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Modélisation et virus du Nil

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BIORXIV 31/03/21 Dynamics of data availability in disease modeling: An example evaluating the trade-offs of ultra-fine-scale factors applied to human West Nile virus disease models in the Chicago area, USA. Viruses. 2020 Aug 12;Modelling West Nile Virus and Usutu Virus Pathogenicity in Human Neural Stem Cells. West Nile virus (WNV) and Usutu virus (USUV) are genetically related neurotropic mosquito-borne flaviviruses, which frequently co-circulate in nature.

Viruses. 2020 Aug 12;Modelling West Nile Virus and Usutu Virus Pathogenicity in Human Neural Stem Cells

Despite USUV seeming to be less pathogenic for humans than WNV, the clinical manifestations induced by these two viruses often overlap and may evolve to produce severe neurological complications. The aim of this study was to investigate the effects of WNV and USUV infection on human induced pluripotent stem cell-derived neural stem cells (hNSCs), as a model of the neural progenitor cells in the developing fetal brain and in adult brain. Zika virus (ZIKV), a flavivirus with known tropism for NSCs, was used as the positive control.

Infection of hNSCs and viral production, effects on cell viability, apoptosis, and innate antiviral responses were compared among viruses. WNV displayed the highest replication efficiency and cytopathic effects in hNSCs, followed by USUV and then ZIKV. ►▼ Show Figures Figure 1 ►▼ Show Figures Figure 1. ARXIV 27/01/21 Can a patchy model describe the potential spread of West Nile virus in Germany? BLOG BUGBITTEN 20/09/19 Big step towards predicting West Nile virus transmission risk by combining citizen science and phylogenetic imputation. In 2015, I gave a presentation at the Society for Vector Ecology, lamenting the difficulties of predicting West Nile virus transmission risk at fine spatial and temporal scale.

BLOG BUGBITTEN 20/09/19 Big step towards predicting West Nile virus transmission risk by combining citizen science and phylogenetic imputation

Up to now, there is no widely used and commonly accepted method to predict transmission risk of this most prevalent arbovirus in North America, with probably the best being the Vector Index used in the State of California. One of the many difficulties of predicting West Nile virus is due to the complexity of its ecology, in particular the variety of bird species that can act as hosts for this virus. These, mostly passerine songbirds, differ in the probability that a susceptible mosquito would get infected if it fed on them.

Environnement, Risques & Santé. Volume 4, Numéro 2, Mars-Avril 2005 Au sommaire: Modélisation de l'agressivité de Culex modestus, vecteur potentiel de West Nile en Camargue, en fonction de données météorologiques. REMOTE SENS 09/08/19 Satellite Earth Observation Data in Epidemiological Modeling of Malaria, Dengue and West Nile Virus: A Scoping Review. The selected articles were organized into two main categories (Figure 3) with respect to the data used as dependent variables for the prevalence of the diseases: (a) epidemiological data (disease incidence, prevalence or case, mortality data) (n = 31) and (b) entomological data (n = 11), while Stilianakis et al. has examined both (a) and (b) [30], and Valiakos et al. has additionally used wild bird data in complement to the epidemiological data [31].

REMOTE SENS 09/08/19 Satellite Earth Observation Data in Epidemiological Modeling of Malaria, Dengue and West Nile Virus: A Scoping Review

The first category (a) used clinical records from the general human population as the main data source. In this case the majority of the studies (n = 23) referred to the clinical data as “confirmed cases”, meaning that the patients were confirmed through laboratory testing. Buczak et al. [32] and Arboleda et al. [33] included also cases that were considered as “possible”, meaning that the patients exhibited some of the symptoms of the infection. Through our database search, mainly data-driven and statistical approaches were returned. 3.1.

JAMA 26/04/19 Modeling and Surveillance of Reporting Delays of Mosquitoes and Humans Infected With West Nile Virus and Associations With Accuracy of West Nile Virus Forecasts. SOUTH DAKOTA STATE UNIVERSITY 10/09/18 West Nile virus prediction model protects human health, empowers communities. A reliable means of predicting disease risk and communities engaged in controlling mosquito populations are helping South Dakotans get a handle on West Nile virus.

SOUTH DAKOTA STATE UNIVERSITY 10/09/18 West Nile virus prediction model protects human health, empowers communities

It did not happen by chance. “It was the vision of the South Dakota Department of Health that got all the players together 15 years ago,” explained South Dakota State University mosquito expert Michael Hildreth, a professor in the Department of Biology and Microbiology, College of Natural Sciences. Hildreth credited State Epidemiologist Lon Kightlinger, now retired, for getting the ball rolling and the state legislature for providing funding for mosquito surveillance and control. In 2008, Hildreth began working with Michael Wimberly, then a senior scientist at the Geospatial Sciences Center of Excellence at SDSU, who began developing a model to predict the risk of West Nile virus using environmental data from Earth-imaging satellites.

The optimized West Nile prediction model has now been handed over to the S.D. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4/W2, 2017 FOSS4G-Europe 2017 – Academic Track, 18–22 July 2017, Marne La Vallée, France - CAN RECONSTRUCTED LAND SURFACE TEMPERATURE DATA FROM.

J Theor Biol. 2016 Jun 21;399:33-42. A host stage-structured model of enzootic West Nile virus transmission to explore the effect of avian stage-dependent exposure to vectors. PEERJ 28/03/17 A comparison of least squares regression and geographically weighted regression modeling of West Nile virus risk based on environmental parameters. Introduction West Nile Virus (WNV) is a vector-borne disease that was first detected in the United States in 1999 (Nash et al., 2001).

PEERJ 28/03/17 A comparison of least squares regression and geographically weighted regression modeling of West Nile virus risk based on environmental parameters

Within a few years the virus had spread across the North American continent (Hayes et al., 2005). WNV has had important environmental and human impacts, including a decline in numerous bird species (CDC) and increased morbidity and mortality among humans. This has also resulted in increased economic burdens due to initial acute health care needs of infected individuals and subsequent long-term costs associates with infection, estimated at approximately $56 million per year between 1999 and 2012 (Barrett, 2014). Because that study indicated how difficult predicting and planning for WNV outbreaks was, we became interested in developing a spatially explicit model using environmental factors in an attempt to improve WNV risk predictions. MATHEMATICAL BIOSCIENCES AND ENGINEEING - APRIL 2016 - A MATHEMATICAL MODEL FOR THE SPREAD OF WEST NILE VIRUS IN MIGRATORY AND RESIDENT BIRDS.

ENTOMOLOGY TODAY 30/06/16 West Nile Virus Infections Can Be Estimated by Observing Rainfall and Temperatures. A northern house mosquito (Culex pipiens), the primary vector of West Nile virus in the United States.

ENTOMOLOGY TODAY 30/06/16 West Nile Virus Infections Can Be Estimated by Observing Rainfall and Temperatures

Photo by Ary Farajollahi, Bugwood.org. By Alan Bolds. Int J Environ Res Public Health. 2013 Nov; 10(11): 5399–5432. Exploring the Spatio-Temporal Dynamics of Reservoir Hosts, Vectors, and Human Hosts of West Nile Virus: A Review of the Recent Literature. YORK UNIVERSITY TORONTO, ONTARIO - JUIN 2014 - Dissertation en ligne : MODELING, DYNAMICS AND OPTIMAL CONTROL OF WEST NILE VIRUSWITH SEASONALITY. PLOS 30/09/14 Modeling Dynamics of Culex pipiens Complex Populations and Assessing Abatement Strategies for West Nile Virus. Parasites & Vectors 2014, 7:289 Modeling the distribution of the West Nile and Rift Valley Fever vector Culex pipiens in arid and semi-arid regions of the Middle East and North Africa. Int. J. Environ. Res. Public Health 2014, 11, 67-90; Predictive Modeling of West Nile Virus Transmission Risk in the Mediterranean Basin: How Far from Landing? ECOHEALTH - 2013 - Ecological Niche Modelling of Potential West Nile Virus Vector Mosquito Species and Their Geographical Association with Equine Epizootics in Italy.

CAA_IT - 2013 – Poster : Preliminary spatial modelling of West Nile Virus circulation in Pianura Padana, Northern Italie, 2013.

Modélisation et virus du Nil aux Etats-Unis

THE ROYAL SOCIETY 17/08/11 Vector host-feeding preferences drive transmission of multi-host pathogens: West Nile virus as a mode. + Author Affiliations ↵*Author for correspondence (maria.diuk@yale.edu).

THE ROYAL SOCIETY 17/08/11 Vector host-feeding preferences drive transmission of multi-host pathogens: West Nile virus as a mode

Abstract Seasonal epizootics of vector-borne pathogens infecting multiple species are ecologically complex and difficult to forecast. Pathogen transmission potential within the host community is determined by the relative abilities of host species to maintain and transmit the pathogen and by ecological factors influencing contact rates between hosts and vectors. Increasing evidence of strong feeding preferences by a number of vectors suggests that the host community experienced by the pathogen may be very different from the local host community. 1. Zoonotic pathogens cause significant mortality, morbidity and economic loss to human, livestock and wildlife hosts throughout the world, constituting an estimated 75 per cent of emerging infectious diseases [1–3].

Figure 1. Flow diagram for the WNV model. 2. (a) Field surveys 3. (a) Blood meal analysis. THESE EN LIGNE - 2006 - De l'identification des vecteurs du virus West Nile à la modélisation du risque d'infection dans le sud. UNIVERSITE PARIS-SUD 14/09/12 Thèse en ligne ; Construction d’un clone infectieux d’une souche méditerranéenne du Virus West Nil. Int J Environ Res Public Health. 2013 Jul 22;10(7):3033-51. Modeling Monthly Variation of Culex tarsalis (Diptera: Culicidae) Ab. Open AccessThis article isfreely availablere-usable Article 1 Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, 52 Campus Drive, Saskatoon, SK S7N 5B4, Canada 2 Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, 52 Campus Drive, Saskatoon, SK S7N 5B4, Canada 3 Saskatchewan Ministry of Health, 3475 Albert Street, Regina, SK S4S 6X6, Canada 4 Environment Canada, Science & Technology Branch, 115 Perimeter Road, Saskatoon, SK S7N 0X4, Canada * Author to whom correspondence should be addressed.

Int J Environ Res Public Health. 2013 Jul 22;10(7):3033-51. Modeling Monthly Variation of Culex tarsalis (Diptera: Culicidae) Ab