Academic literature on the topic 'Bovines movement network'

The aims of the present study were to compare centrality and other measures of bovine movement networks in the state of Mato Grosso, Brazil, in 2007, by examination of the positive and negative herds identified in the brucellosis survey conducted in 2003. In addition, we aimed to examine the association between herd size (measured by the number of females older than 24 months, denoted FEM24+) and animal trade between herds. We found a statistical association between brucellosis occurrence and both the total degree (number of traded animals) and out-degree (for the number of animals sold and the number of neighboring herds). This finding suggests that positive herds in the 2003 survey were trading (particularly selling) more frequently in 2007 than negative herds, thereby presumably increasing the risk of disease spread. Statistical differences observed (p-values) in the network of movements for reproduction purposes were more significant than those observed in other networks for average herd size; degrees of animals, batches, and neighbors; outdegree of neighbors; and betweenness. We found positive associations (p < 0.001) between the following variables: number of traded animals and the FEM24+ herd size; FEM24+ herd size and FEM24+ herd size of neighbors within the network of cattle movement; FEM24+ herd size of neighbors and number of traded animals; and weighted degree (animals) of neighbors and degree (animals) of the herd of origin. A comparison of positive and negative herds stratified by herd size (? 10 FEM24+; 11-50 FEM24+; and > 50 FEM24+), within the network of movements for reproduction purposes, revealed significant differences (p < 0.05) in the > 50 FEM24+ category only, for average herd size, total degree (animals, batches, and neighbors), outdegree (animals, batches, and neighbors), and outcloseness. Logistic regression analysis, in which average herd size and degree (animals) were both factors, showed that a tenfold increase in herd size and the number of animals traded would lead to an increased chance of a herd being positive by 41% (OR = 1.41 [1.01; 1.99]) and 39% (OR = 1.39 [1.05; 1.85]), respectively. We concluded that the presence of bovine brucellosis is associated with a larger herd size, which is consistent with other reports. We also found an association between the increased trade of bovines and the presence of bovine brucellosis. Furthermore, an association was noted between herd size and animal trade, both of which could contribute to the spread of brucellosis.

Beef exports represent a substantial part of Paraguay’s agricultural sector. Cattle movements involve a high risk due to the possible spread of bovine diseases that can have a significant impact on the country’s economy. We analyzed cattle movements from 2014 to 2018 using the networks analysis methodology at the holding and district levels at different temporal scales. We built two types of networks to identify network characteristics that may contribute to the spread of two diseases with different epidemiological characteristics: i) a network including all cattle movements to consider the transmission of a disease of rapid spread like foot and mouth disease, and ii) a network including only cow movements to account for bovine brucellosis, a disease of slow spread that occurs mainly in adult females. Network indicators did not vary substantially among the cattle and cow only networks. The holdings/districts included in the largest strongly connected components were distributed throughout the country. Percolation analysis performed at the holding level showed that a large number of holdings should be removed to make the largest strongly connected component disappear. Higher values of the centrality indicators were found for markets than for farms, indicating that they may play an important role in the spread of an infectious disease. At the holding level (but not at the district level), the networks exhibited characteristics of small-world networks. This property may facilitate the spread of foot and mouth disease in case of re-emergence, or of bovine brucellosis in the country through cattle movements. They should be taken into account when implementing surveillance or control measures for these diseases.

Livestock movements create complex dynamic interactions among premises that can be represented, interpreted, and used for epidemiological purposes. These movements are a very important part of the production chain but may also contribute to the spread of infectious diseases through the transfer of infected animals over large distances. Social network analysis (SNA) can be used to characterize cattle trade patterns and to identify highly connected premises that may act as hubs in the movement network, which could be subjected to targeted control measures in order to reduce the transmission of communicable diseases such as bovine tuberculosis (TB). Here, we analyzed data on cattle movement and slaughterhouse surveillance for detection of TB-like lesions (TLL) over the 2016–2018 period in the state of Rio Grande do Sul (RS) in Brazil with the following aims: (i) to characterize cattle trade describing the static full, yearly, and monthly snapshots of the network contact trade, (ii) to identify clusters in the space and contact networks of premises from which animals with TLL originated, and (iii) to evaluate the potential of targeted control actions to decrease TB spread in the cattle population of RS using a stochastic metapopulation disease transmission model that simulated within-farm and between-farm disease spread. We found heterogeneous densities of premises and animals in the study area. The analysis of the contact network revealed a highly connected (~94%) trade network, with strong temporal trends, especially for May and November. The TLL cases were significantly clustered in space and in the contact network, suggesting the potential for both local (e.g., fence-to-fence) and movement-mediated TB transmission. According to the disease spread model, removing the top 7% connected farms based on degree and betweenness could reduce the total number of infected farms over three years by >50%. In conclusion, the characterization of the cattle network suggests that highly connected farms may play a role in TB dissemination, although being close to infected farms was also identified as a risk factor for having animals with TLL. Surveillance and control actions based on degree and betweenness could be useful to break the transmission cycle between premises in RS.

Bovine viral diarrhea (BVD) caused by BVD virus (BVDV) leads to economic loss worldwide. Cattle that are persistently infected (PI) with BVDV are known to play an important role in viral transmission in association with the animal movement, as they shed the virus during their lifetime. In this research, the “hot spot” for BVD transmission was estimated by combining phylogenetic and epidemiological analyses for PI cattle and cattle that lived together on BVDV affected farms in Tokachi district, Hokkaido prefecture, Japan. Viral isolates were genetically categorized into BVDV-1a, 1b, and 2a, based on the nucleotide sequence of the entire E2 region. In BVDV genotype 1, subgenotype b (BVDV-1b), cluster I was identified as the majority in Tokachi district. Network analysis indicated that 12 of the 15 affected farms had cattle movements from other facilities (PI-network) and farms affected with BVDV-1b cluster I consisted of a large network. It was implied that the number of cattle movements themselves would be a risk of BVD transmission, using the PageRank algorithm. Therefore, these results demonstrate that cattle movements would contribute to disease spread and the combination of virological and epidemiological analysis methods would be beneficial in determining possible virus transmission routes.

O comércio de animais é um importante fator de risco para a disseminação de doenças entre animais e rebanhos. O objetivo do presente estudo foi caracterizar a rede de movimentação de bovinos em Pernambuco, com base nas guias de trânsito animal (GTAs) de 2012 a 2013, e identificar a intensidade da relação comercial entre os estabelecimentos. Foram analisadas 737.950 GTAs emitidas, e as movimentações de bovinos totalizaram 3.481.185 animais (1.688.585 em 2012 e 1.792.600 em 2013). Um percentual de 52,57% (1.829.907/3.481.185) das movimentações de bovinos envolveu entrada ou saída de feiras de gado, indicando que as feiras desempenharam um papel importante na rede. Aproximadamente 20% dos estabelecimentos mais conectados foram responsáveis por aproximadamente 87% das movimentações relacionadas às vendas, e 95% das movimentações, relacionadas às compras. Considerando o importante papel das feiras e o intenso comércio de bovinos entre as propriedades, medidas de vigilância e controle podem ser mais eficientes se aplicadas em feiras e estabelecimentos altamente conectados, para prevenir a propagação de doenças infecciosas.

ABSTRACT: Bovine cysticercosis is a problem distributed worldwide that result in economic losses mainly due to the condemnation of infected carcasses. One of the difficulties in applying control measures is the identification of the source of infection, especially because cattle are typically acquired from multiple farms. Here, we tested the utility of an animal movement network constructed with data from a farm that acquires cattle from several other different farms to map the major contributors of cysticercosis propagation. Additionally, based on the results of the network analysis, we deployed a sanitary management and drug treatment scheme to decrease cysticercosis’ occurrence in the farm. Six farms that had commercial trades were identified by the animal movement network and characterized as the main contributors to the occurrence of cysticercosis in the studied farm. The identification of farms with a putative risk of Taenia saginata infection using the animal movement network along with the proper sanitary management and drug treatment resulted in a gradual decrease in cysticercosis prevalence, from 25% in 2010 to 3.7% in 2011 and 1.8% in 2012. These results suggest that the animal movement network can contribute towards controlling bovine cysticercosis, thus minimizing economic losses and preventing human taeniasis.

The cattle industry is suffering economic losses caused by bovine leukemia virus (BLV) and enzootic bovine leukosis (EBL), the clinical condition associated with BLV infection. This pathogen spreads easily without detection by farmers and veterinarians due to the lack of obvious clinical signs. Cattle movement strongly contributes to the inter-farm transmission of BLV. This study quantified the farm-level risk of BLV introduction using a cattle movement analysis. A generalized linear mixed model predicting the proportion of BLV-infected cattle was constructed based on weighted in-degree centrality. Our results suggest a positive association between weighted in-degree centrality and the estimated number of introduced BLV-infected cattle. Remarkably, the introduction of approximately six cattle allowed at least one BLV-infected animal to be added to the farm in the worst-case scenario. These data suggest a high risk of BLV infection on farms with a high number of cattle being introduced. Our findings indicate the need to strengthen BLV control strategies, especially along the chain of cattle movement.

BackgroundDespite ongoing eradication efforts, bovine tuberculosis (bTB) is endemic in cattle herds in Northern Ireland (NI). This disease has serious implications for the economy, farming and animal welfare. Previous research identified a population of herds which have remained free from bTB infection for 10 years (2004–2014). Understanding the characteristics of these herds may have important implications for eradication efforts, such as spatially targeted interventions.MethodsA cluster analysis and a retrospective case–control analysis was conducted to compare bTB- free herds with herds which experienced prolonged infection (ie, bTB breakdowns lasting more than ≥ 365 days).ResultsOnly small, localised clusters of herds which have remained free from bTB were revealed, thus limiting the potential for spatially targeted interventions. The results illustrated the importance of herd size to disease status; over 27 per cent of the bTB-free herds had up to 10 animals. However, the data also showed that there were no inward movements in the year before the bTB skin test in those herds which remained free from bTB.ConclusionsAttention should therefore be given to the cattle movement network in NI to better understand the risk associated with cattle purchasing.

Bovine tuberculosis (TB) is a zoonotic disease, mainly caused by Mycobacterium bovis. France was declared officially TB free in 2001, however, the disease persists in livestock and wildlife. Among wild animals, deer are particularly susceptible to bovine TB. Here, a whole genome sequence (WGS) analysis was performed on strains with the same genetic profile—spoligotype SB0121, Multiple Loci VNTR Analysis (MLVA) 6 4 5 3 11 2 5 7—isolated from different types of outbreaks, including from deer or cattle herds, or zoological or hunting parks where the presence of infected deer was a common trait in most of them. The results of the phylogeny based on the SNP calling shows that two sub-clusters co-exist in France, one related to deer bred to be raised as livestock, and the other to hunting parks and zoos. The persistence over almost 30 years of sporadic cases due to strains belonging to these clusters highlights the deficiency in the surveillance of captive wildlife and the need for better monitoring of animals, especially before movement between parks or herds.

Cattle behaviour is a significant indicator of cattle welfare. With the advancements in electronic equipment, monitoring and classifying multiple cattle behaviour patterns is becoming increasingly important in precision livestock management. The aim of this study was to detect important cattle physiological states using a neural network model and wearable electronic sensors. A novel long short-term memory (LSTM) recurrent neural network model that uses two-way information was developed to accurately classify cattle behaviour and compared with baseline LSTM. Deep residual bidirectional LSTM and baseline LSTM were used to classify six behavioural patterns of cows with window sizes of 64, 128 and 256 (6.4 s, 12.8 s and 25.6 s, respectively). The results showed that when using deep residual bidirectional LSTM with window size 128, four classification performance indicators, namely, accuracy, precision, recall, and F1-score, achieved the best results of 94.9%, 95.1%, 94.9%, and 94.9%, respectively. The results showed that the deep residual bidirectional LSTM model can be used to classify time-series data collected from twelve cows using inertial measurement unit collars. Six aim cattle behaviour patterns can be classified with high accuracy. This method can be used to quickly detect whether a cow is suffering from bovine dermatomycosis. Furthermore, this method can be used to implement automated and precise cattle behaviour classification techniques for precision livestock farming.

Generally, the movement of cattle within any country including Italy is very essential to the economics of livestock industry. However, this transmission can also carry and spread the risk of contracting the disease (infectious diseases) by other cattle in various geographical areas. For example, this pattern of animal movements brought about an outbreak of foot-and-mouth infectious disease throughout the UK in 2001. Also as Taylor et. al (2001) mentioned that these diseases can give rise to the productivity decline and even can lead to some threats to human health. Therefore, to reduce the risk and economic loss of this kind of contagious diseases, authorities should be able to manage and control them (Andesron, 2002). This control measures can consist of monitoring the animal trades, inspecting entry to and exit from premises, adopting some eradication programs (say, sending sick cattle to slaughterhouses), quarantining cattle, and etc. To properly assess this kind of control measures, we need a comprehensive and detailed information and regulation about the cattle movement pattern. To address these issues, European Economic Community (EEC) devised some regulations and imposed them on its member states to adhere to these measures (EU traceability framework). Actually, these measures originate from the public health and food health concerns, which are related to animal health and the economic impacts of the outbreak of infectious diseases. The EEC issued Council Directive 92/102/EEC in 1992 (with latest modifications in 2013), which obliged member states to record the origin and destination point of each cattle. Also, each cattle should be tagged by an ear tag to be traceable . Specifically, European Parliament and European council in 2000 tried to simplify and implement this process through a digital framework that allows countries to identify and register their bovines . In Italy, this procedure was done by Italian National Animal Identification and Registration Database which proposes us a rich and valuable dataset, including the all required parameters, to perform and analyze some important determinants of Bovines movements and the effects of this kind of disease outbreaks on the pattern of bovines trade among different holdings. In recognition of the importance of national and international bovines’ trade, this thesis attempts to assess and investigate some relevant determinants of bovines movements among Italian holdings and Italian provinces. This study consists of three chapters. In the first chapter, we introduced a structural gravity model of trade and then we linked it to the Italian bovine trade system. Then, we assessed two important determinants of any animal movements, i.e. feed prices and financial literacy rate of farmers. In addition, we tried to analyze the interaction of these determinants on the movements of bovines among Italian provinces. We found that feed (corn, in our case) price shocks and financial literacy rate of farmers could significantly affect on the pattern of bovines movement. Furthermore, our findings suggest that this two factors have a close relationship together and can offset each other's effects, in the sense that the enhancing financial literacy rate of farmers can somehow immune them to the unexpected price shocks and actually undermine the effects of unfavorable price shocks on their business. In the second chapter, we used again the structural gravity model and employed it to investigate the risk of the outbreak of bovine diseases among Italian provinces. We found that the disease incidence rate has a significant positive effect of the movement of bovines from origin nodes to destination points. Also, we tried to merge our findings with the feed (corn) price effects and saw that these two factors act in a different direction. That is the more is the incidence rate, the effect of feed prices become less relevant to the movement of bovines among different provinces. In chapter 3, we tried to have a more detailed view on the effects of disease outbreaks on the movements of bovines among farms and slaughterhouses. In general, we found that the disease status has a negative effect on bovines movement from farms to farms, and a positive influence on the movements of bovines from farms to slaughterhouses. In addition, we found that the ownership has a significant role in determining the pattern of trade among holdings, in the sense that the results are reliable only if two trading partners have different owner/keeper. Although, if the effects were driven by movements between farms with the same owner, it would be a rational decision by the owners in order to separate and protect healthy bovines from sick bovines. However, we found that in the case of positive disease tests, distance has a positive effect on the movement of bovines between various farms. This somehow shows us that some farms may act in such an opportunistic behaviors that can even lead to the spread of diseases among different regions. Finally, we analyzed some network characteristics of the bovines movements to see the effect of network structure and its interaction with disease status on the pattern of movements. More specifically, we used the most commonly used feature of any network i.e. indegree, outdegree, and degree and found that in the case of diseases the farms tend to send more bovines to the slaughterhouses. Actually, the results on the interaction of indegree and disease tests show us that the farms that have received more (probably sick) bovines from more suppliers in the previous period, tend to send more bovines to other farms in the current time period. Also, we should note that the indegree analysis can help us tracing back the diseases to the nodes that are more exposed to receiving bovines and consequently more subject to contracting diseases. On the other hand, we found the outdegree is also important only in case of the trade from farms to other farms. This tells us that in the case of diseases, the farms tend to not change significantly the pattern of their trading partners (other farms), and probably they tend to send their (probably sick) bovines to the other farms and this situation can even decrease the number of heads which transfer from farms to slaughterhouses. This confirms the importance of such nodes in the network in the sense that those with higher outdegree can be considered as most dangerous nodes and can act as a source of spreading diseases among different premises.

Uma análise da rede de movimentação de bovinos entre estabelecimentos do Estado de Mato Grosso foi realizada utilizando os dados das guias de trânsito animal (GTA) emitidas durante o ano de 2007. A utilização de parâmetros descritivos da rede de movimentação de bovinos permitiu a caracterização da intensidade de comercialização de bovinos entre os estabelecimentos. Os parâmetros calculados foram: grau (entrada e saída), betweenness, closeness, coeficiente de aglomeração e PageRank. Dados referentes ao status das propriedades (foco ou livre de brucelose) obtidos do banco de dados do levantamento para brucelose bovina do Programa Nacional de Controle e Erradicação da Brucelose e da Tuberculose Animal (PNCEBT) foram utilizados para comparar os parâmetros das propriedades positivas e negativas para brucelose. A comparação foi realizada pelo teste de Mann Whitney e foi encontrada diferença estatisticamente significante (P< 0,05) apenas para os parâmetros grau total e de saída ponderados por número de animais e ponderados por número de lotes movimentados. A análise descritiva da rede de movimentação de bovinos mostra que a distribuição de valores para todos os parâmetros, exceto o closeness, seguiu qualitativamente a Lei de potências. As informações obtidas são importantes para auxiliar em medidas de controle e prevenção de doenças em rebanhos bovinos, como a brucelose.
An analysis of the network of cattle movement between farm premises of the state of Mato Grosso was carried out using data from the records of animal transit (GTA) collected during 2007. The use of descriptive parameters of the network of movement allowed the characterization of the intensity of bovine trade between the farm premises. The parameters calculated were: degree (incoming and outgoing), betweenness, closeness, clustering coefficient and PageRank. The database concerning the status of the premises (positive or brucellosis free) obtained from the survey for bovine brucellosis of National Programme for Control and Eradication of Brucellosis and Tuberculosis Animal (PNCEBT) was used to compare the parameters of positive and negative premises for brucellosis. The comparison was done by using the Mann Whitney test and found a statistically significant difference (P <0.05) for the parameters total degree and outgoing degree weighted by number of animals and number of batches. The descriptive analysis of the network of bovine movements showed that the distribution of values for all parameters, except the closeness, qualitatively followed a power law. The information obtained is important to assist in control measures and prevention of diseases in cattle herds, such as brucellosis.

A dinâmica de movimentação de animais em uma rede de propriedades rurais e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle destas. Neste projeto, foram implementados algoritmos para gerar redes de movimentação de animais hipotéticas e reconstruiu-se a rede de movimentações de bovinos do Estado do Mato Grosso, 2007, Brasil. Foram feitas diversas simulações a fim de verificar o espalhamento de doenças agudas e crônicas nessas redes. Diferentes dinâmicas de espalhamento de doenças infecciosas foram observadas em redes com a mesma distribuição de graus e diferentes estruturas topológicas. Espera-se que os resultados das simulações matemáticas possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e incentivar outros Estados a seguirem o exemplo do Estado do Mato Grosso, a construírem bancos de dados que possam ser analisados utilizando a metodologia de redes.
The animals\' movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. In this project, we have implemented algorithms to generate hypothetical networks of animals\' movements and rebuilt the network of bovine movements from the State of Mato Grosso, 2007, Brazil. We made several simulations in order to check the spreading of acute and chronic disease in these networks. Different dynamics of infectious disease spreading were observed in networks with the same degree distribution and different topological structure. We hope that the results of the mathematical simulations may assist in the activities of agencies responsible for disease surveillance and encourage other States to follow the example of the State of Mato Grosso, to build databases that can be analyzed using the methodology of networks.

A movimentação de animais em uma rede de fazendas e o espalhamento de algumas doenças animais estão intrinsecamente relacionados. Assim, compreender a dinâmica do espalhamento de doenças infecciosas nestas redes é um instrumento importante no controle dessas doenças. Usando as informações sobre as movimentações de bovinos no estado de Mato Grosso, Brasil, em 2007, reconstruiu-se a rede de trânsito e a rede de proximidade geográfica entre os estabelecimentos desse estado, além de redes hipotéticas seguindo os modelos de rede Molloy-Reed, Kalisky, Método A e Método B, onde simulou-se, usando diferentes configurações do modelo SLIRS, o espalhamento de doenças com parâmetros hipotéticos e reais (brucelose e febre aftosa). Além disso, simulou-se o controle do espalhamento dessas doenças considerando o controle por imunização e por restrição, com e sem rearranjo das movimentações após a restrição, selecionando os estabelecimentos a serem protegidos de forma aleatória, baseando-se no grau de movimentação dos animais e utilizando o conceito do paradoxo da amizade. Dentre os resultados, destacam-se que apesar dos padrões das curvas de prevalência nas redes hipotéticas serem semelhantes aos da rede real, os valores observados foram maiores nas redes hipotéticas, indicando que utilizá-las no planejamento de políticas de controle de doenças no lugar da rede real pode levar a um maior uso de recursos do que seria necessário. Além disso, no controle das doenças tanto com parâmetros hipotéticos quanto com parâmetros reais, nas simulações usando apenas a rede de trânsito dos animais, observou-se uma redução mais efetiva da prevalência ao se selecionar os estabelecimentos com maior grau total do que a da seleção aleatória, enquanto que nas simulações que consideraram a rede de proximidade geográfica dos estabelecimentos, a redução na prevalência das estratégias que selecionaram estabelecimentos específicos foram semelhantes aos da seleção aleatória. Sobre o efeito do rearranjo das movimentações, observou-se que este pode facilitar o espalhamento de doenças na rede, mesmo nas situações em que se aplica alguma estratégia de controle. Espera-se que os resultados das simulações matemáticas possam contribuir para a discussão do impacto relativo entre as estratégias de controle mencionadas e que futuramente possam auxiliar nas atividades dos órgãos responsáveis pela vigilância epidemiológica e no desenvolvimento de políticas de prevenção e controle de doenças em animais.
The animals’ movements in a farms network and the spread of some animal diseases are intrinsically related. Therefore, comprehending the dynamics of the spreading of infectious diseases in these networks is an important tool in controlling these diseases. Using the information about the bovine movements from the State of Mato Grosso, Brazil, in 2007, we rebuilt the network of animal movements and the geographic proximity network between the premises of this state, in addition to hypothetical networks following the network models Molloy-Reed, Kalisky, Method A and Method B, where we simulated, using different configurations of the model SLIRS, the spread of diseases with hypothetical parameters e real ones (brucellosis and foot and mouth disease). Moreover, we simulated the control of these diseases spreading, considering the control by immunization and by restriction, with and without the rearrangement of the movements after the restriction, selecting the premises to be protected randomly, based on the degree of animal’s movements and using the concept of the friendship paradox. Among the results, stands out that although the pattern of the prevalence curves in the hypothetical networks were similar to the ones in the real network, the observed values were higher in the hypothetical networks, indicating that using them in the planning of policies to control diseases in place of the real network might lead to a greater expense of resources than it would be necessary. Furthermore, in the control of the diseases both with hypothetical parameters as well as with real parameters, in the simulations using only the animal’s movements network, it was observed a more effective reduction of the prevalence when selecting the premises with the highest total degree than the random selection, while in the simulations that considered the network of geographic proximity of the premises, the reduction in the prevalence of the strategies that selected specific premises were similar to the random selection. On the effect of rearranging the movements, it was observed that it may facilitate the spread of diseases in the network even in situations where some control strategy is used. We hope that the results of the mathematical simulations may contribute to the discussion of the relative impact of the mentioned control strategies and that in the future they may assist in the activities of agencies responsible for disease surveillance and in the development of policies to prevent and control diseases in animals.

Les échanges d'animaux d'élevages entre exploitations agricoles favorisent la diffusion à grande échelle des maladies. L’enjeu est non seulement économique, de par les répercussions fortes sur les marchés de produits d’origine animale en cas de crise, mais également de santé publique, de nombreuses maladies animales étant transmissibles à l’homme (comme la tuberculose bovine). La traçabilité des animaux devient alors une question de plus en plus importante pour retrouver les foyers infectieux, et lutter contre la propagation des maladies. Le développement de ce type de données et leur accessibilité grandissante a permis l’émergence d’études sur leur organisation et leur dynamique. Les outils et modèles développés pour l’étude des réseaux sociaux ont été adaptés à l’étude de ces données. L'apport de cette thèse réside dans l’utilisation de mesures et de modèles intégrant l’information temporelle sur les échanges d’animaux. En effet, le développement des réseaux temporels est relativement récent, et peu d’études les ont à ce jour appliqué échanges d’animaux. L’objectif est donc double, participer au développement des outils d’analyse des réseaux temporels, et en déduire des pistes de développement de mesures de surveillance et de lutte contre la propagation des maladies entre exploitations
Disease spread among agricultural premises is greatly enhanced by cattle trade movements. Preventing spreading is a key issue for economical issues, for instance to prevent trade restrictions, but also for public health. Indeed, many animal diseases affect human beings, such as bovine tuberculosis. Tracing cattle trade movements is aiming at detecting the sources of infection, and thus, helps fighting against disease spread. Accessing databases recording cattle trade movements allows to study the structure and dynamic of the exchanges. To do so, methods developed for Social Network Analysis are more and more adapted and use for these purposes. The aim of this work is to use temporal models and methods to study cattle trade movements. As the development of temporal networks is relatively recent, few analyzes using these methods have been conduct on cattle trade data. Thus, contributions are twofold in this work: taking part to the development of analysis tools of temporal networks, and then, deducting potential ways of enhancement to control and fight against disease spread among holdings