraying and insecticide-treated nets, but is increasingly being considered by some countries as a complementary strategy. However, despite progress towards improved larvicides and new tools for mapping or...

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Autores principales: Runge, Manuela, Mapua, Salum, Nambunga, Ismail, Smith, Thomas A., Chitnis, Nakul, Okumu, Fredros, Pothin, Emilie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314573/
https://www.ncbi.nlm.nih.gov/pubmed/34315473
http://dx.doi.org/10.1186/s12936-021-03854-4
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author Runge, Manuela
Mapua, Salum
Nambunga, Ismail
Smith, Thomas A.
Chitnis, Nakul
Okumu, Fredros
Pothin, Emilie
author_facet Runge, Manuela
Mapua, Salum
Nambunga, Ismail
Smith, Thomas A.
Chitnis, Nakul
Okumu, Fredros
Pothin, Emilie
author_sort Runge, Manuela
collection PubMed
description BACKGROUND: Larviciding against malaria vectors in Africa has been limited to indoor residual spraying and insecticide-treated nets, but is increasingly being considered by some countries as a complementary strategy. However, despite progress towards improved larvicides and new tools for mapping or treating mosquito-breeding sites, little is known about the optimal deployment strategies for larviciding in different transmission and seasonality settings. METHODS: A malaria transmission model, OpenMalaria, was used to simulate varying larviciding strategies and their impact on host-seeking mosquito densities, entomological inoculation rate (EIR) and malaria prevalence. Variations in coverage, duration, frequency, and timing of larviciding were simulated for three transmission intensities and four transmission seasonality profiles. Malaria transmission was assumed to follow rainfall with a lag of one month. Theoretical sub-Saharan African settings with Anopheles gambiae as the dominant vector were chosen to explore impact. Relative reduction compared to no larviciding was predicted for each indicator during the simulated larviciding period. RESULTS: Larviciding immediately reduced the predicted host-seeking mosquito densities and EIRs to a maximum that approached or exceeded the simulated coverage. Reduction in prevalence was delayed by approximately one month. The relative reduction in prevalence was up to four times higher at low than high transmission. Reducing larviciding frequency (i.e., from every 5 to 10 days) resulted in substantial loss in effectiveness (54, 45 and 53% loss of impact for host-seeking mosquito densities, EIR and prevalence, respectively). In seasonal settings the most effective timing of larviciding was during or at the beginning of the rainy season and least impactful during the dry season, assuming larviciding deployment for four months. CONCLUSION: The results highlight the critical role of deployment strategies on the impact of larviciding. Overall, larviciding would be more effective in settings with low and seasonal transmission, and at the beginning and during the peak densities of the target species populations. For maximum impact, implementers should consider the practical ranges of coverage, duration, frequency, and timing of larviciding in their respective contexts. More operational data and improved calibration would enable models to become a practical tool to support malaria control programmes in developing larviciding strategies that account for the diversity of contexts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-03854-4.
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spelling pubmed-83145732021-07-28 Evaluation of different deployment strategies for larviciding to control malaria: a simulation study Runge, Manuela Mapua, Salum Nambunga, Ismail Smith, Thomas A. Chitnis, Nakul Okumu, Fredros Pothin, Emilie Malar J Research BACKGROUND: Larviciding against malaria vectors in Africa has been limited to indoor residual spraying and insecticide-treated nets, but is increasingly being considered by some countries as a complementary strategy. However, despite progress towards improved larvicides and new tools for mapping or treating mosquito-breeding sites, little is known about the optimal deployment strategies for larviciding in different transmission and seasonality settings. METHODS: A malaria transmission model, OpenMalaria, was used to simulate varying larviciding strategies and their impact on host-seeking mosquito densities, entomological inoculation rate (EIR) and malaria prevalence. Variations in coverage, duration, frequency, and timing of larviciding were simulated for three transmission intensities and four transmission seasonality profiles. Malaria transmission was assumed to follow rainfall with a lag of one month. Theoretical sub-Saharan African settings with Anopheles gambiae as the dominant vector were chosen to explore impact. Relative reduction compared to no larviciding was predicted for each indicator during the simulated larviciding period. RESULTS: Larviciding immediately reduced the predicted host-seeking mosquito densities and EIRs to a maximum that approached or exceeded the simulated coverage. Reduction in prevalence was delayed by approximately one month. The relative reduction in prevalence was up to four times higher at low than high transmission. Reducing larviciding frequency (i.e., from every 5 to 10 days) resulted in substantial loss in effectiveness (54, 45 and 53% loss of impact for host-seeking mosquito densities, EIR and prevalence, respectively). In seasonal settings the most effective timing of larviciding was during or at the beginning of the rainy season and least impactful during the dry season, assuming larviciding deployment for four months. CONCLUSION: The results highlight the critical role of deployment strategies on the impact of larviciding. Overall, larviciding would be more effective in settings with low and seasonal transmission, and at the beginning and during the peak densities of the target species populations. For maximum impact, implementers should consider the practical ranges of coverage, duration, frequency, and timing of larviciding in their respective contexts. More operational data and improved calibration would enable models to become a practical tool to support malaria control programmes in developing larviciding strategies that account for the diversity of contexts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12936-021-03854-4. BioMed Central 2021-07-27 /pmc/articles/PMC8314573/ /pubmed/34315473 http://dx.doi.org/10.1186/s12936-021-03854-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Runge, Manuela
Mapua, Salum
Nambunga, Ismail
Smith, Thomas A.
Chitnis, Nakul
Okumu, Fredros
Pothin, Emilie
Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title_full Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title_fullStr Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title_full_unstemmed Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title_short Evaluation of different deployment strategies for larviciding to control malaria: a simulation study
title_sort evaluation of different deployment strategies for larviciding to control malaria: a simulation study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314573/
https://www.ncbi.nlm.nih.gov/pubmed/34315473
http://dx.doi.org/10.1186/s12936-021-03854-4
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