Temporal stability of swine movement networks in the U.S

As a consequence of multi-site pig production practiced in North America, frequent and widespread animal movements create extensive networks of interaction between farms. Social network analysis (SNA) has been used to understand disease transmission risks within these complex and dynamic production ecosystems and is particularly relevant for designing risk-based surveillance and control strategies targeting highly connected farms. However, inferences from SNA and the effectiveness of targeted strategies may be influenced by temporal changes in network structure. Since farm movements represent a temporally dynamic network, it is also unclear how many months of data are required to gain an accurate picture of an individual farm's connectivity pattern and the overall network structure. The extent to which shipments between two specific farms are repeated (i.e., "loyalty" of farm contacts) can influence the rate at which the structure of a network changes over time, which may influence disease dynamics. In this study, we aimed to describe temporal stability and loyalty patterns of pig movement networks in the U.S. swine industry. We analyzed a total of 282,807 animal movements among 2724 farms belonging to two production systems between 2014 and 2017. Loyalty trends were largely driven by contacts between sow farms and nurseries and between nurseries and finisher farms; mean loyalty (percent of contacts that were repeated at least once within a 52-week interval) of farm contacts was 51-60 % for farm contacts involving weaned pigs, and 12-22% for contacts involving feeder pigs. A cyclic pattern was observed for both weaned and feeder pig movements, with episodes of increased loyalty observed at intervals of 8 and 17-20 weeks, respectively. Network stability was achieved when six months of data were aggregated, and only small shifts in node-level and global network metrics were observed when adding more data. This stability is relevant for designing targeted surveillance programs for disease management, given that movements summarized over too short a period may lead to stochastic swings in network metrics. A temporal resolution of six months would be reliable for the identification of potential super-spreaders in a network for targeted intervention and disease control. The temporal stability observed in these networks suggests that identifying highly connected farms in retrospective network data (up to 24 months) is reliable for future planning, albeit with reduced effectiveness.

Identifying challenges to manage body weight variation in pig farms implementing all-in-all-out management practices and their possible implications for animal health: a case study

Background

Managing body weight (BW) variation is a challenge in farrow-to-finish farms implementing all-in/all-out (AIAO) production systems due to the lack of “off-site” facilities to segregate slow growing pigs (SGP). This case study investigated different approaches to managing BW variation in a farrow-to-finish commercial pig farm with a self-declared AIAO management and the possible implications for animal health.

Case presentation

A total of 1096 pigs (1047 pigs born within 1 week plus 49 pigs born 1 week later) were tracked until slaughter as they moved through the production stages. Piglets were individually tagged at birth and their location on the farm was recorded on a weekly basis. In total, 10.3% of pigs died during lactation. Four main cohorts of pigs were created at weaning and retrospectively identified: cohort 1 = pigs weaned at 21 days (4.5%); cohort 2 = pigs weaned at 28 days (81.0%), which was sub-divided at the end of the first nursery stage into sub-cohort 2a = pigs split at 3 weeks post-weaning (29.7%); sub-cohort 2b = pigs split at 3 weeks post-weaning from cohort 2a and split again 5 weeks post-weaning (35.5%) and sub-cohort 2c = remaining smaller size pigs from cohort 2b (10.9%); cohort 3 = pigs weaned at 35 days (2.7%) and cohort 4 = pigs weaned at 49 days (1.5%) that were later mixed with SPG, delayed pigs from other cohorts and sick/injured pigs that recovered. Four strategies to manage BW variation were identified: i) earlier weaning (cohort 1); ii) delayed weaning of SGP (cohort 3 and 4); iii) re-grading pens by BW (sub-cohorts 2a, 2b and 2c) and, iv) delayed movement of SGP to the next production stage (several pigs from all cohorts). A higher percentage of delayed pigs presented pericarditis, pleurisy and enzootic pneumonia like lesions at slaughter compared with pigs under other strategies.

Conclusion

A variety of management practices were implemented to minimise BW variation during the production cycle. However, several cohorts of pigs were created disrupting AIAO management. Earlier weaning should only be practiced under specific circumstances where optimal animal health and welfare are guaranteed. Delayed weaning of SGP and delaying pigs to move to the next production stage could negatively affect animal health and should be avoided.

Analysis of domestic animal movements in Colombia (2006-2014) and their possible influence on the bovine brucellosis spread

Bovine brucellosis is a zoonotic disease that causes great economic losses. The disease is endemic in Colombia and animal movements from infected herds carry a risk of introduction to other herds. With the objective of analyzing the animal movements and determining their relationship with bovine brucellosis, we performed a descriptive analysis of the space-time movement of livestock in Colombia between 2006 and 2014. Multiple linear regression models (MLR) were employed to determine the relationship between brucellosis status and animal movements at the province level. The prevalence of bovine brucellosis in cattle was the dependent variable, and a total of 14 independent variables related to location, year, census, and animal movements were included. The prevalence of bovine brucellosis was significantly affected by the province (F = 3.42; P < 0.001), the year (F = 9.03; P < 0.001), and bovine (F = 5.45; P = 0.02) and equine movements (F = 3.8; P = 0.053). Fewer cattle and more horses entered provinces with high prevalence than those with low prevalence, indicating the possible relationship between the animal movements and the brucellosis infection in the country.

Combining Salmonella Dublin genome information and contact-tracing to substantiate a new approach for improved detection of infectious transmission routes in cattle populations

This study presents a new method for detection of between-herd livestock movements to facilitate disease tracing and more accurately describe network behaviour of relevance for spread of infectious diseases, including within-livestock business risk-carrying contacts that are not necessarily recorded anywhere. The study introduces and substantiates the concept of grouping livestock herds into business-units based on ownership and location in the tracing analysis of animal movement-based contact networks. To test the utility of this approach, whole core genome sequencing of 196 Salmonella Dublin isolates stored from previous surveillance and project activities was combined with information on cattle movements recorded in the Danish Cattle Database between 1997 and 2017. The aim was to investigate alternative explanations for S. Dublin circulation in groups of herds connected by ownership, but without complete records of livestock movements. The EpiContactTrace R-package was used to trace the contact networks between businesses and compare the network characteristics of businesses sharing strains of S. Dublin with different levels of genetic relatedness. The ownership-only definition proved to be an unreliable grouping approach for large businesses, which could have internal distances larger than 250 km and therefore do not represent useful epidemiological units. Therefore, the grouping was refined using spatial analysis. More than 90% of final business units formed were composed of one single cattle property, whereas multi-property businesses could reach up to eight properties in a given year, with up to 15 cattle herds having been part of the same business through the study period. Results showed markedly higher probabilities of introduction of infectious animals between proposed businesses from which the same clone of S. Dublin had been isolated, when compared to businesses with non-related strains, thus substantiating the business-unit as an important epidemiological feature to consider in contact network analysis and tracing of infection routes. However, this approach may overestimate real-life contacts between cattle properties and putatively overestimate the degree of risk-contacts within each business, since it is based solely on information about property ownership and location. This does not consider administrative and individual farmers behaviours that essentially keep two properties separated. Despite this, we conclude that defining epidemiological units based on businesses is a promising approach for future disease tracing tasks.

Herd level estimation of probability of disease freedom applied on the Norwegian control program for bovine respiratory syncytial virus and bovine coronavirus

A national control program against bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCV) was launched in Norway in 2016. A key strategy in the program is to test for presence of antibodies and protect test-negative herds from infection. Because these viruses are endemic, the rate of re-introduction can be high, and a disease-free status will become more uncertain as time from testing elapses. The aim of this study was to estimate the probability of freedom (PostPFree) from BRSV and BCV antibodies over time by use of bulk tank milk (BTM) antibody-testing, geographic information and animal movement data, and to validate the herd-level estimates against subsequent BTM testing.

BTM samples were collected from 1148 study herds in West Norway in 2013 and 2016, and these were analyzed for BRSV and BCV antibodies. PostPFree was calculated for herds that were negative in 2013/2014, and updated periodically with new probabilities every three months. Input variables were test sensitivity, the probability of introduction through animal purchase and local transmission. Probability of introduction through animal purchase was calculated by using real animal movement data and herd prevalence in the region of the source herd. The PostPFree from the final three months in 2015 was compared to BTM test results from March 2016 using a Wilcoxon Rank Sum Test.

The probability of freedom was generally high for test-negative herds immediately after testing, reflecting the high sensitivity of the tests. It did however, decrease with time since testing, and was greatly affected by purchase of livestock. When comparing the median PostPFree for the final three months to the test results in 2016, it was significantly lower (p < 0.01) for test positive herds. Furthermore, there was a large difference in the proportion of test positive herds between the first and fourth quartile of PostPFree. The results show that PostPFree provides a better estimate of herd-level BTM status for both BRSV and BCV than what can be achieved by relying solely on the previous test-result.

Review of the foot and mouth disease situation in North Africa and the risk of introducing the disease into Europe

Foot and mouth disease (FMD) is a highly contagious disease of cloven-hoofed animals, including cattle, pigs, sheep, goats, and certain wildlife species. The disease can cause massive economic losses when introduced into countries that were free from the infection, generating negative effects due to reduced animal productivity and restrictions on international livestock trade. Following 15 years of FMD absence, Tunisia and Algeria experienced an incursion of the disease in 2014. The epidemiological situation and disease control measures in operation for FMD in the North African region are not homogeneous. The FMD virus detected in Tunisia and Algeria during the epidemic in 2014 showed 99% identity with a strain isolated in Libya in 2013. Morocco was not affected by the 2014 epidemic but it started a preventive vaccination campaign for cattle in August of that year. The relatively short distance between the North African continent and southern Europe may facilitate the introduction of pathogens, including FMD virus. The history of infectious diseases demonstrates that the Mediterranean Sea is not a sufficient barrier to viral infections. Considering the geography and the FMD situation in North African countries, strong and coordinated intervention strategies are required, including economic, political and disease control aspects, to prevent the spread of FMD to other countries in North Africa or to other regions, e.g. southern Europe. Regional platforms such as the Mediterranean Animal Health Network (REMESA) could play a crucial role in coordinating and managing animal health crises, such as the 2014 FMD epidemic.

Noninvasive genetic sampling reveals intrasex territoriality in wolverines

Due to its conspicuous manifestations and its capacity to shape the configuration and dynamics of wild populations, territorial behavior has long intrigued ecologists. Territoriality and other animal interactions in situ have traditionally been studied via direct observations and telemetry. Here, we explore whether noninvasive genetic sampling, which is increasingly supplementing traditional field methods in ecological research, can reveal territorial behavior in an elusive carnivore, the wolverine (Gulo gulo). Using the locations of genotyped wolverine scat samples collected annually over a period of 12 years in central Norway, we test three predictions: (1) male home ranges constructed from noninvasive genetic sampling data are larger than those of females, (2) individuals avoid areas used by other conspecifics of the same sex (intrasexual territoriality), and (3) avoidance of same‐sex territories diminishes or disappears after the territory owner's death. Each of these predictions is substantiated by our results: sex‐specific differences in home range size and intrasexual territoriality in wolverine are patently reflected in the spatial and temporal configuration of noninvasively collected genetic samples. Our study confirms that wildlife monitoring programs can utilize the spatial information in noninvasive genetic sampling data to detect and quantify home ranges and social organization.

Modelling foraging movements of diving predators: a theoretical study exploring the effect of heterogeneous landscapes on foraging efficiency

Foraging in the marine environment presents particular challenges for air-breathing predators. Information about prey capture rates, the strategies that diving predators use to maximise prey encounter rates and foraging success are still largely unknown and difficult to observe. As well, with the growing awareness of potential climate change impacts and the increasing interest in the development of renewable sources it is unknown how the foraging activity of diving predators such as seabirds will respond to both the presence of underwater structures and the potential corresponding changes in prey distributions. Motivated by this issue we developed a theoretical model to gain general understanding of how the foraging efficiency of diving predators may vary according to landscape structure and foraging strategy. Our theoretical model highlights that animal movements, intervals between prey capture and foraging efficiency are likely to critically depend on the distribution of the prey resource and the size and distribution of introduced underwater structures. For multiple prey loaders, changes in prey distribution affected the searching time necessary to catch a set amount of prey which in turn affected the foraging efficiency. The spatial aggregation of prey around small devices (∼ 9 × 9 m) created a valuable habitat for a successful foraging activity resulting in shorter intervals between prey captures and higher foraging efficiency. The presence of large devices (∼ 24 × 24 m) however represented an obstacle for predator movement, thus increasing the intervals between prey captures. In contrast, for single prey loaders the introduction of spatial aggregation of the resources did not represent an advantage suggesting that their foraging efficiency is more strongly affected by other factors such as the timing to find the first prey item which was found to occur faster in the presence of large devices. The development of this theoretical model represents a useful starting point to understand the energetic reasons for a range of potential predator responses to spatial heterogeneity and environmental uncertainties in terms of search behaviour and predator-prey interactions. We highlight future directions that integrated empirical and modelling studies should take to improve our ability to predict how diving predators will be impacted by the deployment of manmade structures in the marine environment.