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The Atlantic Forest biome is considered an area in which tick fever is endemic, while the Caatinga biome is considered an area in which tick fever is non-endemic. A survey on cattle tick fever was carried out in 448 cattle farms located in an area of the Atlantic Forest biome which borders the Caatinga biome. A retrospective study of five years, conducted from January 2018 to October 2022, allowed for the identification of the occurrence of tick fever in 44 out of the 448 herds visited. In 70.5% (31/44) of the herds involved, the disease was caused by Anaplasma marginale; in 6.8% (3/44), the disease was caused by Babesia spp.; and in 22.7% (10/44), the disease was caused by a coinfection of Babesia spp. and A. marginale. The disease mainly occurred from August to November (23/44). Bos taurus or B. taurus crossbreed animals were most affected (29/44) in an area in which 94% of the cattle were Bos indicus and 6% were B. taurus and B. taurus crossbreeds. In 24 herds (with adults affected in 17 and calves in 7), the implicated animals had recently been moved to the Atlantic Forest. In the other 20 herds (calves with heavy tick infestations were affected in 17 and adults in 3), tick fever occurred in non-moved cattle. Even though it is an endemic zone, tick fever is common and mainly affects B. taurus cattle, including adults moved from areas with enzootic instability and calves under nine months old with high tick loads.

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OBJECTIVES: Animal movement is an important factor in the transmission of infectious diseases among livestock. A better understanding of animal movement characteristics provides a more reliable estimation of disease spread and promotes modeling studies. In Japan, all the cattle movement information is recorded in a national database called the Individual Cattle Identification Register (ICIR)." Our previous studies using this information demonstrated heterogeneity in the movement of dairy and beef cows according to location, season, and age. The present study describes the probability distributions of the movement of Japanese dairy and beef cows in the following month on a regional basis. DATA DESCRIPTION: This publication contains four probability distribution datasets for the predicted locations of dairy and beef cows in Japan in the following month, which were developed using individual cattle movement information obtained from the ICIR. These datasets provide information on cattle movement in the following month on a regional basis, given properties such as birth region, location, time, and age.

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Animal movement is an important factor in the transmission of animal infectious diseases. A better understanding of movement patterns is therefore necessary for developing effective control measures against disease spread. In Japan, a cattle tracing system was established in 2003, following a bovine spongiform encephalopathy epidemic, and the information on all cattle movements has been stored in a national database maintained by the National Livestock Breeding Center. Using these data, we previously analyzed the movement of dairy cows, concluding that heterogeneities in cattle movement are associated with regional and seasonal factors. In the present study, we aimed to identify specific factors affecting the regional and seasonal movement patterns of beef cows in Japan. From April 2012 to March 2017, 797,553 farm-to-farm movement events were recorded. We analyzed movements by month and by cattle age and looked at the frequency of movement within and between seven regions spanning the national territory. Our results show that calf movement peaked at 9-10 months old; these movements were considered to be via the market and were frequent within and between regions. For inter-regional movements, Kyushu region was the top producer of calves for calf trading markets throughout Japan. With regard to intra-regional movements, round-trip movements for summer grazing were observed in May and October for cattle of various ages in the northern regions, especially Hokkaido and Tohoku. Moreover, the movements of Japanese Shorthorn breeds in Tohoku region exhibited consistent annual peaks in May and October/November, in accordance with their seasonal breeding practice. In the areas with high relative densities of dairy cows, such as Hokkaido, the shipping of newborn beef calves produced via embryo transfer to dairy cows was also observed. Overall, understanding the patterns of beef cow movement will help develop effective disease surveillance measures, such as pre-movement inspections focused on specific regions and types of movement.

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We used logistic regression to investigate whether the risk of an Irish cattle herd undergoing a bovine tuberculosis (bTB) breakdown increased with the size of the Ingoing Contact Chain (ICC) of previous herd to herd cattle movements, in a sequence up to eight moves back from the most recent, direct, movement into the herd. We further examined whether taking into account the bTB test history of each herd in the chain would improve model fit. We found that measures of cattle movements directly into the herd were risk factors for subsequent bTB restrictions, and the number of herds that animals were coming from was the most important of these. However, in contrast to a previous study in Great Britain, the ICC herd count at steps more remote than direct movements into the herd did not result in better fitting models than restricting the count to direct movements. Restricting the ICC counts to herds which had previously or would in the future test positive for bTB resulted in improved model fits, but this was not the case if only the previous test status was considered. This suggests that in many cases bTB infected animals are moving out of herds before being identified through testing, and that risk-based trading approaches should not rely solely on the previous test history of source herds as a proxy for future risk. Model fit was also improved by the inclusion of variables measuring bTB history of the herd, bTB in neighbouring herds, herd size, herd type, the movement network measures "in strength" and "betweenness", altitude, modelled badger abundance and county. Rainfall was not a good predictor. The most influential measures of bTB in nearby herds (a proxy for neighbourhood infection) were the proportion of herds with a history of bTB whose centroids were within 6 km, or whose boundaries were within 4 km, of the index herd. As well as informing national control and surveillance measures, our models can be used to identify areas where bTB rates are anomalously high, to prompt further investigation in these areas.

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BACKGROUND: Animal movement is considered the most significant factor in the transmission of infectious diseases in livestock. A better understanding of its effects would help provide a more reliable estimation of the disease spread and help develop effective control measures. If the movement pattern is heterogeneous, its characteristics should be considered in epidemiological analyses, such as when using simulation models to obtain reliable outputs. In Japan, following the bovine spongiform encephalopathy epidemic, a traceability system for cattle was established in 2003, and the registration of all cattle movements in the national database began. This study is the first to analyze cattle movements in Japan. We examined regional and seasonal heterogeneity in dairy cow movements, which accounted for most Japanese breeding cattle. RESULTS: In the 14 years from April 2005 to March 2018, 4,577,709 between-farm movements of dairy cows were recorded, and the number of movements was counted by month and age for both inter- and intra-regional movements. As a result, two characteristic round-trip movements were observed: one was non-seasonal and inter-regional movements related to cattle-breeding ranches in Hokkaido (the northern region of Japan), which consists of the movement of cows around ages 6 to 8 and 21 to 23 months old. In addition, the seasonal movement of heifers for summer grazing within Hokkaido occurred in May and October at the peak ages of 13 to 14 and 19 to 20 months old, respectively. The observed heterogeneity seemed to reflect the suitability of raising the Holstein breed in Hokkaido and the shortage of supply of replacement heifers and available farming areas outside Hokkaido. CONCLUSIONS: Understanding the patterns of dairy cow movements will help develop reliable infectious disease models and be beneficial for developing effective control measures against these diseases.

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Our aim was to examine, for the first time, the spatial and network characteristics of cattle movements between herds in the Republic of Ireland (ROI), to inform policy and research of relevance to the surveillance and management of disease in Irish cattle. We analysed movements in 2016 as discrete herd to herd pairings (degree), herd to herd pairings by date of move (contacts) and herd to herd pairings by date and individual animal (transfers), and looked at each of these as movements out of a herd (out degree, out contacts, out transfers) and into a herd (in degree, in contacts, in transfers). We found that the frequency distributions, by herd, of these six move types were all heavily right skewed but in the case of the 'out' data types more closely followed a log-normal than the scale free distribution often reported for livestock movement data. For each distinct herd to herd contact in a given direction, over 90 % occurred only once, whereas the maximum number of occurrences was 62. Herd-level Spearman rank correlations between inward moves (represented as in degree, in contacts, in transfers) and outward moves (out degree, out contacts, out transfers) were weak or even negative whereas correlations between different measures of outward moves or inward moves (e.g. out degree vs. out contacts, in transfers vs. in degree) were stronger. Correlations between these variables and the network measure betweenness varied between r = 0.513 and r = 0.587. Some herds took part in a relatively large number of movements whilst also retaining their cattle for long periods (> 100 days) between moves. In and out degree, contacts and transfers were mapped across Ireland on a 5 km grid, and additionally normalized per 1000 animals and per herd. We found considerable variation in the number of movements by county. Approximately half of transfers were conducted within a single county, but the number and distance of between county movements varied considerably by county of origin and county of destination, with the proportion of moves completed within a single county correlated with its size. Herds exchanging cattle via a market were generally further apart than when moves were made directly herd to herd. For contacts, the distances moved away from the herd were on average greater for origin herds in the west of ROI whereas distances moved to a herd were generally greater for destination herds in the centre-east and the north-west.

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Between-farm transmission of bovine tuberculosis (bTB) occurs mostly through fence-to-fence contact between neighbouring farms, endemic infected wildlife or movement of infected animals. Unfortunately, bTB detection is frequently delayed and identification of the source of introduction is often difficult, particularly in endemic regions. Here, we characterized the cattle movement network of Castilla y Leon, a high bTB-prevalence (1.9% at the farm level in 2015) region in Spain, over six years and analysed the distribution of bTB to ultimately assess the likelihood of spatial and movement-mediated transmission. We analysed movement and bTB data from 27,633 units located in the region, of which 87% were involved in ~1.4 million movements of ~8.8 million animals. Network-level connectivity was low, although a few highly connected units were identified. Up to 15% of the herds became bTB-positive at some point during the study, with the highest percentage found in bullfighting and beef herds. Although bTB-positive herds had a significantly higher degree and moved more cattle than negative herds. Results of the k-test, a permutation-based procedure, suggested that positive farms were not significantly clustered in the movement network. Location was a likely risk factor as bTB-positive farms tended to be located within 5 km from each other. Results suggested that movements may be a source of bTB in cattle in Castilla y Leon, although local factors may be more influential in determining risk of disease at the farm level. The description of the movement network in Castilla y Leon may be valuable for bTB surveillance in Spain. Moreover, results are useful to assess the movement-associated risk for multiple diseases.

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The analysis of animal movement patterns may help identify farm premises with a potentially high risk of infectious disease introduction. Farm herd sizes and bovine movement data from 2007 in the state of Mato Grosso, Brazil, were analyzed. There are three different biomes in Mato Grosso: the Amazon, Cerrado, and Pantanal. The analysis of the animal trade between and within biomes would enable characterization of the connections between the biomes and the intensity of the internal trade within each biome. We conducted the following analyses: 1) the concentration of cattle on farm premises in the state and in each biome, 2) the number and relative frequency of cattle moved between biomes, and 3) the most frequent purposes for cattle movements. Twenty percent (20%) of the farm premises had 81.15% of the herd population. Those premises may be important not only for the spread of infectious diseases, but also for the implementation of surveillance and control strategies. Most of the cattle movement was intrastate (97.1%), and internal movements within each biome were predominant (88.6%). A high percentage of movement from the Pantanal was to the Cerrado (48.6%), the biome that received the most cattle for slaughter, fattening and reproduction (62.4%, 56.8%, and 49.1% of all movements for slaughter, fattening, and reproduction, respectively). The primary purposes for cattle trade were fattening (43.5%), slaughter (31.5%), and reproduction (22.7%). Presumably, movements for slaughter has a low risk of disease spread. In contrast, movements for fattening and reproduction purposes (66.2% of all movements) may contribute to an increased risk of the spread of infectious diseases.(AU)

A análise dos padrões de trânsito animal pode ajudar a identificar estabelecimentos sob um risco potencialmente maior de introdução de doença infecciosa. Foram analisadas a rede de trânsito de bovinos no estado do Mato Grosso, Brasil, e uma base de dados com tamanho de rebanho, ambas de 2007. Há três biomas diferentes em Mato Grosso: Amazônia, Cerrado e Pantanal. A análise do trânsito animal entre e dentro dos biomas nos permitiu caracterizar quão conectados são os biomas e quão intenso é o trânsito interno dentro de cada bioma. Conduzimos as seguintes análises: 1) se o rebanho bovino está concentrado em alguns estabelecimentos no estado todo e em cada bioma; 2) sobre o número absoluto e a frequência relativa de bovinos movimentados entre os biomas; e 3) quais são os propósitos mais frequentes para o trânsito animal. Encontramos que 20% dos estabelecimentos possuíam 81,15% do rebanho total do estado. Estes estabelecimentos podem ser importantes para o espalhamento de doenças infecciosas, mas também para a implementação de estratégias de vigilância e controle. A maior parte do trânsito foi dentro do estado (97,1%), e o trânsito interno dentro de cada bioma foi predominante (88,6%). Um percentual alto de movimentos do Pantanal (48,6%) foi para o Cerrado, o bioma que recebeu mais bovinos para abate, engorda e reprodução (62,4%, 56,8% e 49,1% de todos os movimentos para abate, engorda e reprodução, respectivemente). Os principais propósitos para o comércio de bovinos foram engorda (43,5%), abate (31,5%) e reprodução (22,7%). Movimentos para abate presumivelmente oferecem um baixo risco para espalhamento de doença. Em contraste, movimentos para engorda e reprodução (66,2% de todos os movimentos) podem contribuir para o aumento do risco de espalhamento de doenças infecciosas.(AU)

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The Republic of Ireland has a national eradication programme for bovine viral diarrhoea virus (BVDv) based on tissue-tag testing of calves to identify persistently infected animals (PIs). It has been proposed that serological testing of a sample of home-bred young stock would be a more cost effective surveillance mechanism than continued tissue-tag testing in herds which have previously been found to be BVD-free. These animals would have to be at least 6 months of age to avoid interference from maternal antibodies in test results. To examine the potential practicality of this system, we identified birth profiles and movements of calves born in Ireland during 2014 and 2015. We found that birth profiles for both beef and dairy animals were more evenly distributed throughout the year than often assumed, which should be borne in mind when evaluating the suitability of a single round of serological testing in the autumn for every herd. A large amount of movement was identified, with approximately 43% of calves experiencing a move before they reached 10 months of age, including moves to another Irish herd, to a knackery, to export, or to slaughter. Approximately 19% of calves had moved to other breeding herds in Ireland within this period. There were distinct patterns according to movement type, month of birth and herd type. The majority of herds moved either all or none of their calves in the first 10 months of life. These results indicate that young stock serological testing is unlikely to be an appropriate surveillance mechanism for all BVDv-free herds, as (i) many herds would not be able to supply a large enough sample of suitably aged home-bred young stock at a single point in time and (ii) PIs which would have been picked up by tissue-tag testing soon after birth would have moved from their home herd, to infect other herds, before serological testing could be conducted.

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The aim of this study is to provide insight the network of cattle movement in Kampong Cham, Kampong Speu and Takeo, Cambodia. A cross-sectional study was carried out from July 2014 to August 2014, using questionnaires. It was implemented with 435 interviewees (24.4%, 24.6% and 51.0% from Kampong Cham, Kampong Speu and Takeo, respectively) using one-step snowball sampling. The findings suggest that the key players in all three provinces are producers who raise their cattle as backyard animals. In all three provinces the key players in spreading disease are probably the middlemen, collectors, brokers or traders. The network of cattle movement is presented as a strong component of varying size in each location. In this network we found three cut-points in both Kampong Cham and Kampong Speu. The network in each province indicates a random pattern of node distribution. The results of our study are useful to relevant authorities and researchers to understand the spread of infectious diseases into different areas. The middlemen, collectors, brokers and traders need to be controlled as first priority in order to reduce the magnitude of the spread of disease.

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Cattle movement is one of the most important risk factors for the occurrence of an epidemic. It is a legal requirement in Switzerland that every cattle movement be reported, and this information is held in the Swiss cattle movement database (Tierverkehrsdatenbank, TVD). Using this data we examined all movements, focusing on the geographical distribution of these movements in relation to the spread of epizootic diseases. We considered the period 01 January 2011 through 30 January 2012, in which a total of 786'462 cattle were moved. Looking at premises individually, a maximum of 901 possible transfers of an infectious agent were found on a specific day after the arrival of another cattle. Furthermore, we found that there were more cattle movements in summer than in winter, due to movements of cattle to and from alpine pastures. There were also prominent regional differences. On the first day after the arrival of a cattle there was a minimum of zero and a maximum of 99'168 possible transfers of an infectious agent. Nevertheless, in most cases there were no cattle moved on the first day following the arrival of a cattle (91.4%). In terms of our epizootics of interest, the following numbers of cattle were moved within the relevant incubation periods: 19'779'551 possible transfers for the Lumpy skin disease, with an incubation period of 28 days; 9'891'665 or 15'025'741 possible transfers for foot and mouth disease, depending on the incubation period of 14 or 21 days; 15'025'741 possible transfers for cattle plague and vesicular stomatitis, both with an incubation period of 21 days. The presented data show a large cattle traffic in Switzerland, and therefore suggest that it is very seldom that an infectious agent is able to start an epidemic.

Les déplacements des bovins en tant que facteur de risque épidémiologique Les déplacements d'animaux constituent un des risques les plus importants pour la survenance d'une épidémie. En Suisse, il est prescrit que chaque déplacement d'un animal de rente doit être annoncé et saisi dans la Banque de Données sur le Trafic des Animaux (BDTA). Sur la base de ces annonces, nous avons examiné tous les déplacements de l'année 2011 et concentré notre attention sur leur répartition géographique par rapport à l'extension des maladies animales contagieuses. Entre le 1er janvier 2011 et le 30 janvier 2012, 786'462 bovins au total ont été déplacés. Ce sont au maximum 901 contacts avec possibilité de transmission d'un agent infectieux qui se sont produits un jour donné après l'arrivée d'un nouvel animal. Vu les déplacements liés à la montée et à la descente de l'alpage, il y a eu plus de déplacements en été qu'en hiver. On constate également des différences régionales. Le premier jour après l'arrivée d'un bovin, il existait au minimum 0 et au maximum 99'168 contacts possibles pour la transmission d'un agent infectieux. Dans la plupart des cas (91.4%), il ne se produisait pas de trafic de bovins le jour suivant l'arrivée d'un animal. En ce qui concerne les maladies contagieuses des bovins revêtant un intérêt en Suisse, on a relevé les contacts de bovins suivants durant la période d'incubation: 19'779'551 pour la lumpy skin disease, avec un temps d'incubation de 28 jours, 9'891'665 ou 15'025'741 pour la fièvre aphteuse, selon qu'on considère un temps d'incubation de 14 ou de 21 jours, 15'025'741 pour la peste bovine et la stomatite vésiculeuse, toutes deux avec un temps d'incubation de 21 jours. Ces chiffres démontrent un grand trafic d'animaux en Suisse. C'est une indication qu'un agent infectieux ne peut que rarement faire démarrer une épidémie.

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Movement of animals from one farm to another is a potential risk and can lead to the spreading of livestock diseases. Therefore, in order to implement effective control measures, it is important to understand the movement network in a given area. Using the SANITEL data from 2005 to 2009, around 2 million cattle movements in Belgium were traced. Exploratory analysis revealed different spatial structures for the movement of different cattle types: fattening calves are mostly moved to the Antwerp region, adult cattle are moved to different parts in Belgium. Based on these differences, movement of cattle would more likely cause a spread of disease to a larger number of areas in Belgium as compared to the fattening calves. A closer inspection of the spatial and temporal patterns of cattle movement using a weighted negative binomial model, revealed a significant short-distance movement of bovine which could be an important factor contributing to the local spreading of a disease. The model however revealed hot spot areas of movement in Belgium; four areas in the Walloon region (Luxembourg, Hainaut, Namur and Liege) were found as hot spot areas while East and West Flanders are important "receivers" of movement. This implies that an introduction of a disease to these Walloon regions could result in a spread toward the East and West Flanders regions, as what happened in the case of Bluetongue BTV-8 outbreak in 2006. The temporal component in the model also revealed a linear trend and short- and long-term seasonality in the cattle movement with a peak around spring and autumn. The result of this explorative analysis enabled the identification of "hot spots" in time and space which is important in enhancing any existing monitoring and surveillance system.

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Bovine tuberculosis (Mycobacterium bovis) is an ongoing management issue in the state of Michigan with eradication from livestock as the ultimate goal. Eradication has been a challenge owing to the presence of a wildlife reservoir; competing interests in managing the livestock and wildlife hosts; and many uncertainties in transmission dynamics of M. bovis. One of the cornerstones of the eradication effort has been to stop movement of infected cattle among farms by imposing strict pre-movement testing on cattle being moved within, into and out of the Modified Accredited Zone (MAZ) in northeastern Michigan. In addition to pre-movement tuberculosis testing, detailed information about the origin and destination premises of all movements within the MAZ has been recorded in Michigan. The aim of this study was to describe the farm-to-farm movements of cattle within the MAZ, report changes in the network of movements during a 6-year period when the MAZ was a constant size (2004-2009), and examine changes in cattle movement patterns when the MAZ was reduced from 11 to 5 counties in 2010. Non-slaughter cattle movement within the MAZ was characterized by predominantly local movements at a sub-county scale. Premises that shipped cattle were primarily senders or receivers, but rarely both. From 2004 to 2009, the number of cattle shipped, size of shipments, number of shipments and distance of shipments decreased; there was little change in the network patterns of interaction among individual premises; and interactions among all premises became more disconnected. After accounting for MAZ size, there were also no changes in cattle movement network patterns following the reduction of the MAZ in 2010. The movement of cattle was likely not a key risk factor in bTB spread among premises in the MAZ during the study period and the effect of zonation and movement regulations appeared to further reduce the risk of tuberculosis spread via cattle movements among farms in Michigan's MAZ.

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