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Driven by population growth and rising incomes, the demand for animal source foods in low and middle-income countries is increasing rapidly. Pork is one of the most commonly consumed animal-based food, with the highest demand being in China due to its largest population and changing dietary habits linked to increasing wealth. Here, we show the changes in pig production systems in terms of farms capacity, productivity and production at the national and provincial levels by analyzing several censuses of China. In addition, we used a downscaling methodology to provide a recent and highly detailed map of the distribution of pigs in China. Between 2007 and 2017, pork production in China increased by 26.6%, up to 55 million tons and the number of large-scale farms with a yearly production of over 10 000 heads increased by 145%. Much of the production has changed from extensive backyard subsistence farming to intensive corporate farming. Moreover, the pig distribution has shifted from watercourse-intense southeast to northeast and southwest of China due to environmental policy in 2015. These policy-driven transitions primarily aimed to increase pig production efficiency and reduce environmental impacts and resulted in a profound transformation of geographic production patterns., SCOPUS: ar.j, info:eu-repo/semantics/published

Motivation The potentially low precision associated with the geographic origin of sampled sequences represents an important limitation for spatially-explicit (i.e. continuous) phylogeographic inference of fast-evolving pathogens such as RNA viruses. A substantial proportion of publicly available sequences are geo-referenced at broad spatial scale such as, for example, the administrative unit of origin rather than more exact locations (e.g. GPS coordinates). Most frequently, such sequences are either discarded prior to continuous phylogeographic inference or arbitrarily assigned to the geographic coordinates of the centroid of their administrative area of origin for lack of a better possibility. Results We here implement and describe a new approach that allows to incorporate heterogeneous prior sampling probabilities over a geographic area. External data, such as outbreak locations, are used to specify these prior sampling probabilities over a collection of sub-polygons. We apply this new method to the analysis of highly pathogenic avian influenza (HPAI) H5N1 clade data in the Mekong region. Our method allows to properly include, in continuous phylogeographic analyses, H5N1 sequences that are only associated with large administrative areas of origin and assign them with more accurate locations. Finally, we use continuous phylogeographic reconstructions to analyse the dispersal dynamics of different H5N1 clades and investigate the impact of environmental factors on lineage dispersal velocities. Availability Our new method allowing heterogeneous sampling priors for continuous phylogeographic inference is implemented in the open-source multi-platform software package BEAST 1.10. Supplementary information Supplementary data are available at Bioinformatics online and on figshare.com., SCOPUS: ar.j, info:eu-repo/semantics/published

In winter 2016–2017, Highly Pathogenic Avian Influenza (HPAI) H5N8 virus spread across Europe, causing unprecedented epizootics. France was massively affected, resulting in the culling of over 6 million poultry. Boosted regression tree (BRT) models were used to quantify the association between spatial risk factors and HPAI H5N8 infection in poultry holdings and to generate predictive maps for HPAI infection. Three datasets were combined to build the model: a dataset of the reported outbreaks in poultry, a dataset of the poultry holdings where the virus has not been reported and a set of relevant spatial risk factors, including poultry production and trade, and water bird habitat. Results identified key associations between the ‘foie gras’ production systems and HPAI H5N8 risk of occurrence and indicate that strengthening surveillance of fattening duck production systems and making the transportation of fattening ducks more secure would be key priority options for HPAI prevention and control., SCOPUS: ar.j, info:eu-repo/semantics/published

What explains the geographic distribution of pathogens? Better understanding and characterising disease patterns will help scientists to identify areas likely to host future epidemics and epizootics and to prioritise surveillance and intervention. However, the use of disease surveillance data to assess the risk of transmission and generate risk maps raises conceptual and methodological issues. Indeed, pathogens and more particularly viruses aren't ”species” like others that live in the open environment and must be studied with methods and concepts of their own. Avian influenza (AI), a disease caused by a virus infecting bird populations, has been selected to study these issues. AI has a major economic impact on the poultry industry in many countries, raises concerns of livelihood in low and middle-income countries, and represents a major concern for human health. The aim of this PhD thesis was to improve the knowledge on the spatial epidemiology of AI in different settings and conditions (i). For this, recent epizootics caused by the subtypes A (H5N1) and A (H7N9) were selected as case studies. First, highly pathogenic subtypes of the A (H5N1) virus have been studied in poultry farms (ducks and chickens) at different spatial scales: at the continental scale and the regional scale in the Mekong (Cambodia, Laos, Vietnam, Thailand) and the Nile Delta in Egypt. All these cases occurred between 2003, the date on which the virus starts to spread outside China, and 2015; the HPAI A (H5N1) subtypes are still reported today in many countries. Human infections caused by the A (H7N9) virus in China from March 2013 to 2017 were also studied. Studied different AI subtypes at different spatial scales within different host species also allowed to develop a conceptual model of AI transmission and to discuss the issue of the transferability of results in epidemiology (ii). Lastly, this PhD thesis leads to a discussion about the transfer of methods and concepts from ecology to spatia, Doctorat en Sciences agronomiques et ingénierie biologique, info:eu-repo/semantics/nonPublished

Over the years, the emergence of novel H5 and H7 highly pathogenic avian influenza viruses (HPAI) has been taking place through two main mechanisms: first, the conversion of a low pathogenic into a highly pathogenic virus, and second, the reassortment between different genetic segments of low and highly pathogenic viruses already in circulation. We investigated and summarized the literature on emerging HPAI H5 and H7 viruses with the aim of building a spatio-temporal database of all these recorded conversions and reassortments events. We subsequently mapped the spatio-temporal distribution of known emergence events, as well as the species and production systems that they were associated with, the aim being to establish their main characteristics. From 1959 onwards, we identified a total of 39 independent H7 and H5 LPAI to HPAI conversion events. All but two of these events were reported in commercial poultry production systems, and a majority of these events took place in high-income countries. In contrast, a total of 127 reassortments have been reported from 1983 to 2015, which predominantly took place in countries with poultry production systems transitioning from backyard to intensive production systems. Those systems are characterized by several co-circulating viruses, multiple host species, regular contact points in live bird markets, limited biosecurity within value chains, and frequent vaccination campaigns that impose selection pressures for emergence of novel reassortants. We conclude that novel HPAI emergences by these two mechanisms occur in different ecological niches, with different viral, environmental and host associated factors, which has implications in early detection and management and mitigation of the risk of emergence of novel HPAI viruses., SCOPUS: ar.j, info:eu-repo/semantics/published

In the last few years, several reassortant subtypes of highly pathogenic avian influenza viruses (HPAI H5Nx) have emerged in East Asia. These new viruses, mostly of subtype H5N1, H5N2, H5N6, and H5N8 belonging to clade 2.3.4.4, have been found in several Asian countries and have caused outbreaks in poultry in China, South Korea, and Vietnam. HPAI H5Nx also have spread over considerable distances with the introduction of viruses belonging to the same 2.3.4.4 clade in the U.S. (2014-2015) and in Europe (2014-2015 and 2016-2017). In this paper, we examine the emergence and spread of these new viruses in Asia in relation to published datasets on HPAI H5Nx distribution, movement of migratory waterfowl, avian influenza risk models, and land-use change analyses. More specifically, we show that between 2000 and 2015, vast areas of northeast China have been newly planted with rice paddy fields (3.21 million ha in Heilongjiang, Jilin, and Liaoning) in areas connected to other parts of Asia through migratory pathways of wild waterfowl. We hypothesize that recent land use changes in northeast China have affected the spatial distribution of wild waterfowl, their stopover areas, and the wild-domestic interface, thereby altering transmission dynamics of avian influenza viruses across flyways. Detailed studies of the habitat use by wild migratory birds, of the extent of the wild-domestic interface, and of the circulation of avian influenza viruses in those new planted areas may help to shed more light on this hypothesis, and on the possible impact of those changes on the long-distance patterns of avian influenza transmission., SCOPUS: ar.j, info:eu-repo/semantics/published

In the last two decades, two important avian influenza viruses infecting humans emerged in China, the highly pathogenic avian influenza (HPAI) H5N1 virus in the late nineties, and the low pathogenic avian influenza (LPAI) H7N9 virus in 2013. China is home to the largest population of chickens (4.83 billion) and ducks (0.694 billion), representing, respectively 23.1 and 58.6% of the 2013 world stock, with a significant part of poultry sold through live-poultry markets potentially contributing to the spread of avian influenza viruses. Previous models have looked at factors associated with HPAI H5N1 in poultry and LPAI H7N9 in markets. However, these have not been studied and compared with a consistent set of predictor variables. Significant progress was recently made in the collection of poultry census and live-poultry market data, which are key potential factors in the distribution of both diseases. Here we compiled and reprocessed a new set of poultry census data and used these to analyse HPAI H5N1 and LPAI H7N9 distributions with boosted regression trees models. We found a limited impact of the improved poultry layers compared to models based on previous poultry census data, and a positive and previously unreported association between HPAI H5N1 outbreaks and the density of live-poultry markets. In addition, the models fitted for the HPAI H5N1 and LPAI H7N9 viruses predict a high risk of disease presence for the area around Shanghai and Hong Kong. The main difference in prediction between the two viruses concerned the suitability of HPAI H5N1 in north-China around the Yellow sea (outlined with Tianjin, Beijing, and Shenyang city) where LPAI H7N9 has not spread intensely., SCOPUS: ar.j, info:eu-repo/semantics/published

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors., SCOPUS: ar.j, info:eu-repo/semantics/published

The highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Asia since 2003 and diversified into several genetic lineages, or clades. Although the spatial distribution of its outbreaks was extensively studied, differences in clades were never previously taken into account. We developed models to quantify associations over time and space between different HPAI H5N1 viruses from clade 1, 2.3.4 and 2.3.2 and agro-ecological factors. We found that the distribution of clades in the Mekong region from 2004 to 2013 was strongly regionalised, defining specific epidemiological zones, or epizones. Clade 1 became entrenched in the Mekong Delta and was not supplanted by newer clades, in association with a relatively higher presence of domestic ducks. In contrast, two new clades were introduced (2.3.4 and 2.3.2) in northern Viet Nam and were associated with higher chicken density and more intensive chicken production systems. We suggest that differences in poultry production systems in these different epizones may explain these associations, along with differences in introduction pressure from neighbouring countries. The different distribution patterns found at the clade level would not be otherwise apparent through analysis treating all outbreaks equally, which requires improved linking of disease outbreak records and genetic sequence data., SCOPUS: ar.j, info:eu-repo/semantics/published

Forest, in particular deciduous forest, is a key element in determining areas with a high probability of tick presence. The way forest is generally monitored may be ill suited to some landscapes where Ixodes ricinus is found, as forest is usually characterised using crisp land cover classes. However, tree vegetation can be found outside of forests and continuous gradations of tree density can be found in a variety of landscapes. In this paper we investigate the probability of tick presence in southern Norway using landscape description based both on land cover classes and continuous data describing the tree cover fraction. Both perspectives on the landscape are significant in the logistic model, indicating that the usual approach based solely on land cover classes may not be comprehensive enough in capturing tick habitat, and characterising the landscape with variables focused on single specific elements may be insufficient.

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Collection : Manuels-Roret, Contient une table des matières, Avec mode texte

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Collection : [Manuels Roret], Collection : [Manuels Roret], Contient une table des matières, Avec mode texte

https://patrimoniodigital.ucm.es/r/thumbnail/657363, https://books.google.com/books/ucm?vid=UCM532193504X&printsec=frontcover&img=1, Entre los años 2004-2013 su signatura fue: FA 1022. - Ingresó en la Biblioteca Histórica procedente de la Facultad de Filología en 2013. - Encuadernación holandesa

Collection : [Manuels Roret], Collection : [Manuels Roret], Contient une table des matières, Avec mode texte

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