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Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia

BACKGROUND: The mosquito, Culex tritaeniorhynchus Giles is a prevalent and confirmed Rift Valley Fever virus (RVFV) vector. This vector, in association with Aedimorphus arabiensis (Patton), was responsible for causing the outbreak of 2000 in Jazan Province, Saudi Arabia. METHODOLOGY/PRINCIPAL FINDIN...

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Autores principales: Sallam, Mohamed F., Al Ahmed, Azzam M., Abdel-Dayem, Mahmoud S., Abdullah, Mohamed A. R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3675080/
https://www.ncbi.nlm.nih.gov/pubmed/23762424
http://dx.doi.org/10.1371/journal.pone.0065786
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author Sallam, Mohamed F.
Al Ahmed, Azzam M.
Abdel-Dayem, Mahmoud S.
Abdullah, Mohamed A. R.
author_facet Sallam, Mohamed F.
Al Ahmed, Azzam M.
Abdel-Dayem, Mahmoud S.
Abdullah, Mohamed A. R.
author_sort Sallam, Mohamed F.
collection PubMed
description BACKGROUND: The mosquito, Culex tritaeniorhynchus Giles is a prevalent and confirmed Rift Valley Fever virus (RVFV) vector. This vector, in association with Aedimorphus arabiensis (Patton), was responsible for causing the outbreak of 2000 in Jazan Province, Saudi Arabia. METHODOLOGY/PRINCIPAL FINDINGS: Larval occurrence records and a total of 19 bioclimatic and three topographic layers imported from Worldclim Database were used to predict the larval suitable breeding habitats for this vector in Jazan Province using ArcGIS ver.10 and MaxEnt modeling program. Also, a supervised land cover classification from SPOT5 imagery was developed to assess the land cover distribution within the suitable predicted habitats. Eleven bioclimatic and slope attributes were found to be the significant predictors for this larval suitable breeding habitat. Precipitation and temperature were strong predictors of mosquito distribution. Among six land cover classes, the linear regression model (LM) indicated wet muddy substrate is significantly associated with high-very high suitable predicted habitats (R(2) = 73.7%, P<0.05). Also, LM indicated that total dissolved salts (TDS) was a significant contributor (R(2) = 23.9%, P<0.01) in determining mosquito larval abundance. CONCLUSION/SIGNIFICANCE: This model is a first step in understanding the spatial distribution of Cx. tritaeniorhynchus and consequently the risk of RVFV in Saudi Arabia and to assist in planning effective mosquito surveillance and control programs by public health personnel and researchers.
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spelling pubmed-36750802013-06-12 Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia Sallam, Mohamed F. Al Ahmed, Azzam M. Abdel-Dayem, Mahmoud S. Abdullah, Mohamed A. R. PLoS One Research Article BACKGROUND: The mosquito, Culex tritaeniorhynchus Giles is a prevalent and confirmed Rift Valley Fever virus (RVFV) vector. This vector, in association with Aedimorphus arabiensis (Patton), was responsible for causing the outbreak of 2000 in Jazan Province, Saudi Arabia. METHODOLOGY/PRINCIPAL FINDINGS: Larval occurrence records and a total of 19 bioclimatic and three topographic layers imported from Worldclim Database were used to predict the larval suitable breeding habitats for this vector in Jazan Province using ArcGIS ver.10 and MaxEnt modeling program. Also, a supervised land cover classification from SPOT5 imagery was developed to assess the land cover distribution within the suitable predicted habitats. Eleven bioclimatic and slope attributes were found to be the significant predictors for this larval suitable breeding habitat. Precipitation and temperature were strong predictors of mosquito distribution. Among six land cover classes, the linear regression model (LM) indicated wet muddy substrate is significantly associated with high-very high suitable predicted habitats (R(2) = 73.7%, P<0.05). Also, LM indicated that total dissolved salts (TDS) was a significant contributor (R(2) = 23.9%, P<0.01) in determining mosquito larval abundance. CONCLUSION/SIGNIFICANCE: This model is a first step in understanding the spatial distribution of Cx. tritaeniorhynchus and consequently the risk of RVFV in Saudi Arabia and to assist in planning effective mosquito surveillance and control programs by public health personnel and researchers. Public Library of Science 2013-06-06 /pmc/articles/PMC3675080/ /pubmed/23762424 http://dx.doi.org/10.1371/journal.pone.0065786 Text en © 2013 Sallam et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Sallam, Mohamed F.
Al Ahmed, Azzam M.
Abdel-Dayem, Mahmoud S.
Abdullah, Mohamed A. R.
Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title_full Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title_fullStr Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title_full_unstemmed Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title_short Ecological Niche Modeling and Land Cover Risk Areas for Rift Valley Fever Vector, Culex tritaeniorhynchus Giles in Jazan, Saudi Arabia
title_sort ecological niche modeling and land cover risk areas for rift valley fever vector, culex tritaeniorhynchus giles in jazan, saudi arabia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3675080/
https://www.ncbi.nlm.nih.gov/pubmed/23762424
http://dx.doi.org/10.1371/journal.pone.0065786
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