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International Journal of Health Geographics (2008) 7:24, May 22, 2008 Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change. In this study, we developed an algorithm for predicting the occurrence of I. scapularis populations in Canada.

International Journal of Health Geographics (2008) 7:24, May 22, 2008 Risk maps for range expansion of the Lyme disease vector, Ixodes scapularis, in Canada now and with climate change

The algorithm predicted with reasonable accuracy the occurrence of the small number of I. scapularis populations that were known in Canada prior to this study. A warming climate was considered to cause changes in the speed of bird migration and distances of dispersion of ticks by migrating birds, and changes in the geographic range of territory with a climate warm enough for the ticks to complete their lifecycle and establish populations.

With this information, the algorithm was then used as a simple model to predict the progression of I. scapularis as it spreads across Canada as the climate warms, given two scenarios for the current potential occurrence of I. scapularis populations in Canada. There were of course many assumptions in this process. Further studies are required to expand our current knowledge of the suitability of habitat for I. scapularis in Canada. PLOS 20/04/07 Risk Maps for the Spread of Highly Pathogenic Avian Influenza in Poultry. Abstract Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens.

PLOS 20/04/07 Risk Maps for the Spread of Highly Pathogenic Avian Influenza in Poultry

Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner.

A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. Author Summary Editor: Lauren A. Received: October 25, 2006; Accepted: March 1, 2007; Published: April 20, 2007. DRIEE ILE DE FRANCE - Cartographie des risques et des nuisances. Les services déconcentrés de l’État recueillent et organisent la communication de l’information en matière de risques, qu’ils soient d’origine naturelle ou technologique.

DRIEE ILE DE FRANCE - Cartographie des risques et des nuisances.

Voici les liens vers les principales bases de données en la matière : Prim.net : mise à disposition, partage et actualisation d’informations relatives aux risques naturels et technologiques.Géorisques : site d’information pour tous les publics sur les risques naturels (inondations, séisme, mouvement de terrain, argiles, avalanches…) et technologiques (usines à risques, nucléaire, sols pollués…). Basol : base de données listant les sites et sols pollués ou potentiellement pollués appelant une action des pouvoirs publics, à titre préventif ou curatif. Basias : inventaire historique des sites industriels et activités de service. ITV 22/11/02 MODELISATION DES MALADIES DE LA VIGNE : CARTOGRAPHIE DES RISQUES D'EPIDEMIES ET OPTIMISATION AGRONOMIQUE DE L'APPLICATION DES PRODUITS PHYTOSANITAIRES. CIRAD - 2009 - Rapport de stage : Diagnostic et cartographie des risques de pollution de l'environnement (eau, plantes, sol), par les métaux lourds, autour de fermes camelines, au Kazakhstan.

Diagnostic et cartographie des risques de pollution de l'environnement (eau, plantes, sol), par les métaux lourds, autour de fermes camelines, au Kazakhstan.

CIRAD - 2009 - Rapport de stage : Diagnostic et cartographie des risques de pollution de l'environnement (eau, plantes, sol), par les métaux lourds, autour de fermes camelines, au Kazakhstan

Le Guillou Maëla. 2009. Montpellier : UM2, 53 p. Mémoire de master 2 : Biologie géosciences agroressources et environnement. Parcours élevage dans les pays du sud environnement et développement : Université Montpellier 2 Disertation Abstract : Le lait de chamelle et le shubat (lait de chamelle fermenté) sont des produits de consommation courante au Kazakhstan. ECDC - MAI 2009 - Development of Aedes albopictus risk maps. IRD - SEPT 2009 - SCIENCES AU SUD - Paludisme : cartographier les risques. MEDSCAPE 28/07/08 Risk Maps for Range Expansion of the Lyme Disease Vector, Ixodes scapularis, in Canada Now and With Climate Change. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY - 1997 - Objective Assessment of Risk Maps of Tick-Borne Encephalitis and Lyme Borreliosis Based on Spatial Patterns of Located Cases.

PARASITOLOGY TODAY - 2000 - Risk Maps: Transmission and Burden of Vector-borne Diseases. ECDC - MAI 2009 - Development of Aedes albopictus risk maps. PLOS - MARS 2009 - Risk Maps of Lassa Fever in West Africa. Abstract Background Lassa fever is caused by a viral haemorrhagic arenavirus that affects two to three million people in West Africa, causing a mortality of between 5,000 and 10,000 each year.

PLOS - MARS 2009 - Risk Maps of Lassa Fever in West Africa

The natural reservoir of Lassa virus is the multi-mammate rat Mastomys natalensis, which lives in houses and surrounding fields. With the aim of gaining more information to control this disease, we here carry out a spatial analysis of Lassa fever data from human cases and infected rodent hosts covering the period 1965–2007. Information on contemporary environmental conditions (temperature, rainfall, vegetation) was derived from NASA Terra MODIS satellite sensor data and other sources and for elevation from the GTOPO30 surface for the region from Senegal to the Congo.

Methodology/Principal Findings Three different analyses (models) are presented, one superimposing Lassa fever outbreaks on the mean rainfall surface (Model 1) and the other two using non-linear discriminant analytical techniques.