Simulation of Cross-border Impacts Resulting from Classical Swine Fever Epidemics within the Netherlands and Germany

Risks of introduction and economic consequences associated with African swine fever, classical swine fever and foot-and-mouth disease: A review of the literature

African swine fever (ASF), classical swine fever (CSF) and foot-and-mouth disease (FMD) are considered to be three of the most detrimental animal diseases and are currently foreign to the U.S. Emerging and re-emerging pathogens can have tremendous impacts in terms of livestock morbidity and mortality events, production losses, forced trade restrictions, and costs associated with treatment and control. The United States is the world's top producer of beef for domestic and export use and the world's third-largest producer and consumer of pork and pork products; it has also recently been either the world's largest or second largest exporter of pork and pork products. Understanding the routes of introduction into the United States and the potential economic impact of each pathogen are crucial to (a) allocate resources to prevent routes of introduction that are believed to be more probable, (b) evaluate cost and efficacy of control methods and (c) ensure that protections are enacted to minimize impact to the most vulnerable industries. With two scoping literature reviews, pulled from global data, this study assesses the risk posed by each disease in the event of a viral introduction into the United States and illustrates what is known about the economic costs and losses associated with an outbreak.

Development of simulation models for transmission of Salmonid Rickettsial Septicaemia between salt water fish farms in Chile

This study aimed at estimating parameters representing between-farm transmission of Salmonid Rickettsial Septicaemia (SRS) in Chile, and developing and validating simulation models to predict weekly spread of SRS between farms in Los Lagos (Region 10), using InterSpread Plus. The model parameters were estimated by analyses of the historical SRS outbreak data. The models incorporated time and distance-dependent transmission kernels, representing the probabilities of waterborne spread of SRS between farms. Seven candidate transmission kernels were estimated, with varying maximum distance of between-farm SRS spread (15-60 km). Farms were categorized by size (small; medium; large) and species (Coho salmon; Atlantic salmon; rainbow trout). The time that it took a farm to recover from infection was parameterized to be shortest for small Coho farms (median: 7 weeks), followed by medium and large Coho farms (median: 25 weeks), Atlantic salmon farms (median: 42 weeks, any size) and rainbow trout farms (median: 43 weeks, any size). The relative infectiousness parameters of rainbow trout farms were 1.5-6.3 times that of Coho or Atlantic salmon, or those of large farms was 1.3-4.2 times that of small or medium farms. The models predicted SRS prevalence in Region 10 between 2013 and 2015 (79 weeks) with 76.5%-93.0% overall accuracy. The model with a transmission kernel of <20 km (P20) achieved a maximum overall accuracy (93.0%). Within each neighbourhood, the accuracy of P20 varied between 32.4% and 88.1%; 13/20 neighbourhoods had a reasonable temporal agreement between the simulated and actual dynamics of SRS (within 5th-95th percentiles), but 5/20 neighbourhoods underestimated and 2/20 overestimated the SRS spread. The model could be used for evaluation of semi-global control policies in Region 10, while addition of other factors such as seasonality, ocean currents, and movement of infected fish may improve the model performance at a finer scale.

Willingness to Comply With Biosecurity in Livestock Facilities: Evidence From Experimental Simulations

Disease in U.S. animal livestock industries annually costs over a billion dollars. Adoption and compliance with biosecurity practices is necessary to successfully reduce the risk of disease introduction or spread. Yet, a variety of human behaviors, such as the urge to minimize time costs, may induce non-compliance with biosecurity practices. Utilizing a “serious gaming” approach, we examine how information about infection risk impacts compliance with biosecurity practices. We sought to understand how simulated environments affected compliance behavior with treatments that varied using three factors: (1) the risk of acquiring an infection, (2) the delivery method of the infection risk message (numerical, linguistic and graphical), and (3) the certainty of the infection risk information. Here we show that compliance is influenced by message delivery methodology, with numeric, linguistic, and graphical messages showing increasing efficacy, respectively. Moreover, increased situational uncertainty and increased risk were correlated with increases in compliance behavior. These results provide insight toward developing messages that are more effective and provide tools that will allow managers of livestock facilities and policy makers to nudge behavior toward more disease resilient systems via greater compliance with biosecurity practices.