Cattle Movement Research Articles

Individual-based model for the control of Bovine Viral Diarrhea spread in livestock trade networks

Bovine Viral Diarrhea (BVD) is a cattle disease that causes substantial financial losses, in particular to the dairy industry. Hence, several countries including Germany introduced compulsory disease control programs. For the case of Germany in particular, all animals had to be tested and persistently infected animals (PI animals) were removed from the population. The program was successful in reducing the number of PI animals, but was overtly expensive. Alternative approaches were therefore discussed to eliminate the remaining PI animals and alter the testing system in order to reduce costs. Contributing to these efforts, we developed an agent-based model that aimed to cover all relevant aspects of the disease biology and would allow to evaluate different control strategies. For the biological part of the infection spread, the model includes horizontal and vertical transmission, transient and persistent infections. Moreover, several control strategies including import of animals, trade restrictions, vaccination, as well as various testing schemes were included. The model was furthermore defined to be stochastic, event-driven and hierarchical, with cattle movements as the main route of spreading between farms. For the spread within farms, we included susceptible-infected-recovered (SIR) dynamics with an additional permanently infectious class. The interaction between the farms was described by a supply and demand farm manager mechanism governing the network structure and dynamics. Additionally, we carried out a sensitivity analysis of the input parameters to study the impact of extreme values on the model. Since the population size in the model is limited, we tested the influence of the initial population size on the model results. Our results showed that the model could accurately describe the dynamics of the disease in the presence and absence of disease control. Although we developed the model for the spread of BVD, it may be adapted to similar diseases of cattle and swine.

Livestock Network Analysis for Rhodesiense Human African Trypanosomiasis Control in Uganda.

Background: Infected cattle sourced from districts with established foci for Trypanosoma brucei rhodesiense human African trypanosomiasis (rHAT) migrating to previously unaffected districts, have resulted in a significant expansion of the disease in Uganda. This study explores livestock movement data to describe cattle trade network topology and assess the effects of disease control interventions on the transmission of rHAT infectiousness.Methods: Network analysis was used to generate a cattle trade network with livestock data which was collected from cattle traders (n = 197) and validated using random graph methods. Additionally, the cattle trade network was combined with a susceptible, infected, recovered (SIR) compartmental model to simulate spread of rHAT (Ro 1.287), hence regarded as “slow” pathogen, and evaluate the effects of disease interventions.Results: The cattle trade network exhibited a low clustering coefficient (0.5) with most cattle markets being weakly connected and a few being highly connected. Also, analysis of the cattle movement data revealed a core group comprising of cattle markets from both eastern (rHAT endemic) and northwest regions (rHAT unaffected area). Presence of a core group may result in rHAT spread to unaffected districts and occurrence of super spreader cattle market or markets in case of an outbreak. The key cattle markets that may be targeted for routine rHAT surveillance and control included Namutumba, Soroti, and Molo, all of which were in southeast Uganda. Using effective trypanosomiasis such as integrated cattle injection with trypanocides and spraying can sufficiently slow the spread of rHAT in the network.Conclusion: Cattle trade network analysis indicated a pathway along which T. b. rhodesiense could spread northward from eastern Uganda. Targeted T. b. rhodesiense surveillance and control in eastern Uganda, through enhanced public–private partnerships, would serve to limit its spread.

Spatial and network analysis of U.S. livestock movements based on Interstate Certificates of Veterinary Inspection

Livestock movements are a common pathway for the spread infectious diseases in a population. An understanding of livestock movement patterns is needed to understand national transmission risks of highly infectious diseases during epidemics. Social Network Analysis (SNA) is an approach that helps to describe the relationships among individuals and the implications of those relationships. We used SNA to describe the contact structure of livestock movements throughout the contiguous U.S. from April 1st, 2015 to March 31st, 2016. We describe 4 network types: beef cattle, dairy cattle, swine, and small ruminant. Livestock movement data were sourced from Interstate Certificates of Veterinary Inspection (ICVI) while county-level farm demographic data were from the National Agricultural Statistics Service (NASS). In the described networks, nodes are represented by counties and arcs by shipments between nodes; the networks were weighted based on the number of shipments between nodes. For the analyses, movement data were aggregated at the county level and on an annual basis. Measures of centrality and cohesiveness were computed and identification of trade-communities in all networks was conducted. During the study period, a total of 219,042 movements were recorded and beef cattle movements accounted for 63 % of all movements. At least 70 % of U.S. counties were present in each of the networks, but the density of arcs was less than 2% in all networks. In the beef cattle network, counties with high out-degree were strongly correlated (0.8) with the number of beef cows per county while for the dairy cattle network a strong correlation (>0.86) was found with the number of dairy cattle per km2 at the county level. All networks were found to have between 4 and 6 large communities (50 counties or more per community), and were geographically clustered except for the communities in the small ruminant network. Outputs reported in these analyses can help to understand the structure of the contact networks for beef cattle, dairy cattle, swine, and small ruminants. They may also be used in conjunction with simulation modeling to evaluate spread of highly infectious disease such as foot-and-mouth disease at the national level and to evaluate the application of intervention strategies.

Infectious Bovine Rhinotracheitis Control Program in Slovakia.

As for other European countries, IBR is a significant cause of financial losses in cattle in Slovakia. The State Veterinary and Food Administration of the Slovak Republic prepared a voluntary IBR control program for cattle farms in 1995, which was implemented in 1996. In subsequent years, 48-119 farms/year enrolled in the voluntary IBR control program. Since the end of 2006, the IBR control program became compulsory by law for all cattle farms in Slovakia. Serology was used to identify infected animals using a conventional ELISA amongst non-vaccinated cattle and a gE specific ELISA in cattle vaccinated with marker vaccine. Eradication is based on culling when the serological prevalence of IBR in a herd is below 15%. When the prevalence is higher than 15%, the culling is combined with the application of a marker vaccine. A radical method where all animals are slaughtered is used with the agreement of the farmer when appropriate, especially for very small herds. Depending upon the selected eradication method, the antibody positive cattle can be gradually replaced in the herds to eliminate financial losses due to the disease. The movement of cattle is under strict control requiring a health certificate issued by the state veterinary authority and the movement must be recorded in the central livestock registry. The next step for herds is monitoring to achieve official IBR-free status. Based on the official figures from The State Veterinary and Food Administration, 60.2% herds were free of IBR in Slovakia in 2020.

An observational field study on the effects of changes in shadow contrasts and noise on cattle movement in a small abattoir

This observational field study examined the effect of changes in shadow contrasts on the floor and noise on balking behavior during handling. Seventy-four Bos taurus beef cattle were observed during handling at a small abattoir. Shadow contrast type (none, soft, sharp) was recorded during three stages of handling (unloading, lairage to single-file alley and into stun box). Cattle balking behavior (stop, put head down, back up) and aversive handling (electric prod, tail twist) were recorded for each shadow contrast type and the presence or absence of a noisy rendering truck. Sharp contrast shadows increased balking behavior compared to soft contrast shadows or none during unloading (X2 = 12.4, P < 0.001). The noisy truck increased balking behavior during handling from the lairage holding pens to the single-file alley (P < 0.001) and during movement into the stun box (P = 0.001). Sharp contrast shadows on the floor from lighting changes and noise from the truck increased balking behavior in cattle.

OPTIMIZATION OF HERD MOVEMENT AND COMPOSITION IN LIVESTOCK THROUGH ECONOMIC-MATHEMATICAL METHODS

The article deals with the issues of increasing meat and milk production in livestock as a result of economic-mathematical modeling and optimization of mathematical methods to determine the movement and composition of cattle on farms specializing in animal husbandry. In addition, a numerical economic-mathematical model of the problem was developed on the basis of the initial data of a specific diversified farm, solved on a computer using a standard program using a mathematical method, and as a result of solving the problem of optimizing the movement and composition of livestock for each age group. or sold, transferred from one group to another, the number of head of cattle at the end of the year, as well as the indicators of maximum milk and meat production were determined and thoroughly analyzed in economics.

Non-Invasive Cattle Body Temperature Measurement Using Infrared Thermography and Auxiliary Sensors.

To achieve a sensitive and accurate method in body temperature measurement of cattle, this study explores the uses of infrared thermography (IRT), an anemometer, and a humiture meter as a multiple sensors architecture. The influence of environmental factors on IRT, such as wind speed, ambient temperature, and humidity, was considered. The proposed signal processes removed the IRT frames affected by air flow, and also eliminated the IRT frames affected by random body movement of cattle using the frame difference method. In addition, the proposed calibration method reduced the impact of ambient temperature and humidity on IRT results, thereby increasing the accuracy of IRT temperature. The difference of mean value and standard deviation value between recorded rectal reference temperature and IRT temperature were 0.04 °C and 0.10 °C, respectively, and the proposed system substantially improved the measurement consistency of the IRT temperature and reference on cattle body temperature. Moreover, with a relatively small IRT image sensor, the combination of multiple sensors architecture and proper data processing still achieved good temperature accuracy. The result of the root-mean-square error (RMSE) was 0.74 °C, which is quite close to the accurate result of the IRT measurement.

Spatio‐temporal clustering and risk factor analysis of bovine theileriosis ( Theileria parva ) in Zimbabwe from 1995 to 2018

Bovine theileriosis (caused by Theileria parva) is the most important tick-borne transboundary animal disease endemic to Zimbabwe, yet its distribution dynamics data in the country remain scant and outdated. A retrospective study was conducted to determine high-risk areas of bovine theileriosis and associated risk factors in Zimbabwe. Records on bovine theileriosis spanning 23years (January 1995 to December 2018) were obtained from the Epidemiological Unit of the Division of Field Veterinary Services of Zimbabwe (DVSZ). Data were analysed using Studio R® version 11.0 for regression analysis and SatScan® version 9.4.6 for spatio-temporal clustering. Communal farmers (72%), adult cattle (29%), the year 2018 (60%) and the hot wet season (42%) had the highest proportion (p<.050) of bovine theileriosis cases recorded. Seven out of the country's ten provinces and 36 of its 59 districts were affected. Bovine theileriosis was observed to lose seasonality when cases rose exponentially in 2018. Five and four high-risk clusters of bovine theileriosis were detected using one-year and one-month time aggregate, respectively, all within the last eight years of the study (2011-2018). Two potential risk factors (province and farming system) were significantly (p<.050) associated with bovine theileriosis occurrence. Bovine theileriosis was found to be rampant and if left unchecked will spread and adversely affect the whole country. Improved theileriosis surveillance and control is warranted. Recommendations for control and prevention strategies revolve around better farmer awareness about the disease, correct and consistent use of acaricides, cattle movement control and disease surveillance among others.

Mycoplasma bovis outbreak in New Zealand cattle: An assessment of transmission trends using surveillance data.

Mycoplasma bovis most likely infected New Zealand cattle in the latter half of 2015. Infection was detected in mid-2017 after which control activities were implemented. An official eradication programme commenced in mid-2018, which is ongoing. We examined farm-level tracing and surveillance data to describe the outbreak, analyse transmission trends and make inference on progress towards eradication. Results indicate that cattle movements were the primary means of spread. Although case farms were distributed throughout both islands of New Zealand, most animal movements off infected farms did not result in newly infected farms, indicating Mycoplasma bovis is not highly transmissible between farms. To describe and analyse outbreak trends, we undertook a standard descriptive outbreak investigation, including construction of an epidemic curve and calculation of estimated dissemination ratios. We then employed three empirical models-a non-linear growth model, time series model and branching process model based on time-varying effective reproduction numbers-to further analyse transmission trends and provide short-term forecasts of farm-level incidence. Our analyses suggest that Mycoplasma bovis transmission in New Zealand has declined and progress towards eradication has been made. Few incident cases were forecast for the period between 8 September and 17 December 2019. To date, no case farms with an estimated infection date assigned to this period have been detected; however, case detection is ongoing, and these results need to be interpreted cautiously considering model validation and other important contextual information on performance of the eradication programme, such as the time between infection, detection and implementation of movement controls on case farms.

Multi-species temporal network of livestock movements for disease spread

IntroductionThe objective of this study is to show the importance of interspecies links and temporal network dynamics of a multi-species livestock movement network. Although both cattle and sheep networks have been previously studied, cattle-sheep multi-species networks have not generally been studied in-depth. The central question of this study is how the combination of cattle and sheep movements affects the potential for disease spread on the combined network.Materials and methodsOur analysis considers static and temporal representations of networks based on recorded animal movements. We computed network-based node importance measures of two single-species networks, and compared the top-ranked premises with the ones in the multi-species network. We propose the use of a measure based on contact chains calculated in a network weighted with transmission probabilities to assess the importance of premises in an outbreak. To ground our investigation in infectious disease epidemiology, we compared this suggested measure with the results of disease simulation models with asymmetric probabilities of transmission between species.ResultsOur analysis of the temporal networks shows that the premises which are likely to drive the epidemic in this multi-species network differ from the ones in both the cattle and the sheep networks. Although sheep movements are highly seasonal, the estimated size of an epidemic is significantly larger in the multi-species network than in the cattle network, independently of the period of the year. Finally, we demonstrate that a measure based on contact chains allow us to identify around 30% of the key farms in a simulated epidemic, ignoring markets, whilst static network measures identify less than 10% of these farms.ConclusionOur results ascertain the importance of combining species networks, as well as considering layers of temporal livestock movements in detail for the study of disease spread.

Modeling Intervention Scenarios During Potential Foot-and-Mouth Disease Outbreaks Within U.S. Beef Feedlots.

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock and has severely affected livestock industries during the past two decades in previously FMD-free countries. The disease was eliminated in North America in 1953 but remains a threat for re-introduction. Approximately 44% of the on-feed beef cattle in the U.S. are concentrated in feedlots <32,000 heads, but little information is available on dynamics of FMD in large feedlots. Therefore, there is a need to explore possible management and intervention strategies that might be implemented during potential FMD outbreaks on feedlots. We used a within home-pen stochastic susceptible-latent-infectious-recovered (SLIR) FMD dynamics model nested in a meta-population model of home-pens in a feedlot. The combinatory model was previously developed to simulate foot-and-mouth disease virus (FMDv) transmission within U.S. beef feedlots. We evaluated three intervention strategies initiated on the day of FMD detection: stopping movements of cattle between home-pens and hospital-pen(s) (NH), barrier depopulation combined with NH (NH-BD), and targeted depopulation of at-risk home-pens combined with NH (NH-TD). Depopulation rates investigated ranged from 500 to 4,000 cattle per day. We evaluated the projected effectiveness of interventions by comparing them with the no-intervention FMD dynamics in the feedlot. We modeled a small-size (4,000 cattle), medium-size (12,000 cattle), and large-size (24,000 cattle) feedlots. Implementation of NH delayed the outbreak progression, but it did not prevent infection of the entire feedlot. Implementation of NH-BD resulted in depopulation of 50% of cattle in small- and medium-size feedlots, and 25% in large-size feedlots, but the intervention prevented infection of the entire feedlot in 40% of simulated outbreaks in medium-size feedlots, and in 8% in large-size feedlots. Implementation of NH-TD resulted in depopulation of up to 50% of cattle in small-size feedlots, 75% in medium-size feedlots, and 25% in large-size feedlots, but rarely prevented infection of the entire feedlot. Number of hospital-pens in the feedlot was shown to weakly impact the success of NH-TD. Overall, the results suggest that stopping cattle movements between the home-pens and hospital-pens, without or with barrier or targeted cattle depopulation, would not be highly effective to interrupt FMDv transmission within a feedlot.

Development of Noncontact Body Temperature Monitoring and Prediction System for Livestock Cattle

Annually, numerous cattle die of various diseases, necessitating the need for effective cattle health management. To ensure cattle disease detection at an early stage and identify the health status of cattle, we collected the environment temperature, humidity, illuminance, and infrared images of cattle in an actual-life environment as input parameters to develop an artificial intelligence characterization module for measuring deep body temperature in a contactless manner. By analyzing the correlation of estimating deep body temperature at the horn, eyeball, and nose of cattle, the most effective way of estimating this temperature was found to be at the horn. The estimation accuracy was particularly high in the sitting state. Moreover, we proposed a noncontact measurement system that can approximately measure the moving distance of cattle and depict the cattle movement trajectory. The usability and reliability of the proposed systems were verified via an experiment using special feed. We used moving distance data as an additional input for the body temperature estimation system and found that rumen temperature can be accurately estimated. The body temperature estimated using the proposed system can be used to realize long-term remote monitoring of cattle health and early and timely abnormality detection.

A Static Video Summarization Approach for the Analysis of Cattle's Movement

A Static Video Summarization Approach for the Analysis of Cattle's Movement

Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil.

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.

“It’s just the luck of the draw”: Luck, good farming and the management of animal disease in Aotearoa New Zealand

The mobility of livestock in modern farming systems is connected with the geographical spread of animal disease. Government attempts to control this geography increasingly rely on practices of self-government that create new farming subjectivities to shape farming conduct. However, studies show that perceptions of luck are influential in shaping behaviour to environmental hazards, as are socio-cultural concepts of ‘good farming’ in which forms of cultural capital define appropriate conduct. This paper examines how luck is woven into farmers’ understandings of disease and the conduct of ‘good farming’ in relation to government attempts to restrict the movement of cattle. Drawing on 41 qualitative interviews with farmers in Aotearoa New Zealand, the paper examines understandings of good farming in relation to a metrological system to encourage fewer high-risk livestock movements. Data reveal that luck is an important resource in shaping farmers’ perceptions of animal disease, justifying their disease control behaviour; responses to practices of self-government; and allowing farmers to displace blame and rely on experts to manage animal disease. A focus on luck also highlights a range of competing versions of good farming and the importance of context when assessing the symbols of good farming. The failure to inscribe multiple forms of good farming within practices of animal disease self-government and narrowly associate good farming with disease freedom means they lack cultural relevance. In conclusion the paper considers the importance of luck for the concept of good farming and government approaches to managing the geography of animal disease.

Livestock Mobility Through Integrated Beef Production-Scapes Supports Rangeland Livestock Production and Conservation

Much of the world's rangelands contribute to food production through extensive grazing systems. In these systems, livestock producers, pastoralists, and ranchers move grazing animals to access variable feed and water resources to create value while supporting numerous other ecosystem services. Loss of mobility due to political, social, ecological, and economic factors is documented throughout the world and poses a substantial risk to rangeland livestock production and conservation of rangeland resources. The integration of production-scapes can facilitate livestock mobility through transportation and trade. This paper describes the beef cattle production system in California, where transporting and marketing animals integrate an extensive grazing system with intensive production systems, including feeding operations. Analysis of livestock inspection data quantifies the magnitude of livestock movements in the state and the scope of production-system integration. Over 500,000 head−47 percent of the state's calf crop—leave California rangelands and are moved to new pastures or feedyards seasonally over a 12 week period each year. Most ranchers in California, from small-scale producers (1 to 50 head) to larger producers (more than 5,000), participate in the integrated beef production system. Less than 1% of steers and heifers go from rangeland to meat processing. Like pastoralists, ranchers strategically move cattle around (and off) rangeland to optimize production within a variable climate. Ranchers indicate that their movements result from changes in forage quality and quantity and support their desire to manage for conservation objectives, including reducing fire fuels, controlling weeds, and managing for wildlife habitat. Inspection data, as well as direct observation, interviews, and surveys within the San Francisco Bay area, reveal the extent to which the region's ranchers rely on saleyards to facilitate the movement of cattle and integration of production systems. Saleyards and cattle buyers drive beef production efficiency by sorting, pricing, and moving cattle and matching them to feed resources in more intensive production systems. However, transactions lack traceability to inform policy and consumer choice. New data technologies like blockchain can provide traceability through integrated production-scapes and facilitate market development to support grazing landscapes and consumer choice.

The application of virtual fencing technology effectively herds cattle and sheep

Context Herding and mustering procedures during livestock management can be time-consuming, labour intensive, and costly. The ability to gather animals virtually is an enticing notion but technology to do this is not widely commercially available. Aims The eShepherd® virtual fencing system being developed for cattle may be able to remotely herd animals. This system operates via global positioning system, and requires animals to wear a neckband device. Animals are trained to associate an audio tone with an electrical pulse to avoid a virtual boundary. Methods Experiments were conducted with cattle using pre-commercial prototypes of the automated virtual fencing neckbands, and with sheep using manually operated dog training collars implementing the same virtual fencing algorithm to explore the potential of this technology for herding, and optimal fence designs for herding success. In the first experiment, five groups of 12 cattle were moved down a 344 m paddock using three different fence placement designs. Results The most successful design for cattle herding was a back fence that followed behind the animals to prevent them from turning back in the wrong direction. The fences were manually activated by personnel based on the cattle movement. The same type of fence design was manually applied to two groups of six sheep to successfully herd them down a 140 m paddock in the second experiment. Conclusions All herding was highly dependent on the animal’s own pace of movement as no signals were applied to ‘push’ the animals, the systems only prevented movement back in the wrong direction. The pre-commercial prototype of the automated eShepherd® device used is now obsolete and testing with updated versions would be needed to confirm its application for animal herding. Implications These preliminary trials indicate potential for virtual fencing technology to herd livestock, but technology improvements are required, and an automated device for sheep is not yet available.

Targeted Grazing of an Invasive Grass Improves Outcomes for Native Plant Communities and Wildlife Habitat

Rangelands provide ecosystem services that are economically and ecologically critical for humans. Globally, invasion of exotic grasses drives loss of biodiversity and resilience of rangelands. In South Texas, buffelgrass (Cenchrus ciliaris syn. Pennisetum ciliare [L.] Link), a C4 perennial grass, was brought from Africa for range improvement as early as the 1930s. Buffelgrass generally increases forage biomass for livestock yet reduces habitat suitability for wildlife. Interest in controlling buffelgrass has increased due to its negative impacts on iconic wildlife, such as whitetailed deer (Odocoileus virginianus, Zimmermann 1780) and northern bobwhite (Colinus virginianus, Linnaeus 1758). The objective of this study was to evaluate the effect of a targeted grazing strategy that used buffelgrass and plant community phenology as indicators to determine the timing of cattle movement. On two private ranches in different ecoregions, we tracked targeted grazing versus light grazing in native-dominated and buffelgrass-dominated plant communities across variable precipitation through five growing seasons. We measured the effects of grazing type, plant community type, and precipitation on buffelgrass cover, native plant species richness, foliar cover, and Shannon diversity. Targeted grazing had a strong impact on diversity, increasing 0.37 ± 0.07 from a mean of H = 1.29 under the targeted grazing management. Conversely, buffelgrass cover was negatively correlated with Shannon diversity, decreasing it by 0.075 ± 0.03 for every 10% increase in buffelgrass cover from a mean of H = 1.29. Despite a variability in precipitation across seasons and years (93−455 mm), targeted grazing improved species richness and cover of native plants throughout the study. Our findings suggest that targeted grazing shows promise as an adaptive grazing strategy that reduces the impact of buffelgrass across highly variable precipitation. In unpredictable environments, management techniques that improve the resilience of plant communities through preserving biodiversity are critical.

Haemoparasites infection in bullfighting cattle in southern of Thailand

Haemoparasites affect animal health and the production leading to economic losses and may have effects on human health. In Thailand, there are few reports of infections in the bullfighting cattle are for cultural fighting competitions. Therefore, this research aimed to investigate the distribution of haemoparasites infection in bullfighting cattle in order to control the transmission of disease to the local domestic cattle. A total of 1906 blood samples were collected from the bullfighting cattle from eight provinces in southern Thailand from 2017 to 2020. Those cattle showed the clinical signs of gasping, pale mucous membrane, haematuria, anorexia, sneezing and weakness. Micro-haematocrit centrifugation and thin blood smears with Giemsa’s staining were used. The results indicated 42.50% (810/1906) of cases positive for haemoparasites infection. The most commonly found was Theileria spp. (38.20%, 728/1906) followed by microfilaria of Setaria spp. (2.68%, 51/1906), Trypanosoma spp. (1.21%, 23/1906), Babesia spp. (0.94%, 18/1906) and Anaplasma spp. (0.10%, 2/1906). Out of 810 positive samples, there was co-infection between Theileria spp. and Setaria spp. (1.36%, 11/810), Theileria spp. and Babesia spp. (0.99%, 8/810), and Theileria spp., Trypanosoma spp. and Setaria spp. (0.37%, 3/810). The distribution of haemoparasites infection in eight raising areas ranged from 39.71 to 75%, with no significantly differences. From this result is was determined that haemoparasites were of generalised distribution in southern Thailand. Therefore, there should be strict surveillance and control of movement of cattle into the fighting arena. Moreover, vector control and blood checking before fighting should be promoted.

Analysis of the cattle trade network in the state of Mato Grosso, Brazil

We characterized the network of cattle movements in Mato Grosso, Brazil—a state responsible for a significant amount of Brazilian beef exports. In this analysis, we were particularly interested in the importance of slaughterhouses in the network of cattle movements, in the characteristics of the trade for different purposes (especially for reproduction, fattening, and slaughter), and about the importance of the main traders. We found that the median distance of all movements was 79.0 km, with an interquartile range between 37.2 and 163.2 km, which suggests a relatively short-range trade pattern; roughly 20% of the premises purchasing more animals were responsible for 95% of the animals purchased and 20% of the premises selling more animals were responsible for 86% of the animals sold, indicating the importance of the cattle trade hubs. Fitting the degree distribution using a power-law distribution, we obtained a scaling parameter of 2.59, indicating that the cattle movement network of Mato Grosso is less dense than other observed cattle movement networks. The networks for fattening, reproduction, and slaughtering only comprised 73%, 56%, and 25% of all nodes and 52%, 30%, and 17% of all edges, respectively; and slaughterhouses had the highest in-degrees and total degrees, followed by markets and farms, playing the role of main cattle trade hubs. Therefore, slaughterhouses are potentially useful as surveillance points to detect cases, and controlling important trader premises may optimize the use of resources for controlling diseases.