Characterization of swine movements in the United States and implications for disease control.

Understanding between-farm movement patterns is an essential component in developing effective surveillance and control programs in livestock populations. Quantitative knowledge on movement patterns is particularly important for the commercial swine industry, in which large numbers of pigs are frequently moved between farms. Here, we described the annual movement patterns between swine farms in three production systems of the United States and identified farms that may be targeted to increase the efficacy of infectious disease control strategies. Research results revealed a high amount of variability in movement patterns across production systems, indicating that quantities captured from one production system and applied to another may lead to invalid estimations of disease spread. Furthermore, we showed that targeting farms based on their mean infection potential, a metric that captured the temporal sequence of movements, substantially reduced the potential for transmission of an infectious pathogen in the contact network and performed consistently well across production systems. Specifically, we found that by targeting farms based on their mean infection potential, we could reduce the potential spread of an infectious pathogen by 80% when removing approximately 25% of farms in each of the production systems. Whereas other metrics, such as degree, required 26-35% of farms to be removed in two of the production systems to reach the same outcome; this outcome was not achievable in one of the production systems. Our results demonstrate the importance of fine-scale temporal movement data and the need for in-depth understanding of the contact structure in developing more efficient disease surveillance and response strategies in swine production systems.

Managing complexity: Simplifying assumptions of foot-and-mouth disease models for swine.

Compartmental models have often been used to test the effectiveness and efficiency of alternative control strategies to mitigate the spread of infectious animal diseases. A fundamental principle of epidemiological modelling is that models should start as simple as possible and become as complex as needed. The simplest version of a compartmental model assumes that the population is closed, void of births and deaths and that this closed population mixes homogeneously, meaning that each infected individual has an equal probability of coming into contact with each susceptible individual in the population. However, this assumption may oversimplify field conditions, leading to conclusions about disease mitigation strategies that are suboptimal. Here, we assessed the impact of the homogeneous mixing/closed population assumption, which is commonly assumed for within-farm models of highly contagious diseases of swine, such as foot-and-mouth disease (FMD), on predictions about disease spread. Incorporation of farm structure (different barns or rooms for breeding and gestation, farrowing, nursery and finishing) and demography (piglet births and deaths, and animal movement within and off of the farm) resulted in transmission dynamics that differed in the latter portion of an outbreak. Specifically, farm structure and demography, which were included in the farrow to finish and farrow to wean farms, resulted in FMD virus persistence within the population under certain conditions. Results here demonstrate the impact of incorporating farm structure and demography into models of FMD spread in swine populations and will ultimately contribute to the design and evaluation of effective disease control strategies to mitigate the impact of potential incursions.

Influenza A virus in swine breeding herds: Combination of vaccination and biosecurity practices can reduce likelihood of endemic piglet reservoir.

Recent modelling and empirical work on influenza A virus (IAV) suggests that piglets play an important role as an endemic reservoir. The objective of this study is to test intervention strategies aimed at reducing the incidence of IAV in piglets and ideally, preventing piglets from becoming exposed in the first place. These interventions include biosecurity measures, vaccination, and management options that swine producers may employ individually or jointly to control IAV in their herds. We have developed a stochastic Susceptible-Exposed-Infectious-Recovered-Vaccinated (SEIRV) model that reflects the spatial organization of a standard breeding herd and accounts for the different production classes of pigs therein. Notably, this model allows for loss of immunity for vaccinated and recovered animals, and for vaccinated animals to have different latency and infectious periods from unvaccinated animals as suggested by the literature. The interventions tested include: (1) varied timing of gilt introductions to the breeding herd, (2) gilt separation (no indirect transmission to or from the gilt development unit), (3) gilt vaccination upon arrival to the farm, (4) early weaning, and (5) vaccination strategies of sows with different timing (mass and pre-farrow) and efficacy (homologous vs. heterologous). We conducted a Latin Hypercube Sampling and Partial Rank Correlation Coefficient (LHS-PRCC) analysis combined with a random forest analysis to assess the relative importance of each epidemiological parameter in determining epidemic outcomes. In concert, mass vaccination, early weaning of piglets (removal 0-7days after birth), gilt separation, gilt vaccination, and longer periods between introductions of gilts (6 months) were the most effective at reducing prevalence. Endemic prevalence overall was reduced by 51% relative to the null case; endemic prevalence in piglets was reduced by 74%; and IAV was eliminated completely from the herd in 23% of all simulations. Importantly, elimination of IAV was most likely to occur within the first few days of an epidemic. The latency period, infectious period, duration of immunity, and transmission rate for piglets with maternal immunity had the highest correlation with three separate measures of IAV prevalence; therefore, these are parameters that warrant increased attention for obtaining empirical estimates. Our findings support other studies suggesting that piglets play a key role in maintaining IAV in breeding herds. We recommend biosecurity measures in combination with targeted homologous vaccination or vaccines that provide wider cross-protective immunity to prevent incursions of virus to the farm and subsequent establishment of an infected piglet reservoir.

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region.

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Mosquitoes in Moose Country: A Mosquito Survey of Northern Minnesota.

An adult mosquito survey was conducted at 12 sites using carbon dioxide traps in northern Minnesota throughout the summer of 2012. Specimens were counted, identified to species, sorted into pools, and tested for eastern equine encephalitis (EEEV) and West Nile virus (WNV). Our findings extend the known range of Culiseta melanura, Anopheles barberi, and An. quadrimaculatus and document the presence and abundance of 27 other mosquito taxa in the region. None of the pools tested positive for EEEV or WNV.

From network analysis to risk analysis--An approach to risk-based surveillance for bovine tuberculosis in Minnesota, US.

Bovine tuberculosis (bTB) was first detected in 2005 in cattle in northwestern Minnesota (MN) through slaughter surveillance. By the end of 2008, 12 cattle herds were infected with bTB, and the main cause for infection was determined to be the movement of infected animals between herds. Bovine tuberculosis was contained in a smaller area in northwestern Minnesota classified as modified accredited (MA), corresponding to a prevalence inferior to 0.1% in cattle. From January 2008 to 2011, all cattle movements within the bTB MA were recorded electronically. The primary objectives of this study were to characterize cattle movements within this region and identify cattle herds with higher risk of bTB introduction based on network parameters and known risk factors from the published literature. During the period that data was collected, 57,460 cattle were moved in 3762 movements corresponding to permits issued to 682 premises, mostly representing private farms, sale yards, slaughter facilities and county or state fairs. Although sale yards represented less than 2% of the premises (nodes), 60% of the movements were to or from a sale yard. The network showed an overall density of 0.4%, a clustering coefficient of 14.6% and a betweenness centralization index of 12.7%, reflecting the low connectivity of this cattle network. The degree distribution showed that 20% of nodes performed 90% of the movements. Farms were ranked based on the total risk score and divided into high, medium, and low risk groups based on the score and its variability. The higher risk group included 14% (n=50) of the farms, corresponding to 80% of the cumulative risk for the farms in the bTB area. This analysis provides a baseline description about the contact structure of cattle movements in an area previously infected with bTB and develops a framework for a targeted surveillance approach for bTB to support future surveillance decisions.

Dynamics of a multihost pathogen in a carnivore community.

1. We provide the first theoretical analysis of multihost disease dynamics to incorporate social behaviour and contrasting rates of within- and between-group disease transmission. 2. A stochastic susceptible-infected-recovered (SIR) model of disease transmission involving one to three sympatric species was built to mimic the 1994 Serengeti canine distemper virus outbreak, which infected a variety of carnivores with widely ranging social structures. The model successfully mimicked the erratic and discontinuous spatial pattern of lion deaths observed in the Serengeti lions under a reasonable range of parameter values, but only when one to two other species repeatedly transmitted the virus to the lion population. 3. The outputs from our model suggest several principles that will apply to most directly transmitted multihost pathogens: (i) differences in social structure can significantly influence the size, velocity and spatial pattern of a multihost epidemic; and (ii) social structures that permit higher intraspecific neighbour-to-neighbour transmission are the most likely to transmit disease to other species; whereas (iii) species with low neighbour-to-neighbour intraspecific transmission suffer the greatest costs from interspecific transmission.