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Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models / Tong Zhang in Transactions in GIS, vol 25 n° 6 (December 2021)  

Public [article]  inTransactions in GIS > vol 25 n° 6 (December 2021) . - pp 3025 - 3047 Titre : Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models Type de document : Article/Communication Auteurs : Tong Zhang, Auteur ; Jing Li, Auteur Année de publication : 2021 Article en page(s) : pp 3025 - 3047 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] Colorado (Etats-Unis) [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] maladie virale [Termes IGN] mobilité territoriale [Termes IGN] modèle de simulation [Termes IGN] modélisation spatio-temporelle [Termes IGN] outil d'aide à la décision [Termes IGN] quartier [Termes IGN] réseau de transport [Termes IGN] risque sanitaire [Termes IGN] surveillance sanitaire Résumé : (Auteur) In order to find useful intervention strategies for the novel coronavirus (COVID-19), it is vital to understand how the disease spreads. In this study, we address the modeling of COVID-19 spread across space and time, which facilitates understanding of the pandemic. We propose a hybrid data-driven learning approach to capture the mobility-related spreading mechanism of infectious diseases, utilizing multi-sourced mobility and attributed data. This study develops a visual analytic approach that identifies and depicts the strength of the transmission pathways of COVID-19 between areal units by integrating data-driven deep learning and compartmental epidemic models, thereby engaging stakeholders (e.g., public health officials, managers from transportation agencies) to make informed intervention decisions and enable public messaging. A case study in the state of Colorado, USA was performed to demonstrate the applicability of the proposed transmission modeling approach in understanding the spatio-temporal spread of COVID-19 at the neighborhood level. Transmission path maps are presented and analyzed, demonstrating their utility in evaluating the effects of mitigation measures. In addition, integrated embeddings also support daily prediction of infected cases and role analysis of each area unit during the transmission of the virus. Numéro de notice : A2021-932 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12803 Date de publication en ligne : 16/07/2021 En ligne : https://doi.org/10.1111/tgis.12803 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99447 [article]

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]

Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)  

Public [article]  inAnnals of GIS > vol 26 n° 3 (July 2020) . - pp 219 - 226 Titre : Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases Type de document : Article/Communication Auteurs : Meifang Li, Auteur ; Xun Shi, Auteur ; Xia Li, Auteur Année de publication : 2020 Article en page(s) : pp 219 - 226 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] épidémie [Termes IGN] historique des données [Termes IGN] modèle orienté objet [Termes IGN] modélisation spatio-temporelle [Termes IGN] risque sanitaire [Termes IGN] système d'information géographique [Termes IGN] transmissibilité Résumé : (auteur) In the past several decades, epidemic modelling for communicable diseases has experienced transitions from treating the entire study area as a whole to addressing spatial variation within the area, and from targeting the entire population to incorporating characteristics of categorized subpopulations and finally going down to the individual level. These transitions have been first driven by the recognition that generalizations of space and population in conventional epidemic modelling may have hampered the effectiveness of the modelling; they then have been supported by increasingly available data that allow depiction of detailed spatiotemporal characteristics of an epidemic, as well as those characteristics of the environment in both human and natural aspects; and finally they have been facilitated by developments in geographic information science, data science, computer science, and computing technologies. Based on a review of a variety of recently developed communicable disease models, we explicitly put forward the notions of spatialization and individualization in this area, and point out that the integration of the two is the future of communicable disease modelling. We also point out that in this area models based on the object conceptualization are good at modelling spatiotemporal process, whereas models based on the field conceptualization are good at representing spatialized information. We propose a procedural framework of epidemic modelling that implements the integration of individualization and spatialization, integration of object-based process and field-based representation, and integration of modelling that retrospectively traces infection relationships based on historical patient data and modelling that prospectively predicts such relationships of future epidemics. Numéro de notice : A2020-581 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2020.1768438 Date de publication en ligne : 25/05/2020 En ligne : https://doi.org/10.1080/19475683.2020.1768438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95903 [article]

Estimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 18 p. Titre : Estimating and interpreting fine-scale gridded population using random forest regression and multisource data Type de document : Article/Communication Auteurs : Yun Zhou, Auteur ; Mingguo Ma, Auteur ; Kaifang Shi, Auteur ; Zhenyu Peng, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] cartographie urbaine [Termes IGN] catastrophe naturelle [Termes IGN] Chine [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] densité de population [Termes IGN] données maillées [Termes IGN] données multisources [Termes IGN] migration humaine [Termes IGN] modèle numérique de surface [Termes IGN] point d'intérêt [Termes IGN] population urbaine [Termes IGN] risque sanitaire [Termes IGN] secours d'urgence [Termes IGN] zone urbaine Résumé : (auteur) Gridded population results at a fine resolution are important for optimizing the allocation of resources and researching population migration. For example, the data are crucial for epidemic control and natural disaster relief. In this study, the random forest model was applied to multisource data to estimate the population distribution in impervious areas at a 30 m spatial resolution in Chongqing, Southwest China. The community population data from the Chinese government were used to validate the estimation accuracy. Compared with the other regression techniques, the random forest regression method produced more accurate results (R2 = 0.7469, RMSE = 2785.04 and p Numéro de notice : A2020-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060369 Date de publication en ligne : 03/06/2020 En ligne : https://doi.org/10.3390/ijgi9060369 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95155 [article]

Assessment of malaria hazard, vulnerability, and risks in Dire Dawa City Administration of eastern Ethiopia using GIS and remote sensing / Abdinasir Moha in Applied geomatics, vol 12 n° 1 (April 2020)  

Public [article]  inApplied geomatics > vol 12 n° 1 (April 2020) . - pp 15 - 22 Titre : Assessment of malaria hazard, vulnerability, and risks in Dire Dawa City Administration of eastern Ethiopia using GIS and remote sensing Type de document : Article/Communication Auteurs : Abdinasir Moha, Auteur ; Molla Maru, Auteur ; Tebarek Lika, Auteur Année de publication : 2020 Article en page(s) : pp 15 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] ArcGIS [Termes IGN] cartographie des risques [Termes IGN] changement climatique [Termes IGN] Ethiopie [Termes IGN] image infrarouge [Termes IGN] image Landsat-OLI [Termes IGN] maladie parasitaire [Termes IGN] risque sanitaire [Termes IGN] système d'information géographique [Termes IGN] utilisation du sol Résumé : (auteur) Malaria is a serious vector-borne disease affecting a greater proportion of the world’s population. Sub-Saharan Africa carries a disproportionately high share of the global malaria burden. Ethiopia is generally considered a low-to-moderate malaria transmission intensity country. However, the health sector in Ethiopia is greatly affected by climate change, which has profound consequences on the transmission cycles of vector-borne infectious diseases like malaria. The main objective of the study was to assess the spatial distribution of malaria hazard, vulnerability, and risk areas in Dire Dawa City Administration. GIS and remote-sensing in general and multi-criteria evaluation (MCE) in particular was used for assessing and mapping malaria hazard, risk, and vulnerable areas in Dire Dawa City Administration based on the data collected from various sources. The malaria hazard map of the study area labeled 0.6% of the region as low-hazard level, 79.7% moderate, 19.7% high, and 0.1% very low. Results of malaria vulnerability analysis reveal that about 23%, 73%, and 4% of the region was found to be vulnerable to malaria risk at very high, high, and low levels, respectively. The malaria risk map classifies 80% of the region as a moderate malaria-risk area and 20% as high malaria-risk area. This assessment advocates that the GIS and remote-sensing technology as tools can be used to provide timely information on malaria hazard, vulnerability, and risk areas for planning and taking measures at various levels ranging from early warning, monitoring, and control to prevention against malaria epidemics in a resource-efficient and cost-effective way. Numéro de notice : A2020-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-019-00276-5 Date de publication en ligne : 17/07/2019 En ligne : https://doi.org/10.1007/s12518-019-00276-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95862 [article]

A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data / Haiyan Tao in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

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Guide de gestion des crises sanitaires en forêt / Louise Brunier (2020)

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Epidémiologie et géographie / Marc Souris (2019)

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Adapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018) 

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Rapport 2013-2014 de la déléguée aux risques majeurs / Direction générale de la prévention des risques (2015)  

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Conception et réalisation d'un atlas relatif au parcours de santé des personnes âgées : une approche comparative multisite et multiéchelle / Constance Lecomte (2014)

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Cartes en mains contre Lili la tigresse / Françoise de Blomac in DécryptaGéo le mag, n° 152 (01/12/2013)

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Dracunculiasis, proximity, and risk: Analyzing the location of Guinea worm disease in a GIS / Nataniel Royal in Transactions in GIS, vol 17 n° 2 (April 2013)  

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Les impacts du changement climatique en Aquitaine / Hervé Le Treut (2013)

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Mapping malaria severity zones with Nigeriasat-1 incorporated into geographical information system / E. Ogunbadewa in Geocarto international, vol 27 n° 7 (November 2012)  

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