Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/15639
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dc.contributor.authorKhormi, Hassanen
dc.contributor.authorKumar, Laliten
dc.contributor.authorElzahrany, Ramzeen
dc.date.accessioned2014-09-09T15:03:00Z-
dc.date.issued2013-
dc.identifier.citationJournal of Earth Science & Climatic Change, 5(1), p. 1-8en
dc.identifier.issn2157-7617en
dc.identifier.urihttps://hdl.handle.net/1959.11/15639-
dc.description.abstractConsiderable interest exists in confirming that meteorological variables may play determinant roles in dengue vector abundance. The principle vector for dengue is 'Aedes aegypti'. Dengue Fever has been considered the most important vector-borne viral disease in Jeddah, Saudi Arabia, and is susceptible to climate variability. The aim of this study is to describe the association between adult female 'Aedes aegypti' mosquitoes and meteorological variables and to develop models for predicting the mosquito abundance using Pearson's correlation and regression analyses. Our results show that mosquitoes have the highest correlation with temperature at lag 0 time and relative humidity at lag 5 weeks. The highest two correlations were found between the mosquitoes and minimum temperature (r=-0.57) and maximum relative humidity (r=0.46). Two models were created based on the regression analysis results. The first model shows that 86% of mosquito values were within the upper and lower limits of agreement. The second model shows that 94% of the values were within the limits of agreement. The study findings could contribute to the forecasting of mosquito abundance peaks and subsequently guide a plan for mosquito control operations ahead of time that would help to minimize the outbreak of dengue occurrence and prevent the spread of dengue infections.en
dc.languageenen
dc.publisherOmics Publishing Groupen
dc.relation.ispartofJournal of Earth Science & Climatic Changeen
dc.titleRegression Model for Predicting Adult Female 'Aedes aegypti' Based on Meteorological Variables: A Case Study of Jeddah, Saudi Arabiaen
dc.typeJournal Articleen
dc.identifier.doi10.4172/2157-7617.1000168en
dc.subject.keywordsGeospatial Information Systemsen
dc.subject.keywordsEnvironmental Monitoringen
dc.subject.keywordsPhotogrammetry and Remote Sensingen
local.contributor.firstnameHassanen
local.contributor.firstnameLaliten
local.contributor.firstnameRamzeen
local.subject.for2008090903 Geospatial Information Systemsen
local.subject.for2008090905 Photogrammetry and Remote Sensingen
local.subject.for2008050206 Environmental Monitoringen
local.subject.seo2008960411 Control of Pests, Diseases and Exotic Species in Urban and Industrial Environmentsen
local.subject.seo2008960604 Environmental Management Systemsen
local.subject.seo2008960405 Control of Pests, Diseases and Exotic Species at Regional or Larger Scalesen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emailhkhormi2@une.edu.auen
local.profile.emaillkumar@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20140905-164111en
local.publisher.placeUnited States of Americaen
local.identifier.runningnumber1000168en
local.format.startpage1en
local.format.endpage8en
local.peerreviewedYesen
local.identifier.volume5en
local.identifier.issue1en
local.title.subtitleA Case Study of Jeddah, Saudi Arabiaen
local.contributor.lastnameKhormien
local.contributor.lastnameKumaren
local.contributor.lastnameElzahranyen
dc.identifier.staffune-id:hkhormi2en
dc.identifier.staffune-id:lkumaren
dc.identifier.staffune-id:relzahraen
local.profile.orcid0000-0002-9205-756Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:15875en
local.identifier.handlehttps://hdl.handle.net/1959.11/15639en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleRegression Model for Predicting Adult Female 'Aedes aegypti' Based on Meteorological Variablesen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorKhormi, Hassanen
local.search.authorKumar, Laliten
local.search.authorElzahrany, Ramzeen
local.uneassociationUnknownen
local.year.published2013-
local.subject.for2020401302 Geospatial information systems and geospatial data modellingen
local.subject.for2020401304 Photogrammetry and remote sensingen
local.subject.for2020410599 Pollution and contamination not elsewhere classifieden
local.subject.seo2020180204 Control of pests, diseases and exotic species in coastal and estuarine environmentsen
local.subject.seo2020180302 Control of pests, diseases and exotic species in fresh, ground and surface wateren
local.subject.seo2020180602 Control of pests, diseases and exotic species in terrestrial environmentsen
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School of Environmental and Rural Science
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