SCIENTIFIC REPORTS 08/02/21 Author Correction: Data mining and model-predicting a global disease reservoir for low-pathogenic Avian Influenza (AI) in the wider Pacific Rim using big data sets. Novosibirsk State University, Novosibirsk, RussiaMarina GulyaevaFederal Research Center of Fundamental and Translational Medicine, Novosibirsk, RussiaMarina Gulyaeva, Alexander Shestopalov & Alexandra GlushchenkoEWHALE Lab, Institute of Arctic Biology, Biology and Wildlife Department, University of Alaska Fairbanks (UAF), Fairbanks, USAFalk HuettmannLaboratory of Microbiology, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Hokkaido, JapanMasatoshi Okamatsu, Keita Matsuno & Yoshihiro SakodaGlobal Station for Zoonosis Control, Global Institute for Collaborative Research and Education (GI‑CoRE), Hokkaido University, Sapporo, Hokkaido, JapanKeita Matsuno & Yoshihiro SakodaDepartment of Animal Health, Ministry of Agriculture and Rural Development, Ha Noi, Viet NamDuc‑Huy ChuUniversity of Alaska Anchorage (UAA), Anchorage, USAElaina Milton & Eric Bortz.
UNIVERSIDAD COMPLUTENSE DE MADRID - 2011 - Thèse en ligne : Modelo epidemiológico de difusión de la influenza aviar altamente patógena (IAAP) SCIENTIFIC REPORTS 08/10/20 Data mining and model-predicting a global disease reservoir for low-pathogenic Avian Influenza (A) in the wider pacific rim using big data sets. Study area The study area consists of the wider northern Pacific Rim area which is known to be an exchange frontier between diseases and cultures (Fig. 12,9).
We followed methods outlined in5,11,12 and specifically13 drawing inference from predictions. The conducted international landscape investigation in this study area is described in a research workflow (Fig. 2), and it mainly consists of different steps: field work, open access data compilation, data cleaning and lab work, GIS mapping, data mining and prediction, reflection and inference, as further described below (for more clarifications or questions please contact authors). Workflow of this study to obtain best-available AI data and to data mine and predict them with machine learning in a geographic information system (GIS) for best-possible predictions and inference for the Pacific Rim study area (IRD = Influenza Research Database; USDA = U.S.
Epidemics Volume 17, December 2016 Modelling the impact of co-circulating low pathogenic avian influenza viruses on epidemics of highly pathogenic avian influenza in poultry. Epidemics Available online 21 February 2017 Modelling H5N1 in Bangladesh across spatial scales: Model complexity and zoonotic transmission risk. Highlights H5N1 avian influenza remains a persistent threat to public health.
We modelled two different H5N1 outbreaks in Bangladesh at two spatial scales. Our model framework incorporated transmission at the human–poultry interface. We assessed the main contributors to poultry infection and spillover transmission to humans. The model parameters meriting inclusion are sensitive to spatial scale. Abstract Highly pathogenic avian influenza H5N1 remains a persistent public health threat, capable of causing infection in humans with a high mortality rate while simultaneously negatively impacting the livestock industry.
Keywords. 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.
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. Trop Anim Health Prod (2014) 46:57–63 Modelling influenza A H5N1 vaccination strategy scenarios in the household poultry sector in Egypt. The countries in which HPAI H5N1 virus is currently considered endemic include Bangladesh, China, Egypt, Indonesia, Vietnam as well as the Indian State of West Bengal (Hinrichs and Otte 2012).
Waves of AI outbreaks may occur in poultry populations in endemic areas whenever large parts of the population are left with a low level of immunity as a result of low VC (Magalhaes et al. 2006). The present study represents an assessment of the interaction of VS with poultry production parameters that affect population dynamics on the CAFI. The level of village CAFI depended on the VE and VC achieved.
The latter varied between villages but was generally low. CAFI is also affected by the flock composition and production parameters. For Pekin duck, the CAFI modelled under the adopted strategy was limited because the required booster shot was not given and the short cycle (4–6 weeks) results in rapid removal of vaccinated Pekin ducks (to be replaced by unvaccinated ones). COMMUNITY OF ORDINARY DIFFERENTIAL EQUATIONS EDUCATORS 03/09/14 Modeling the Effects of Avian Flu (H5N1) Vaccination Strategies on Poultry.
Publication Date Keywords Disease Modeling; Avian Flu; Poultry; SIR Model Abstract The work in this article addresses a problem posed by Dr.
Maria Salvato to the CODEE community. 10.5642/codee.201410.01.01. VETERINARY RESEARCH Vol. 41 No. 3 (May-June 2010) Anthropogenic factors and the risk of Highly Pathogenic Avian Influenza H5N1: prospects from a spatial-based model. Vet.
Res. (2010) 41:28 Original article Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model Mathilde Paul1,2*, Saraya Tavornpanich3, David Abrial1, Patrick Gasqui1, Myriam Charras-Garrido1, Weerapong Thanapongtharm3, Xiangming Xiao4, Marius Gilbert5,6, Francois Roger2 and Christian Ducrot1. JOURNEE D'EPIDEMIOLOGIE AEEMA, 1er juin 2007 Influenza aviaire : Modélisation du risque d'infection des oiseaux à partir d'étangs contaminés.
BMC 21/07/16 Model-based clustering with certainty estimation: implication for clade assignment of influenza viruses. The experimental dataset 1 was studied previous in , where a 2D MDS was used to visualize structure of HPAI H5N1 HA sequence data.
Further investigation identifies 2 issues: 1) the 2D MDS may not be an optimal way to represent the complexity of the sequence data; 2) there is no estimation of confidence level for individual sequences or specific clusters. To address the first issue, we used the criterion suggested in  to select the dimension of MDS (d). The Mardia criterion (a parameter used for determining the number of dimensions that considerably differ) shows significant increases for d from 1 to 2 and from 2 to 3 (Fig. 1), and after that the increase becomes less obvious. Therefore, we chose d = 3. Figure 2 shows the corresponding 3D MDS plot of the H5N1 HA influenza sequences, which obviously provides better separation between clusters (i.e., clades). We compared the clusters obtained from Mclust based on the 3D MDS and those from the clade designation of WHO. AVIAN DISEASES - MAI 2016 - The Use of Spatial and Spatiotemporal Modeling for Surveillance of H5N1 Highly Pathogenic Avian Influenza in Poultry in the Middle East.
UNIVERSITE BLAISE PASCAL CLERMONT-FERRAND 26/06/14 Thèse en ligne : Mathematical modelling of the infectious spread of avian influenza on a backyard chicken production chain in Thailand. IND44395547. PLOS 27/08/14 Mathematical Modeling of Influenza A Virus Dynamics within Swine Farms and the Effects of Vaccination. Abstract Influenza A virus infections are widespread in swine herds across the world. Influenza negatively affects swine health and production, and represents a significant threat to public health due to the risk of zoonotic infections.
Swine herds can act as reservoirs for potentially pandemic influenza strains. In this study, we develop mathematical models based on experimental data, representing typical breeding and wean-to-finish swine farms. These models are used to explore and describe the dynamics of influenza infection at the farm level, which are at present not well understood. Citation: Reynolds JJH, Torremorell M, Craft ME (2014) Mathematical Modeling of Influenza A Virus Dynamics within Swine Farms and the Effects of Vaccination. Editor: Alain Barrat, Centre de Physique Théorique, France. Nonlinear Analysis Real World Applications. 09/2008; Modeling the spread of bird flu and predicting outbreak diversity. NONLINEAR ANALYSIS: REAL WORLD APPLICATIONS - 2015 - Modeling avian influenza using Filippov systemps to determine culling of infected birds and quarantine. Computational and Mathematical Methods in Medicine - 2015 - Global Dynamics of Avian Influenza Epidemic Models with Psychological Effect.
Preventive Veterinary Medicine Volume 114, Issue 1, 1 April 2014, Zero-inflated models for identifying disease risk factors when case detection is imperfect: Application to highly pathogenic avian influenza H5N1 in Thailand. Volume 114, Issue 1, 1 April 2014, Pages 28–36 Special Issue: GEOVET 2013 Edited By Michael Ward, Olaf Berke, Andres M. Perez, Dirk Pfeiffer and Mark Stevenson. Preventive veterinary medicine 2014 Mar. 1, v. 113, no. 4 Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America. Search National Agricultural Library Digital Collections Back to Search NALDC Record Details: Using quantitative disease dynamics as a tool for guiding response to avian influenza in poultry in the United States of America Permanent URL: Theory Biosci. (2014) 133:23–38 A mathematical model of avian influenza with half-saturated incidence. INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES 26/08/14 Modelling an Econometric Regional Equations for Avian Influenza Outbreaks in Egypt under Current Climate Conditions.
International Journal of Biological Sciences and Applications Manuscript Information Modelling an Econometric Regional Equations for Avian Influenza Outbreaks in Egypt under Current Climate Conditions International Journal of Biological Sciences and Applications Vol.1 , No. 3, Publication Date: August 26, 2014, Page: 1-6 150 Views Since August 26, 2014, 6 Downloads Since April 14, 2015 AuthorsAbstract. BMC Bioinformatics 2014, 15:276 Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks. INFECTIOUS DISEASE OF POVERTY - 2013 - Research priorities in modeling the transmission risks of H7N9 bird flu. SCIENTIFIC REPORTS 12/07/13 Modeling highly pathogenic avian influenza transmission in wild birds and poultry in West Bengal, India. Data collection The National Institute of Virology and the Ela Foundation of India collected migratory bird data as part of an avian influenza surveillance project in 2010.
The data included observations of known wintering grounds along with incidentally found congregations on large natural water-bodies, flooded rice fields, and reservoirs. Data available regarding avian influenza risk factors for these congregations included avian community size, habitat, sentinel species, species previously known positive for H5N1, bridge species, and occurrence of domestic ducks in the same water-body43, 44, 45. Observations were done using standard “point count” techniques by authors (SP and PP)46. UNIVERSITY OF FLORIDA 23/11/13 Avian Flu: Modeling and Implications for Control. IFPRI - AVRIL 2009 - Mapping the Likelihood of Introduction and Spread of Highly Pathogenic Avian Influenza Virus H5N1 in Africa, Ghana, Ethiopia, Kenya and Nigeria using Multicriteria Decision Modelling.
IFPRI - SEPT 2006 - Assessing potential impact of avian influenza on poultry in West Africa - A spatial equilibrium model analysis. BIOMED 14/06/13 A global model of avian influenza prediction in wild birds. Procedia Environmental Sciences Volume 7, 2011, Pages 104–109 Spatio-temporal model of avian influenza spread risk. Volume 7, 2011, Pages 104–109 Spatial Statistics 2011: Mapping Global Change Edited By Alfred Stein, Edzer Pebesma and Gerard Heuvelink Abstract HPAI virus has caused significant economic losses in the poultry industry. Backyard and outdoor poultry farms (BOPF) can play an important role in the spread of the disease. Keywords. WAGENINGEN UNIVERSITY 21/01/13 Thèse en ligne : Mechanisms of Avian Influenza virus transmission between farms: combining data c. MASSACHUSETTS INSTITUTE OF TECHNOLOGY - 2009 - Thèse en ligne : Modelling pandemic influenza progression using Spatiotemporal Ep.
BMC - 2012 - Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: the AsiaFlu. Bull World Health Organ vol.90 no.4 Genebra Apr. 2012 Epidemic and intervention modelling - a scientific rationale for policy de. Epidemic and intervention modelling - a scientific rationale for policy decisions?
Bull World Health Organ vol.90 no.4 Genebra Apr. 2012 Epidemic and intervention modelling - a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic – guatemalt
MEDICAL NEWS 06/04/11 Mathematical Modeling Of Migratory Birds, Domestic Poultry And Bird Flu. Eurosurveillance, Volume 14, Issue 26, 02 July 2009. Eurosurveillance, Volume 14, Issue 26, 02 July 2009. Epidemiol. Infect. (2011), 139, 68–79. Model predictions and evaluation of possible control strategies for the 2009 A/H1N1v infl.
Epidemiol. Infect. (2011), 139, 68–79. Model predictions and evaluation of possible control strategies for the 2009 A/H1N1v influenza pandemic in Italy – guatemalt
INRA 07/08/09 Des modèles mathématiques et statistiques pour prévoir les évolutions des épidémies et pandémies de grippes. INVS 17/01/06 Au sommaire BEH n°02-03 Au sommaire: Risques infectieux : approches méthodologiques de la veille et de l'aide à la. PLOS 14/02/12 Modelling the Wind-Borne Spread of Highly Pathogenic Avian Influenza Virus between Farms.
ROYAL SOCIETY - SEPT 2015 - Modelling the species jump: towards assessing the risk of human infection from novel avian influenzas.