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The transport of weaned calves from cow-calf producers to fatteners is a general concern for the young bull industry due to its documented negative impact on the welfare, health and performance of the animals. These transfers are often managed by intermediaries who transport weaned calves to sorting centres, where they are grouped into batches before being sent to fattening units. In this study, we present an algorithm to limiting these transfer distances by appropriately selecting the sorting centre through which they must go. We tested the effectiveness of this algorithm on historical data from a French beef producer organization managing 136,892 transfers using 13 sorting centres. The results show a decrease in the transfer distances compared to the historical record, especially for the calves travelling over long distances (- 76 km, i.e. 18% on average for the 33% longest transfers). Moreover, the distribution of calves between the sorting centres proposed by the algorithm reveals differences in their efficiency in minimizing transfer distances. In addition to its usefulness as a management tool for the daily transport of cattle, this algorithm provides prospects for improving the management of the sorting centres themselves.

A good knowledge of the specificities of the animal trade network is highly valuable to better control pathogen spread on a large regional to transnational scale. Because of their temporal dynamical nature, studying multi-annual datasets is particularly needed to investigate whether structural patterns are stable over the years. In this study, we analysed the French cattle movement network from 2005 to 2009 for different spatial granularities and temporal windows, with the three-fold objective of exploring temporal variations of the main network characteristics, computing proxies for pathogen spread on this network, which accounts for its time-varying properties and identifying specificities related to the main types of animals and farms (dairy versus beef). Network properties did not qualitatively vary among different temporal and spatial granularities. About 40% of the holdings and 80% of the communes were directly interconnected. The width of the aggregation time window barely impacted normalised distributions of indicators. A period of 8-16 weeks would suffice for robust estimation of their main trends, whereas longer periods would provide more details on tails. The dynamic nature of the network could be seen through the small overlap between consecutive networks with 65% of common active nodes for only 3% of common links over 2005-2009. To control pathogen spread on such a network, by reducing the largest strongly connected component by more than 80%, movements should be prevented from 1 to 5% of the holdings with the highest centrality in the previous year network. The analysis of breed-wise and herd-wise subnetworks, dairy, beef and mixed, reveals similar trends in temporal variation of average indicators and their distributions. The link-based backbones of beef subnetworks seem to be more stable over time than those of other subnetworks. At a regional scale, node reachability accounting for time-respecting paths, as proxy of epidemic burden, is greater for a dairy region than for a beef region. This highlights the importance of considering local specificities and temporal dynamics of animal trade networks when evaluating control measures of pathogen spread., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Bluetongue (BT) can cause severe livestock losses and large direct and indirect costs for farmers. To propose targeted control strategies as alternative to massive vaccination, there is a need to better understand how BT virus spread in space and time according to local characteristics of host and vector populations. Our objective was to assess, using a modelling approach, how spatiotemporal heterogeneities in abundance and distribution of hosts and vectors impact the occurrence and amplitude of local and regional BT epidemics. We built a reaction-diffusion model accounting for the seasonality in vector abundance and the active dispersal of vectors. Because of the scale chosen, and movement restrictions imposed during epidemics, host movements and wind-induced passive vector movements were neglected. Four levels of complexity were addressed using a theoretical approach, from a homogeneous to a heterogeneous environment in abundance and distribution of hosts and vectors. These scenarios were illustrated using data on abundance and distribution of hosts and vectors in a real geographical area. We have shown that local epidemics can occur earlier and be larger in scale far from the primary case rather than close to it. Moreover, spatial heterogeneities in hosts and vectors delay the epidemic peak and decrease the infection prevalence. The results obtained on a real area confirmed those obtained on a theoretical domain. Although developed to represent BTV spatiotemporal spread, our model can be used to study other vector-borne diseases of animals with a local to regional spread by vector diffusion.

Beef cow-calf farming systems are assumed to be resilient to biological disturbances that induce variations in herd demography; however, this hypothesis has not been fully investigated to date. Modeling is an interesting approach to study farming system resilience and to evaluate the impact of biological disturbances, taking into account interactions between system components, including biological variability and management practices. Our objective was to evaluate the resilience of beef cow-calf farming systems to variations in fertility and mortality using a modeling approach. We studied the direct effect of variations in demographic parameters on production objectives without explicitly representing the causes of the variations. We developed a stochastic model to represent the population dynamics of a beef cow-calf herd with breeding by natural service and biological processes occurring at the animal level. The model was validated by comparing observed and simulated distributions of the calving-to-calving interval, which were found to be consistent. Resistance was evaluated by the proportion of simulations where the objective in terms of number of weaned calves is reached even when there is a disturbance that persists for 10 yr. Reversibility was evaluated by the time needed to return to the predisturbance production level. Beef cow-calf farming systems did not appear to be resistant to variations in mortality and infertility rates except when increases in the infertility rates were low (0.02 for cows and 0.03 for heifers). Critical situations, consequently, may emerge with regard to farm production if management practices are not adapted. Reversibility was observed for disturbances that persist for up to 5 yr. However, the system needed 2 to 3 yr to recover its predisturbance production level and up to 4 yr after an increase in cow infertility of 0.12.

Q fever, a worldwide zoonotic disease caused by Coxiella burnetii, is a looming concern for livestock and public health. Epidemiological features of inter-herd transmission of C. burnetii in cattle herds by wind and trade of cows are poorly understood. We present a novel dynamic spatial model describing the inter-herd regional spread of C. burnetii in dairy cattle herds, quantifying the ability of airborne transmission and animal trade in C. burnetii propagation in an enzootic region. Among all the new herd infections, 92% were attributed to airborne transmission and the rest to cattle trade. Infections acquired following airborne transmission were shown to cause relatively small and ephemeral intra-herd outbreaks. On the contrary, disease-free herds purchasing an infectious cow experienced significantly higher intra-herd prevalence. The results also indicated that, for short duration, both transmission routes were independent from each other without any synergistic effect. The model outputs applied to the Finistère department in western France showed satisfactory sensitivity (0.71) and specificity (0.80) in predicting herd infection statuses at the end of one year in a neighbourhood of 3 km around expected incident herds, when compared with data. The model developed here thus provides important insights into the spread of C. burnetii between dairy cattle herds and paves the way for implementation and assessment of control strategies.

Abstract: The ever increasing demand for animal products in tropical environments requires urgent improvements in herd productivity. Animal production in the tropics is often limited by resource availability. In this context, the effects of potential management strategies are difficult to test experimentally, and a modelling approach can therefore be useful. Modelling can also be used to evaluate the sensitivity of the dynamics of cattle herds to such management strategies. Here, I use a deterministic matrix model based on methods widely used in ecology to represent the reproductive cycle of cattle in an extensive production system with minimal management. Seasonal variations in demography and management are described on a monthly time scale. Cows are grouped into classes according to their reproductive state and their body condition, a field measure of phenotypic quality, which is related to performance. Improved feeding conditions are assumed to result in an increase in the body condition score of the supplemented cows, so the feeding strategy is represented by variations in the ratio of fat/thin reproductive cows in the herd. I show that the population dynamics of the herds is sensitive to a change in this ratio. When the proportion of fat cows in late gestation increases, milk production increases, but the numerical productivity of the herd slightly declines. An increase in the proportion of fat non-pregnant cows gives rise to an increase in the numerical productivity, and an increase in milk production, although the effect varies strongly among seasons. The model predicts that an increase in cows body condition will be most effective in the late dry season. [Copyright &y& Elsevier]