ROYAL SOCIETY - SEPT 2015 - Modelling the species jump: towards assessing the risk of human infection from novel avian influenzas. Abstract The scientific understanding of the driving factors behind zoonotic and pandemic influenzas is hampered by complex interactions between viruses, animal hosts and humans.
This complexity makes identifying influenza viruses of high zoonotic or pandemic risk, before they emerge from animal populations, extremely difficult and uncertain. As a first step towards assessing zoonotic risk of influenza, we demonstrate a risk assessment framework to assess the relative likelihood of influenza A viruses, circulating in animal populations, making the species jump into humans. The intention is that such a risk assessment framework could assist decision-makers to compare multiple influenza viruses for zoonotic potential and hence to develop appropriate strain-specific control measures. It also provides a first step towards showing proof of principle for an eventual pandemic risk model. 1.
Influenza A has a natural reservoir in wild aquatic birds . 2. 2.1 Model framework Table 1. Figure 1. NATIONAL VETERINARY INSTITUTE (SVA_SE) - 2013 - Thèse en ligne : Emerging Infectious Diseases: a model of disease transmission dynamics at the wildlife-livestock interface in Uganda. Clinical Microbiology and Infection Volume 19, Issue 11, November 2013, Modelling in infectious diseases: between haphazard and hazard. Abstract Modelling of infectious diseases is difficult, if not impossible.
No epidemic has ever been truly predicted, rather than being merely noticed when it was already ongoing. Modelling the future course of an epidemic is similarly tenuous, as exemplified by ominous predictions during the last influenza pandemic leading to exaggerated national responses. The continuous evolution of microorganisms, the introduction of new pathogens into the human population and the interactions of a specific pathogen with the environment, vectors, intermediate hosts, reservoir animals and other microorganisms are far too complex to be predictable.
Our environment is changing at an unprecedented rate, and human-related factors, which are essential components of any epidemic prediction model, are difficult to foresee in our increasingly dynamic societies. Modélisation et alimentation (sécurité sanitaire, TIAC) ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY - 2010 - Modelling parasite transmission and control. CORNELL UNIVERSITY - 2014 - Predictive Modeling of Cholera Outbreaks in Bangladesh. CORNELL UNIVERSITY 02/12/14 Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola. Rev. sci. tech. Off. int. Epiz., 2013, 32 (3), 605-617 Modelling risk aversion to support decision making for controlling zoonotic livestock diseases. Epidemics Available online 19 September 2014 Nine challenges in modelling the emergence of novel pathogens. DFID_GOV_UK 08/02/12 Characterising livestock system ‘zoonoses hotspots’ BMC Medical Informatics and Decision Making 2013, 13:12 In silico surveillance: evaluating outbreak detection with simulation mo.
EUROPEAN RESEARCH COUNCIL - Modelling waterborne epidemics. The 22nd of March is UN World Water Day.
Each year World Water Day highlights the importance of fresh water for global health: water's critical role in food security; its cultural role in shaping societies worldwide; the impact of natural disasters; the significance of clean water supplies in preventing the spread of diseases. Caption: A young boy drinking the water of the Meghna River near Matlab (Bangladesh), a place where cholera is endemic©Photos by courtesy of Professor Andrea Rinaldo A UN report, unveiled last week at the World Water Forum in Marseille (France), revealed that nearly 800 million people do not have access to a safe water supply, whilst nearly 2.5 billion people lack basic sanitation.
This represents a grave threat to global health. Professor Andrea Rinaldo, an ERC Advanced grantee 2008, is at the forefront of the fast-developing field of ecohydrology with his project 'River Networks as Ecological Corridors' (RINEC).
Modélisation et Listéria. Modélisation et Campylobacter. Modélisation et ESST. BIOSS - 2011 - Modelling the immuno-magnetic separation method of detecting E. coli O157 in bovine faecal samples. Modelling the immuno-magnetic separation method of detecting E. coli O157 in bovine faecal samples Escherichia coli O157 (E. coli O157) is an important food-borne illness in humans, of major concern to health agencies.
Cattle and other ruminants act as a natural reservoir and are an important source of infection, shedding the bacteria in their faeces. Detection of shedding animals in a herd is an important step in the prevention of contamination of food. The immuno-magnetic separation method (IMS) is a relatively rapid, simple and sensitive assay to detect E. coli O157, compared to conventional direct plate culture method (PC). Using antibody-coated beads, IMS can detect E. col O157 in bovine faeces, allowing us to classify animals as positive or negative. Working with BioSS, experimentalists at the SAC analysed faecal samples using both IMS and PC. NATIONAL VETERINARY INSTITUTE (Suède) 19/12/12 Présentation : Environmental factors in modelling zoonotic infectious diseases,
INRA/METARISK 03/04/12 Présentation : Inférence d’un réseau bayésien augmenté visant à confronter : Veterinary Research Communications - 2005 - Probabilistic Models for Food-Borne Disease Risk Assessment. Eurosurveillance, Volume 15, Issue 12, 25 March 2010 Q fever outbreak in Cheltenham, United Kingdom, in 2007 and the use of disp. Weekly and monthly releases: Eurosurveillance releases: Two articles on Q fever outbreaks with different epidemiological patterns Eurosurveillance, Volume 15, Issue 12, 25 March 2010.
UNIVERSITY OF FLORIDA - 2010 - Thèse en ligne : ECOLOGICAL NICHE MODELING OF A ZOONOSIS: A CASE STUDY USING ANTHRAX OUTBREAKS AN. EHP 17/12/09 Ecological Niche Modeling of Cryptococcus gattii in British Columbia, Canada. Mathematical Biosciences and Engineering 7, 1 (2010) 199-215 MODELS FOR THE SPREAD AND PERSISTENCE OF HANTAVIRUS INFECTION IN RO. IPCSIT vol.22 (2012) © (2012) Modelling Provenance in Food Supply Chain to Track and Trace Foodborne Disease.