Imke Traulsen

Static network analysis of a pork supply chain in Northern Germany—Characterisation of the potential spread of infectious diseases via animal movements

Transport of live animals is a major risk factor in the spread of infectious diseases between holdings. The present study analysed the pork supply chain of a producer community in Northern Germany. The structure of trade networks can be characterised by carrying out a network analysis. To identify holdings with a central position in this directed network of pig production, several parameters describing these properties were measured (in-degree, out-degree, ingoing and outgoing infection chain, betweenness centrality and ingoing and outgoing closeness centrality). To obtain the importance of the different holding types (multiplier, farrowing farms, finishing farms and farrow-to-finishing farms) within the pyramidal structure of the pork supply chain, centrality parameters were calculated for the entire network as well as for the individual holding types. Using these centrality parameters, two types of holdings could be identified. In the network studied, finishing and farrow-to-finishing farms were more likely to be infected due to the high number of ingoing trade contacts. Due to the high number of outgoing trade contacts multipliers and farrowing farms had an increased risk to spread a disease to other holdings. However, the results of the centrality parameters degree and infection chain were not always consistent, such that the indirect trade contacts should be taken into consideration to understand the real importance of a holding in spreading or contracting an infection. Furthermore, all calculated parameters showed a highly right-skewed distribution. Networks with such a degree distribution are considered to be highly resistant concerning the random removal of nodes. But by strategic removal of the most central holdings, e.g. by trade restrictions or selective vaccination or culling, the network structure can be changed efficiently and thus decompose into fragments. Such a fragmentation of the trade networks is of particular importance from an epidemiological perspective.

Environmental Impact Assessment--methodology with special emphasis on European pork production.

One of the most discussed topics worldwide is climate change, upon which livestock production is known to have a great environmental impact. There are different methods to measure these environmental impacts, some of which are mentioned in this review. It especially focuses on the method of Life Cycle Assessment (LCA), because it is widely used, of high relevance and good quality. This review highlights a sample of the few published European LCA studies on pork production. These assessments result in an average global warming potential of 3.6 kg CO(2)- eq per kg pork, ranging from 2.6 to 6.3 kg CO(2)- eq per kg pork. Additionally, it illustrates the main limitations of the methodology itself (e.g. data intensiveness, different allocation techniques) and its application in pork production (e.g. limited data availability, use of multiple functional units, varying system boundaries). The missing comparability of various studies arising from a vague standard still represents the main problem in LCA. Therefore, a new standardisation and the development of a more exhaustive database would generate a future trend.

Risk factors for Salmonella infection in fattening pigs - an evaluation of blood and meat juice samples.

The main objective of this study was to analyse potential herd‐level factors associated with the detection of Salmonella antibodies in fattening pigs. Two independent datasets, consisting of blood and meat juice samples respectively, were used. Additional information about husbandry, management and hygiene conditions was collected by questionnaire for both datasets. The serological analysis showed that 13.8% of the blood samples and 15.7% of the meat juice samples had to be classified as Salmonella‐positive. Logistic‐regression models were used to assess statistically significant risk factors associated with a positive sample result. The results of the statistical blood sample analysis showed that the application of antibiotics increased the odds ratio (OR) by a factor of 5.21 (P < 0.001) compared to untreated pigs. A fully slatted floor decreased the prevalence of Salmonella as well as the use of protective clothing or the cleaning of the feed tube (ORs 0.35–0.54, P < 0.001). It was shown that a distance of less than 2 km to other swine herds increased the chance of a positive Salmonella result (OR = 3.76, P < 0.001). The statistical analysis of the meat juice samples revealed the importance of feed aspects. The chance of obtaining a positive meat juice sample increased by a factor of 3.52 (P < 0.001) by using granulated feed instead of flour. It also became clear that liquid feeding should be preferred to dry feeding (OR = 0.33, P < 0.001). A comparison of the blood sample analysis to the meat juice model revealed that the latter was less powerful because data structure was less detailed. The expansion of data acquisition might solve these problems and improve the suitability of QS monitoring data for risk factor analyses.

Characterization of Contact Structures for the Spread of Infectious Diseases in a Pork Supply Chain in Northern Germany by Dynamic Network Analysis of Yearly and Monthly Networks

A major risk factor in the spread of diseases between holdings is the transport of live animals. This study analysed the animal movements of the pork supply chain of a producer group in Northern Germany. The parameters in-degree and out-degree, ingoing and outgoing infection chain, betweenness and ingoing and outgoing closeness were measured using dynamic network analysis to identify holdings with central positions in the network and to characterize the overall network topology. The potential maximum epidemic size was also estimated. All parameters were calculated for three time periods: the 3-yearly network, the yearly and the monthly networks. The yearly and the monthly networks were more fragmented than the 3-yearly network. On average, one-third of the holdings were isolated in the yearly networks and almost three quarters in the monthly networks. This represented an immense reduction in the number of holdings participating in the trade of the monthly networks. The overall network topology showed right-skewed distributions for all calculated centrality parameters indicating that network resilience was high concerning the random removal of holdings. However, for a targeted removal of holdings according to their centrality, a rapid fragmentation of the trade network could be expected. Furthermore, to capture the real importance of holdings for disease transmission, indirect trade contacts (infection chain) should be considered. In contrast to the parameters regarding direct trade contacts (degree), the infection chain parameter did not underestimate the potential risk of disease transmission. This became more obvious, the longer the observed time period was. For all three time periods, the results for the estimation of the potential maximum epidemic size illustrated that the outgoing infection chain should be chosen. It considers the chronological order and the directed nature of the contacts and has no restrictions such as the strongly connected components of a cyclic network.

Efficient interruption of infection chains by targeted removal of central holdings in an animal trade network

Centrality parameters in animal trade networks typically have right-skewed distributions, implying that these networks are highly resistant against the random removal of holdings, but vulnerable to the targeted removal of the most central holdings. In the present study, we analysed the structural changes of an animal trade network topology based on the targeted removal of holdings using specific centrality parameters in comparison to the random removal of holdings. Three different time periods were analysed: the three-year network, the yearly and the monthly networks. The aim of this study was to identify appropriate measures for the targeted removal, which lead to a rapid fragmentation of the network. Furthermore, the optimal combination of the removal of three holdings regardless of their centrality was identified. The results showed that centrality parameters based on ingoing trade contacts, e.g. in-degree, ingoing infection chain and ingoing closeness, were not suitable for a rapid fragmentation in all three time periods. More efficient was the removal based on parameters considering the outgoing trade contacts. In all networks, a maximum percentage of 7.0% (on average 5.2%) of the holdings had to be removed to reduce the size of the largest component by more than 75%. The smallest difference from the optimal combination for all three time periods was obtained by the removal based on out-degree with on average 1.4% removed holdings, followed by outgoing infection chain and outgoing closeness. The targeted removal using the betweenness centrality differed the most from the optimal combination in comparison to the other parameters which consider the outgoing trade contacts. Due to the pyramidal structure and the directed nature of the pork supply chain the most efficient interruption of the infection chain for all three time periods was obtained by using the targeted removal based on out-degree.

Salmonella control measures with special focus on vaccination and logistic slaughter procedures.

This study focussed on the effectiveness of Salmonella control measures to decrease Salmonella prevalence at slaughter. Considered measures were the control of hygiene and husbandry management as well as vaccination and logistic slaughter procedures. Results emphasized the capabilities of the farrowing stage to influence slaughter pig prevalence. Limited Salmonella entry by the implementation of hygiene control measures at farrowing farms obtained a significant decrease in prevalence after lairage at slaughterhouse. In contrast, hygiene control measures at finishing stage were less effective. Husbandry control measures, preventing physical contacts between pigs, were proved to decrease slaughter pig prevalence whether they were implemented at farrowing or finishing stage. Furthermore, the vaccination of sows and piglets was an appropriate control measure to decrease slaughter pig prevalence, if a large part of farms established this control measure. Simultaneous implementation of control measures showed that vaccination and especially hygiene measures are mutually supportive. Concerning logistic slaughter procedures it became obvious that with decreasing prevalence, infections at transport and lairage become more and more important. The herd status separation significantly decreased the percentage of infected pigs that became infected at lairage.

Consideration of different outbreak conditions in the evaluation of preventive culling and emergency vaccination to control foot and mouth disease epidemics

In recent foot and mouth disease outbreaks, many healthy animals have been culled to prevent disease transmission. Emergency vaccination is discussed as an alternative to culling of unaffected animals. A spatial and temporal Monte-Carlo simulation model was used to compare preventive culling and emergency vaccination. Different outbreaks are described using additional influence factors such as airborne spread, farm density, type of index-case farm and delay until establishment of the control strategies. The fewest farms were infected establishing a combined strategy including a 1 km preventive culling and 1-10 km emergency vaccination zone around each outbreak farm. Taking the number of culled and vaccinated farms into account, vaccination around the first diagnosed farm combined with the baseline strategy (culling of outbreak farms, protection and surveillance zone, contact tracing) is to be preferred. In the present study, emergency vaccination was an effective control strategy especially in densely populated regions.

Implementation of multivariate cumulative sum control charts in mastitis and lameness monitoring.

This study analyzed the methodology and applicability of multivariate cumulative sum (MCUSUM) charts for early mastitis and lameness detection. Data used were recorded on the Karkendamm dairy research farm, Germany, between August 2008 and December 2010. Data of 328 and 315 cows in their first 200 d in milk were analyzed for mastitis and lameness detection, respectively. Mastitis as well as lameness was specified according to veterinary treatments. Both diseases were defined as disease blocks. Different disease definitions for mastitis and lameness (2 for mastitis and 3 for lameness) varied solely in the sequence length of the blocks. Only the days before the treatment were included in the disease blocks. Milk electrical conductivity, milk yield, and feeding patterns (feed intake, number of trough visits, and feeding time) were used for the recognition of mastitis. Pedometer activity and feeding patterns were used for lameness detection. To exclude biological trends and obtain independent observations, the values of each input variable were either preprocessed by wavelet filters or a multivariate vector autoregressive model. The residuals generated between the observed and filtered or observed and forecast values, respectively, were then transferred to a classic or self-starting MCUSUM chart. The combination of the 2 preprocessing methods with each of the 2 MCUSUM sum charts resulted in 4 combined monitoring systems. For mastitis as well as lameness detection requiring a block sensitivity of at least 70%, all 4 of the combined monitoring systems used revealed similar results within each of the disease definitions. Specificities of 73 to 80% and error rates of 99.6% were achieved for mastitis. The results for lameness showed that the definitions used obtained specificities of up to 81% and error rates of 99.1%. The results indicate that the monitoring systems with these study characteristics have appealing features for mastitis and lameness detection. However, they are not yet directly applicable for practical implementations.

Assessing individual sow risk factors for coliform mastitis: a case-control study.

In order to investigate sow-specific risk factors associated with coliform mastitis, a case-control study was performed over the course of 28 months. Data of three farms were collected under production conditions. Sows suffering from coliform mastitis after farrowing served as cases, and healthy half- or full-sib sows from the same farm served as controls. Individual sow characteristics and the seasonal influence were analysed by conditional logistic regression. The final multivariate model identified four risk factors: the risk of suffering from coliform mastitis increased with a higher number of piglets born alive and stillborn piglets. Gilts had an increased risk for the disease, and birth intervention was also associated with a higher prevalence of mastitis. Birth induction and season had no significant influence on the occurrence of coliform mastitis. The time during and soon after farrowing is a very sensitive period in pig production demanding great attention by the farmer. With respect to the economic losses, monitoring of potentially endangered sows as well as detailed documentation and selection of disease cases are of particular importance when coping with coliform mastitis.

Epidemic spreading in an animal trade network – comparison of distance-based and network-based control measures

This study considered a simple SIR model for the spread of epidemics amongst holdings of a producer community in Northern Germany, based on the directed network of animal movements. The aim of this study was to evaluate the efficiency of different control measures to reduce the epidemic size substantially. The currently applied control measures based on the distance to an infected holding were compared with the control measures based on the specific network-based centrality parameters. We found that network-based measures led to a more efficient control of epidemics with a much smaller number of removed holdings. To assess the impact of different holding types, the analysed control measures were implemented by both including and excluding these holding types. The comparison revealed a crucial role of multipliers in the spread of an epidemic. The network-based control measures depending on the removal by out-degree, outgoing infection chain, betweenness centrality and outgoing closeness centrality showed the best results: In the three-year network, on average, 2.75, 4.15, 3.73 and 3.43 times more holdings had to be removed by the control measures based on the 1, 3, 5 and 10 km radius to reduce the epidemic to the same size compared with the network-based control measures. In an area with a higher holding density, the improvement of the network-based control measures may become even more obvious. The removal of holdings based on the above-mentioned centrality parameters did thus not only rapidly decompose the network into fragments, but also reduced the epidemic size most efficiently.