background preloader

MODELISATION EN ZOONOSES D'ORIGINE VECTORIELLE ET PARASITAIRE

Facebook Twitter

PARASITES & VECTORS 26/04/17 Landscape structure affects distribution of potential disease vectors (Diptera: Culicidae) Distribution, endemicity and transmission potential of vector-borne pathogens is regulated by the communities of potential vector organisms [1, 2].

PARASITES & VECTORS 26/04/17 Landscape structure affects distribution of potential disease vectors (Diptera: Culicidae)

Mosquitoes, while mostly a nuisance of little impact, are also among the most important vectors for various pathogens. Several Culicidae taxa have been demonstrated to (potentially) transmit members of the Flaviviridae (e.g. West Nile virus, Japanese encephalitis virus, dengue virus, Usutu virus) and the Togaviridae (e.g. sindbis virus), and various endo-parasites like Plasmodium spp. and Dirofilaria spp. [3, 4, 5]. However, each mosquito-borne pathogen can only be successfully transmitted by a specific range of suitable mosquito species. NATURE / SCIENTIFIC REPORTS 19/04/16 Predicting the epidemic threshold of the susceptible-infected-recovered model. Theoretical predictions of epidemic threshold In the SIR pattern of the spread of disease through a network, at any given time each node is either susceptible, infected, or recovered.

NATURE / SCIENTIFIC REPORTS 19/04/16 Predicting the epidemic threshold of the susceptible-infected-recovered model

A susceptible node does not transmit the disease. Infected nodes contract the disease and spread it to their neighbors. A recovered node has returned to health and no longer spreads the disease. The synchronous updating method30 is applied to renew the states of nodes. BLOG BIOMED 06/10/15 Predicting Epidemics Dr. Hiroshi Nishiura, Editor-in-Chief of Theoretical Biology and Medical Modelling, discusses what the current biggest epidemics are, where the next big epidemic will come from and how we will cope with it and if. How can we prevent epidemics?

BLOG BIOMED 06/10/15 Predicting Epidemics Dr. Hiroshi Nishiura, Editor-in-Chief of Theoretical Biology and Medical Modelling, discusses what the current biggest epidemics are, where the next big epidemic will come from and how we will cope with it and if

Flickr Professor Hiroshi Nishiura is an Associate Professor at Graduate School of Medicine, The University of Tokyo. After working 10 years for different infectious disease modeling groups at Imperial College London, University of Tuebingen (Germany), University of Utrecht (The Netherlands) and the University of Hong Kong, he returned to Japan in 2013, launching a real-time epidemic modelling unit and starting to building up research capacity and intensify collaborations with governmental entities using mathematical models. His research interests span the areas of statistical epidemiology of infectious diseases, epidemiological modeling and biomathematical formulation of the transmission dynamics of infectious diseases.

He aims to answer policy-relevant questions by integrating various mathematical models with empirically observed data. What are the biggest epidemics at the moment? The ongoing worst epidemic is AIDS which has continuously grown since 1981. ARXIV 25/11/13 Bayesian Analysis of Epidemics - Zombies, Influenza, and other Diseases. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY - 2010 - Modelling parasite transmission and control. MASSEY UNIVERSITY 01/06/15 Bayesian data assimilation provides rapid decision support for vector-borne diseases. ARXIV 25/11/13 Bayesian Analysis of Epidemics - Zombies, Influenza, and other Diseases. IMPERIAL COLLEGE LONDON 04/02/14 Présentation : Predicting the utility of novel strategies for vector-borne disease control using mathematical models. INTERNATIONAL CENTER OF INSECT PHYSIOLOGY (ICIPE) - FEV 2015 - Présentation: Crop insect pest modeling: What have we learned from past efforts?

Applied Mathematics, 2013, 4, 13-17 SEIR Model and Simulation for Vector Borne Diseases. PARASITES AND VECTORS 18/12/13 Bayesian geostatistical modelling of soil-transmitted helminth survey data in the People's Republic of China. Ethical considerations The work presented here is based on soil-transmitted helminth survey data derived from the second national survey and additional studies identified through an extensive review of the literature.

PARASITES AND VECTORS 18/12/13 Bayesian geostatistical modelling of soil-transmitted helminth survey data in the People's Republic of China.

All data in our study was extracted from published sources and they are aggregated over villages, towns or counties; therefore, do not contain information that is identifiable at individual or household level. Hence, there are no specific ethical considerations. Disease data Geo-referenced data on soil-transmitted helminth infections from the second national survey conducted in P.R. Climatic, demographic and environmental data Climatic, demographic and environmental data were downloaded from different readily accessible remote sensing data sources, as shown in Table 1.

Moderate Resolution Imaging Spectroradiometer (MODIS) Reprojection Tool version 4.1 (EROS; Sioux Falls, USA) was applied to process MODIS/Terra data. Statistical analysis. ISPRS Int. J. Geo-Inf. - 2014 - Dasymetric Mapping and Spatial Modeling of Mosquito Vector Exposure, Chesapeake, Virginia, USA. 4.1.

ISPRS Int. J. Geo-Inf. - 2014 - Dasymetric Mapping and Spatial Modeling of Mosquito Vector Exposure, Chesapeake, Virginia, USA

Human Vulnerability and Mosquito Vector Abundance To assess the sensitivity and accuracy of the dasymetric mapping techniques, the raster surface of vulnerability can be compared to the data mapped by block groups. The dasymetric map was expected to provide a more spatially precise representation of population vulnerability as compared to the Census block group choropleths. BIOLOGICAL REVIEWS - 2014 - Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks. GLOBAL ENVIRONMENTAL CHANGE - 1995 - Climate change and vector-borne diseases - A global modeling perspective.

KANSAS STATE UNIVERSITY - 2013 - Thèse en ligne : MODELING AND ANALYSIS OF VECTOR-BORNE DISEASES ON COMPLEX NETWORKS. ARCHIVES OUVERTES - 2009 - Modelling Dengue Epidemics with Autoregressive Switching Markov Models (AR-HMM) Epidémiol. et santé anim., 2005, 47, 35-51 MODELISATION DES MALADIES VECTORIELLES* Détails Mis à jour le lundi 15 septembre 2014 18:02 EditorialBarbara Dufour L'aide de l'épidémiologie aux décisions de santéL.

Epidémiol. et santé anim., 2005, 47, 35-51 MODELISATION DES MALADIES VECTORIELLES*

Int. J. Environ. Res. Public Health 2014, Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences. 1 Center of Excellence for Vectors and Vector-Borne Diseases, Faculty of Science, Mahidol University at Salaya, Nakhon Pathom 73170, Thailand 2 Department of Medical Sciences, Ministry of Public Health, Nonthaburi 11000, Thailand 3 Umeå Centre for Global Health Research, Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå 90187 , Sweden * Author to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2014, Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

Received: 12 March 2014 / Revised: 30 September 2014 / Accepted: 7 October 2014 / Published: 16 October 2014 Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. 6th EUROSIM Congress on Modelling and Simulation - SEPT 2007 - MODELLING A FOOD INDUSTRY PROCESS BY DECISION TREE. Parasitology. 2014 May;141(6):837-48. Modelling inter-human transmission dynamics of Chagas disease: analysis and application. Applied Mathematics, 2013, 4, 13-17 SEIR Model and Simulation for Vector Borne Diseases. PLOS 13/06/13 Developing Models of Disease Transmission: Insights from Ecological Studies of Insects and Their Baculoviruses.

Figures Citation: Elderd BD (2013) Developing Models of Disease Transmission: Insights from Ecological Studies of Insects and Their Baculoviruses.

PLOS 13/06/13 Developing Models of Disease Transmission: Insights from Ecological Studies of Insects and Their Baculoviruses

PLoS Pathog 9(6): e1003372. doi:10.1371/journal.ppat.1003372 Editor: Joseph Heitman, Duke University Medical Center, United States of America Published: June 13, 2013 Copyright: © 2013 Elderd. Funding: The study was supported by the Louisiana Board of Regents. Competing interests: The author has declared that no competing interests exist. Mathematical models of disease outbreaks play a crucial role in guiding public health policy [1]–[3] and have provided critical insights into the ecological dynamics of pathogen-regulated populations [4], [5]. What Are Baculoviruses? From a medical and microbiology perspective, baculoviruses have been developed as expression vectors and for research tools in medicine such as vaccine development [8], [9]. Figure 1. . , a population's heterogeneity has a dramatic impact on disease transmission. INRA ANGERS 20/06/12 Modéliser pour comprendre et prédire la dynamique des populations de vecteurs et des maladies vectorielles.

Modélisation et moustiques. Conference of the International Cartographic Association, Paris : France (2011) From Grid Environment to Geographic Vector Agent.

Conference of the International Cartographic Association, Paris : France (2011) From Grid Environment to Geographic Vector Agents, Modeling with the GAMA simulation platform – guatemalt

International Journal of Health Geographics 2012, 11:39 Modelling zoonotic diseases in humans: comparison of methods for hantavi.

International Journal of Health Geographics 2012, 11:39 Modelling zoonotic diseases in humans: comparison of methods for hantavirus in Sweden – guatemalt

Malar J. 2013 Jan 3;12:4. Modelling the cost-effectiveness of mass screening and treatment for reducing Plasmodium falciparum ma.

Malar J. 2013 Jan 3;12:4. Modelling the cost-effectiveness of mass screening and treatment for reducing Plasmodium falciparum malaria burden. – guatemalt

Environnement, Risques & Santé. Volume 4, Numéro 2, Mars-Avril 2005 Au sommaire:Modélisation de l'agressivité de Culex modestus, EPIDEMIOLOGY - JUILLET 1998 - Probability Model on the Use of Sentinel Animal Monitoring for Arbovirus. Int. J. Environ. Res. Public Health 2012 Using the Gravity Model to Estimate the Spatial Spread of Vector-Borne Diseases.

Universidade Santa Úrsula - USU / ICBA - Laboratoire « Espace, Nature, Culture » (UMR 8185 CNRS - Université Paris 8, UFR TES –

Références PLOS

Fièvre de la vallée du Rift, géolocalisation et modélisation. Modélisation, géolocalisation et culicoïdes. Zika et modélisation.