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An agent-based model of the population dynamics of Anopheles gambiae
BACKGROUND: Agent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypoth...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4233045/ https://www.ncbi.nlm.nih.gov/pubmed/25373418 http://dx.doi.org/10.1186/1475-2875-13-424 |
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author | Arifin, SM Niaz Zhou, Ying Davis, Gregory J Gentile, James E Madey, Gregory R Collins, Frank H |
author_facet | Arifin, SM Niaz Zhou, Ying Davis, Gregory J Gentile, James E Madey, Gregory R Collins, Frank H |
author_sort | Arifin, SM Niaz |
collection | PubMed |
description | BACKGROUND: Agent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypothetical vector control interventions (HVCIs) are implemented to target specific activities in the mosquito life cycle, and their impacts are evaluated. METHODS: The core model is described in terms of the complete An. gambiae mosquito life cycle. Primary features include the development and mortality rates in different aquatic and adult stages, the aquatic habitats and oviposition. The density- and age-dependent larval and adult mortality rates (vector senescence) allow the model to capture the age-dependent aspects of the mosquito biology. Details of hypothetical interventions are also described. RESULTS: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles. Thus, these stages may be the most effective points of target for newly developed and novel interventions. A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages. It is emphasized that although the model described in this paper is designed specifically around the mosquito An. gambiae, it could effectively apply to many other major malaria vectors in the world (including the three most efficient nominal anopheline species An. gambiae, Anopheles coluzzii and Anopheles arabiensis) by incorporating a variety of factors (seasonality cycles, rainfall, humidity, etc.). Thus, the model can essentially be treated as a generic Anopheles model, offering an excellent framework for such extensions. The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques). |
format | Online Article Text |
id | pubmed-4233045 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42330452014-11-17 An agent-based model of the population dynamics of Anopheles gambiae Arifin, SM Niaz Zhou, Ying Davis, Gregory J Gentile, James E Madey, Gregory R Collins, Frank H Malar J Research BACKGROUND: Agent-based models (ABMs) have been used to model the behaviour of individual mosquitoes and other aspects of malaria. In this paper, a conceptual entomological model of the population dynamics of Anopheles gambiae and the agent-based implementations derived from it are described. Hypothetical vector control interventions (HVCIs) are implemented to target specific activities in the mosquito life cycle, and their impacts are evaluated. METHODS: The core model is described in terms of the complete An. gambiae mosquito life cycle. Primary features include the development and mortality rates in different aquatic and adult stages, the aquatic habitats and oviposition. The density- and age-dependent larval and adult mortality rates (vector senescence) allow the model to capture the age-dependent aspects of the mosquito biology. Details of hypothetical interventions are also described. RESULTS: Results show that with varying coverage and temperature ranges, the hypothetical interventions targeting the gonotrophic cycle stages produce higher impacts than the rest in reducing the potentially infectious female (PIF) mosquito populations, due to their multi-hour mortality impacts and their applicability at multiple gonotrophic cycles. Thus, these stages may be the most effective points of target for newly developed and novel interventions. A combined HVCI with low coverage can produce additive synergistic impacts and can be more effective than isolated HVCIs with comparatively higher coverages. It is emphasized that although the model described in this paper is designed specifically around the mosquito An. gambiae, it could effectively apply to many other major malaria vectors in the world (including the three most efficient nominal anopheline species An. gambiae, Anopheles coluzzii and Anopheles arabiensis) by incorporating a variety of factors (seasonality cycles, rainfall, humidity, etc.). Thus, the model can essentially be treated as a generic Anopheles model, offering an excellent framework for such extensions. The utility of the core model has also been demonstrated by several other applications, each of which investigates well-defined biological research questions across a variety of dimensions (including spatial models, insecticide resistance, and sterile insect techniques). BioMed Central 2014-11-05 /pmc/articles/PMC4233045/ /pubmed/25373418 http://dx.doi.org/10.1186/1475-2875-13-424 Text en © Arifin et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Arifin, SM Niaz Zhou, Ying Davis, Gregory J Gentile, James E Madey, Gregory R Collins, Frank H An agent-based model of the population dynamics of Anopheles gambiae |
title | An agent-based model of the population dynamics of Anopheles gambiae |
title_full | An agent-based model of the population dynamics of Anopheles gambiae |
title_fullStr | An agent-based model of the population dynamics of Anopheles gambiae |
title_full_unstemmed | An agent-based model of the population dynamics of Anopheles gambiae |
title_short | An agent-based model of the population dynamics of Anopheles gambiae |
title_sort | agent-based model of the population dynamics of anopheles gambiae |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4233045/ https://www.ncbi.nlm.nih.gov/pubmed/25373418 http://dx.doi.org/10.1186/1475-2875-13-424 |
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