Social network analysis reveals the failure of between-farm movement restrictions to reduce Salmonella transmission

An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella (S.) Dublin, which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-year period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for non-infected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and post-movement measures within a 1-mo time-window may help reduce S. Dublin spread.

Supply chain management in times of crisis: a systematic review

Complexities of crises force supply chains managers to formulate crisis-induced strategies, which contrast with the conventional strategies that give precedence to competitive priorities. Recent crises, such as the coronavirus outbreaks, large-scale product recalls, and financial crises, underscore the increasing regularity and severity of crises with imperatives for introspective and retrospective socio-economic insights on the contexts, priorities, and themes of supply chain management in times of crisis. The purpose of this article is to review the literature on supply chain management in times of crisis, systematically coalescing the related body of scholarly work; outlining current methods applied by researchers; capturing strategic priorities and themes of complexities in research studies; and highlighting potentials for future studies. Using a systematic review of 250 journal articles published between 1996 and 2021, the review finds four dimensions for restorative priorities that reflect operations strategy during crisis: (i) critical supplies with essential services, (ii) timely response with recovery, (iii) safety with security, and (iv) traceability with transparency. The review also finds that operational complexities during crises originate from network configurations and business cycle complexities, optimal selections and provisioning system complexes, and complex learning processes and demand predictions. Insights from the review aid in the proposal of build-to-cycle, organic capabilities, and operational mindfulness framings for supply chain management in times of crisis. The article concludes by recommending future research studies on supply chain upgrades, diagnosis, solidarity, mapping, temporariness, and thresholds, as well as optimal selection problems on linking crisis systems investments with liabilities and on linking crisis network allotments with cross-functionalities.

Identification of potential vulnerable points and paths of contamination in the Dutch broiler meat trade network

The poultry meat supply chain is complex and therefore vulnerable to many potential contaminations that may occur. To ensure a safe product for the consumer, an efficient traceability system is required that enables a quick and efficient identification of the potential sources of contamination and proper implementation of mitigation actions. In this study, we explored the use of graph theory to construct a food supply chain network for the broiler meat supply chain in the Netherlands and tested it as a traceability system. To build the graph, we first identified the main actors in the supply chain such as broiler breeder farms, broiler farms, slaughterhouses, processors, and retailers. The capacity data of each supply chain actor, represented by its production or trade volumes, were gathered from various sources. The trade relationships between the supply chain actors were collected and the missing relationships were estimated using the gravity model. Once the network was modeled, we computed degree centrality and betweenness centrality to identify critical nodes in the network. In addition, we computed trade density to get insight into the complexity of sub-networks. We identified the critical nodes at each stage of the Dutch broiler meat supply chain and verified our results with a domain expert of the Dutch poultry industry and literature. The results showed that processors with own slaughtering facility were the most critical points in the broiler meat supply chain.

A systematic review of financial and economic assessments of bovine viral diarrhea virus (BVDV) prevention and mitigation activities worldwide

Infection with bovine viral diarrhea virus (BVDV) results in major economic losses either directly through decreased productive performance in cattle herds or indirectly, such as through expenses for control programs. The aim of this systematic review was to review financial and/or economic assessment studies of prevention and/or mitigation activities of BVDV at national, regional and farm level worldwide. Once all predefined criteria had been met, 35 articles were included for this systematic review. Studies were analyzed with particular focus on the type of financially and/or economically-assessed prevention and/or mitigation activities. Due to the wide range of possible prevention and/or mitigation activities, these activities were grouped into five categories: i) control and/or eradication programs, ii) monitoring or surveillance, iii) prevention, iv) vaccination and v) individual culling, control and testing strategies. Additionally, the studies were analyzed according to economically-related variables such as efficiency, costs or benefits of prevention and/or mitigation activities, the applied financial and/or economic and statistical methods, the payers of prevention and/or mitigation activities, the assessed production systems, and the countries for which such evaluations are available. Financial and/or economic assessments performed in Europe were dominated by those from the United Kingdom, which assessed mostly vaccination strategies, and Norway which primarily carried out assessments in the area of control and eradication programs; whereas among non-European countries the United States carried out the majority of financial and/or economic assessments in the area of individual culling, control and testing. More than half of all studies provided an efficiency calculation of prevention and/or mitigation activities and demonstrated whether the inherent costs of implemented activities were or were not justified. The dairy sector was three times more likely to be assessed by the countries than beef production systems. In addition, the dairy sector was approximately eight times more likely to be assessed economically with respect to prevention and/or mitigation activities than calf and youngstock production systems. Furthermore, the private sector was identified as the primary payer of prevention and/or mitigation activities. This systematic review demonstrated a lack of studies relating to efficiency calculations, in particular at national and regional level, and the specific production systems. Thus, we confirmed the need for more well-designed studies in animal health economics in order to demonstrate that the implementation and inherent costs of BVDV prevention and/or mitigation activities are justified.

Impact of Network Activity on the Spread of Infectious Diseases through the German Pig Trade Network

The trade of livestock is an important and growing economic sector, but it is also a major factor in the spread of diseases. The spreading of diseases in a trade network is likely to be influenced by how often existing trade connections are active. The activity α is defined as the mean frequency of occurrences of existing trade links, thus 0 < α ≤ 1. The observed German pig trade network had an activity of α = 0.11, thus each existing trade connection between two farms was, on average, active at about 10% of the time during the observation period 2008–2009. The aim of this study is to analyze how changes in the activity level of the German pig trade network influence the probability of disease outbreaks, size, and duration of epidemics for different disease transmission probabilities. Thus, we want to investigate the question, whether it makes a difference for a hypothetical spread of an animal disease to transport many animals at the same time or few animals at many times. A SIR model was used to simulate the spread of a disease within the German pig trade network. Our results show that for transmission probabilities <1, the outbreak probability increases in the case of a decreased frequency of animal transports, peaking range of α from 0.05 to 0.1. However, for the final outbreak size, we find that a threshold exists such that finite outbreaks occur only above a critical value of α, which is ~0.1, and therefore in proximity of the observed activity level. Thus, although the outbreak probability increased when decreasing α, these outbreaks affect only a small number of farms. The duration of the epidemic peaks at an activity level in the range of α = 0.2–0.3. Additionally, the results of our simulations show that even small changes in the activity level of the German pig trade network would have dramatic effects on outbreak probability, outbreak size, and epidemic duration. Thus, we can conclude and recommend that the network activity is an important aspect, which should be taken into account when modeling the spread of diseases within trade networks.

The Metabolically Active Bacterial Microbiome of Tonsils and Mandibular Lymph Nodes of Slaughter Pigs

The exploration of microbiomes in lymphatic organs is relevant for basic and applied research into explaining microbial translocation processes and understanding cross-contamination during slaughter. This study aimed to investigate whether metabolically active bacteria (MAB) could be detected within tonsils and mandibular lymph nodes (MLNs) of pigs. The hypervariable V1-V2 region of the bacterial 16S rRNA genes was amplified from cDNA from tonsils and MLNs of eight clinically healthy slaughter pigs. Pyrosequencing yielded 82,857 quality-controlled sequences, clustering into 576 operational taxonomic units (OTUs), which were assigned to 230 genera and 16 phyla. The actual number of detected OTUs per sample varied highly (23–171 OTUs). Prevotella zoogleoformans and Serratia proteamaculans (best type strain hits) were most abundant (10.6 and 41.8%, respectively) in tonsils and MLNs, respectively. To explore bacterial correlation patterns between samples of each tissue, pairwise Spearman correlations (r_s) were calculated. In total, 194 strong positive and negative correlations |r_s| ≥ 0.6 were found. We conclude that (i) lymphatic organs harbor a high diversity of MAB, (ii) the occurrence of viable bacteria in lymph nodes is not restricted to pathological processes and (iii) lymphatic tissues may serve as a contamination source in pig slaughterhouses. This study confirms the necessity of the EFSA regulation with regard to a meat inspection based on visual examinations to foster a minimization of microbial contamination.

The trade network in the dairy industry and its implication for the spread of contamination

In case of an outbreak of a foodborne disease, administrative decisions in the context of crisis management are only efficient if they follow standard practices and are specifically adapted to the outbreak situation in a timely manner. These goals are hard to achieve. The complexity of national and global trade structures obscures a clear view of trade flows and, consequently, it is often impossible to unravel complex trade links quickly. Furthermore, increasing public concerns about possible health hazards caused by global trade put additional pressure on decision makers. The aim of this paper was to unveil the specific trade structures of the German milk supply chain, to highlight how these structures could affect the spatial spread of a hypothetical contaminant, and to quantify the risk of the contaminant reaching the consumer. To achieve this goal, the vertical and horizontal trade links between milk producers, dairies, and consumers were taken into account. The horizontal flow of milk between dairies (inter-dairy trade), which is intended to compensate a temporary over- or undersupply of milk, is of special importance in this respect. We hypothesized that the extent of inter-dairy trade would significantly influence the spatial spread of contaminated milk and the contamination risk. This hypothesis was tested using a computer simulation model that predicts the hypothetical spread of a contaminant via trade of milk. The model parameters were estimated using trade data collected in 2004 and 2010. The results of our study indicate that inter-dairy trade significantly influenced the contamination risk. Compared with a scenario with no inter-dairy trade, the risk that contaminated milk will reach the consumer was up to 4 times higher, even with moderate inter-dairy trade. The contamination risk depended on the extent of inter-dairy trade in a nonlinear way and reached its maximum asymptotically when inter-dairy trade increased. The contamination risk exhibited considerable spatial variation, which could be utilized to implement more accurate food control interventions in times of crisis caused by a foodborne disease.