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Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan / Muhammad Imran in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 197 - 211 Titre : Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan Type de document : Article/Communication Auteurs : Muhammad Imran, Auteur ; Yasra Hamid, Auteur ; Abeer Mazher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 197 - 211 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cartographie des risques [Termes IGN] diptère [Termes IGN] image Landsat [Termes IGN] maladie tropicale [Termes IGN] modélisation spatiale [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Pakistan [Termes IGN] régression géographiquement pondérée [Termes IGN] régression logistique [Termes IGN] risque sanitaire [Termes IGN] série temporelle [Termes IGN] zone intertropicale [Termes IGN] zone urbaine Résumé : (auteur) The study objective is to predict the epidemiological impact of dengue fever arbovirosis in urban tropical areas of Pakistan. To do so, we used the GPS-based data of the Aedes larvae collected during 2014–2015 in Lahore. We developed a Geographically Weighted Logistic Regression (GWLR) model for Geospatially predicting larvae presence or absence in Lahore. Data on rainfall, temperature are included along with time series of the normalized difference vegetation index (NDVI) derived from Landsat imagery. We observed a high spatial variability of the GWLR parameter estimates of these variables in the study area. The GWLR model significantly (R2a = 0.78) explained the presence or absence of Aedes larvae with temperature, rainfall and NDVI variables in South and Southeast of the study area. In the North and North-West, however, GWLR relationships were observed weak in highly populated areas. Interpolating GWLR coefficients generate more accurate maps of Aedes larvae presence or absence. Numéro de notice : A2021-474 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1614100 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1080/10106049.2019.1614100 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96932 [article]