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Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria
Arbovirus transmission by Aedes mosquitoes has long been a significant problem in Africa. In West Africa, Aedes vector management faces significant challenges; lack of recent Aedes distributional data and potential distributional modeling hinder effective vector control and pose serious public healt...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498000/ https://www.ncbi.nlm.nih.gov/pubmed/34646952 http://dx.doi.org/10.1016/j.parepi.2021.e00225 |
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author | Omar, K. Thabet, H.S. TagEldin, R.A. Asadu, C.C. Chukwuekezie, O.C. Ochu, J.C. Dogunro, F.A. Nwangwu, U.C. Onwude, O.C. Ezihe, E.K. Anioke, C.C. Arimoto, H. |
author_facet | Omar, K. Thabet, H.S. TagEldin, R.A. Asadu, C.C. Chukwuekezie, O.C. Ochu, J.C. Dogunro, F.A. Nwangwu, U.C. Onwude, O.C. Ezihe, E.K. Anioke, C.C. Arimoto, H. |
author_sort | Omar, K. |
collection | PubMed |
description | Arbovirus transmission by Aedes mosquitoes has long been a significant problem in Africa. In West Africa, Aedes vector management faces significant challenges; lack of recent Aedes distributional data and potential distributional modeling hinder effective vector control and pose serious public health issues. In this study, larval and adult mosquitoes were collected from four study sites in Enugu State, Nigeria every other month between November 2017 and September 2018. A total number of 2997 Aedes mosquitoes were collected and identified, and 59 positive field occurrence points for both Aedes adult and larvae were recorded. A total of 18 positive occurrence points were used for modeling. Ecological Niche Models (ENMs) were used to estimate the current geographic distribution of Aedes species (spp.) in Enugu State, south-east Nigeria, and mosquito presence was used as a proxy for predicting risk of disease transmission. Maximum Entropy distribution modeling or “MaxEnt” was used for predicting the potential suitable habitats, using a portion of the occurrence records. A total of 23 environmental variables (19 bioclimatic and four topographic) were used to model the potential geographical distribution area under current climatic conditions. The most suitable habitat for Aedes spp. was predicted in the northern, central, and southeastern parts of Enugu State with some extensions in Anambra, Delta, and Edo States in the west, and Ebonyi State in the east. Seasonal temperature, precipitation of the wettest month, mean monthly temperature range, elevation, and precipitation of the driest months were the highest estimated main variable contributions associated with the distribution of Aedes spp. We found that Aedes spp. prefer to be situated in environmental conditions where precipitation of wettest month ranged from 265 to 330 mm, precipitation of driest quarter ranged from 25 to 75 mm while precipitation of wettest quarter ranged from 650 to 950 mm. Aedes mosquitoes, such as Ae. aegypti and Ae. albopictus, pose a significant threat to human health, hence, the results of this study will help decision makers to monitor the distribution of these species and establish a management plan for future national mosquito surveillance and control programs in Nigeria. |
format | Online Article Text |
id | pubmed-8498000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-84980002021-10-12 Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria Omar, K. Thabet, H.S. TagEldin, R.A. Asadu, C.C. Chukwuekezie, O.C. Ochu, J.C. Dogunro, F.A. Nwangwu, U.C. Onwude, O.C. Ezihe, E.K. Anioke, C.C. Arimoto, H. Parasite Epidemiol Control Short Communication Arbovirus transmission by Aedes mosquitoes has long been a significant problem in Africa. In West Africa, Aedes vector management faces significant challenges; lack of recent Aedes distributional data and potential distributional modeling hinder effective vector control and pose serious public health issues. In this study, larval and adult mosquitoes were collected from four study sites in Enugu State, Nigeria every other month between November 2017 and September 2018. A total number of 2997 Aedes mosquitoes were collected and identified, and 59 positive field occurrence points for both Aedes adult and larvae were recorded. A total of 18 positive occurrence points were used for modeling. Ecological Niche Models (ENMs) were used to estimate the current geographic distribution of Aedes species (spp.) in Enugu State, south-east Nigeria, and mosquito presence was used as a proxy for predicting risk of disease transmission. Maximum Entropy distribution modeling or “MaxEnt” was used for predicting the potential suitable habitats, using a portion of the occurrence records. A total of 23 environmental variables (19 bioclimatic and four topographic) were used to model the potential geographical distribution area under current climatic conditions. The most suitable habitat for Aedes spp. was predicted in the northern, central, and southeastern parts of Enugu State with some extensions in Anambra, Delta, and Edo States in the west, and Ebonyi State in the east. Seasonal temperature, precipitation of the wettest month, mean monthly temperature range, elevation, and precipitation of the driest months were the highest estimated main variable contributions associated with the distribution of Aedes spp. We found that Aedes spp. prefer to be situated in environmental conditions where precipitation of wettest month ranged from 265 to 330 mm, precipitation of driest quarter ranged from 25 to 75 mm while precipitation of wettest quarter ranged from 650 to 950 mm. Aedes mosquitoes, such as Ae. aegypti and Ae. albopictus, pose a significant threat to human health, hence, the results of this study will help decision makers to monitor the distribution of these species and establish a management plan for future national mosquito surveillance and control programs in Nigeria. Elsevier 2021-09-15 /pmc/articles/PMC8498000/ /pubmed/34646952 http://dx.doi.org/10.1016/j.parepi.2021.e00225 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Short Communication Omar, K. Thabet, H.S. TagEldin, R.A. Asadu, C.C. Chukwuekezie, O.C. Ochu, J.C. Dogunro, F.A. Nwangwu, U.C. Onwude, O.C. Ezihe, E.K. Anioke, C.C. Arimoto, H. Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title | Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title_full | Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title_fullStr | Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title_full_unstemmed | Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title_short | Ecological niche modeling for predicting the potential geographical distribution of Aedes species (Diptera: Culicidae): A case study of Enugu State, Nigeria |
title_sort | ecological niche modeling for predicting the potential geographical distribution of aedes species (diptera: culicidae): a case study of enugu state, nigeria |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498000/ https://www.ncbi.nlm.nih.gov/pubmed/34646952 http://dx.doi.org/10.1016/j.parepi.2021.e00225 |
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