Factors Associated with Salmonella Prevalence in U.S. Swine Grower-Finisher Operations, 2012.

Nontyphoidal Salmonella is an important foodborne pathogen with diverse serotypes occurring in animal and human populations. The prevalence of the organism on swine farms has been associated with numerous risk factors, and although there are strong veterinary public health controls for preventing Salmonella from entering food, there remains interest in eradicating or controlling the organism in the preharvest environment. In this study, using data collected via the U.S. Department of Agriculture (USDA) National Animal Health Monitoring System Swine 2012 study, we describe nontyphoidal Salmonella and specific serotype prevalence on U.S. grower-finisher swine operations and investigate associations between Salmonella detection and numerous factors via multiple correspondence analysis (MCA) and regression analysis. MCA plots, complementary to univariate analyses, display relationships between covariates and Salmonella detection at the farm level. In the univariate analysis, Salmonella detection varied with feed characteristics and farm management practices, reports of diseases on farms and vaccinations administered, and administration of certain antimicrobials. Results from the univariate analysis reinforce the importance of biosecurity in managing diseases and pathogens such as Salmonella on farms. All multivariable regression models for the likelihood of Salmonella detection were strongly affected by multicollinearity among variables, and only one variable, pelleted feed preparation, remained in the final model. The study was limited by its cross-sectional nature, timelines of data collection, and reliance on operator-reported data via a convenience sample.

Epidemiologic characterization of Colorado backyard bird flocks.

Backyard gallinaceous bird flocks may play an important role in the spread of infectious diseases within poultry populations as well as the transmission of zoonotic diseases to humans. An epidemiologic characterization was conducted of Colorado backyard flocks to gather information on general flock characteristics, human movement of birds, human-bird interaction, biosecurity practices, and flock health. Our results suggest that backyard poultry flocks in Colorado are small-sized flocks (68.6% of flocks had < 50 birds); consist primarily of layer chickens (85.49% of flocks), show chickens (32.18% of flocks), and waterfowl (34.07% of flocks); and are primarily owned for food (meat or egg) production for the family (86.44%) or as pet or hobby birds (42.27%). The backyard flock environment may promote bird-to-bird transmission as well as bird-to-human transmission of infectious disease. Birds are primarily housed with free access to the outside (96.85%), and many are moved from the home premises (46.06% within 1 yr). Human contact with backyard flocks is high, biosecurity practices are minimal, and bird health is negatively impacted by increased movement events. Increased knowledge of backyard bird characteristics and associated management practices can provide guidelines for the development of measures to decrease disease transmission between bird populations, decrease disease transmission from birds to humans, and increase the overall health of backyard birds.

The impact of holding time on the likelihood of moving internally contaminated eggs from a highly pathogenic avian influenza infected but undetected commercial table-egg layer flock.

Emergency response during a highly pathogenic avian influenza (HPAI) outbreak may involve quarantine and movement controls for poultry products such as eggs. However, such disease control measures may disrupt business continuity and impact food security, since egg production facilities often do not have sufficient capacity to store eggs for prolonged periods. We propose the incorporation of a holding time before egg movement in conjunction with targeted active surveillance as a novel approach to move eggs from flocks within a control area with a low likelihood of them being contaminated with HPAI virus. Holding time reduces the likelihood of HPAI-contaminated eggs being moved from a farm before HPAI infection is detected in the flock. We used a stochastic disease transmission model to estimate the HPAI disease prevalence, disease mortality, and fraction of internally contaminated eggs at various time points postinfection of a commercial table-egg layer flock. The transmission model results were then used in a simulation model of a targeted matrix gene real-time reverse transcriptase (RRT)-PCR testing based surveillance protocol to estimate the time to detection and the number of contaminated eggs moved under different holding times. Our simulation results indicate a significant reduction in the number of internally contaminated eggs moved from an HPAI-infected undetected flock with each additional day of holding time. Incorporation of a holding time and the use of targeted surveillance have been adopted by the U.S. Department of Agriculture in their Draft Secure Egg Supply Plan for movement of egg industry products during an HPAI outbreak.

Impact of virus strain characteristics on early detection of highly pathogenic avian influenza infection in commercial table-egg layer flocks and implications for outbreak control.

Early detection of highly pathogenic avian influenza (HPAI) infection in commercial poultry flocks is a critical component of outbreak control. Reducing the time to detect HPAI infection can reduce the risk of disease transmission to other flocks. The timeliness of different types of detection triggers could be dependent on clinical signs that are first observed in a flock, signs that might vary due to HPAI virus strain characteristics. We developed a stochastic disease transmission model to evaluate how transmission characteristics of various HPAI strains might effect the relative importance of increased mortality, drop in egg production, or daily real-time reverse transcriptase (RRT)-PCR testing, toward detecting HPAI infection in a commercial table-egg layer flock. On average, daily RRT-PCR testing resulted in the shortest time to detection (from 3.5 to 6.1 days) depending on the HPAI virus strain and was less variable over a range of transmission parameters compared with other triggers evaluated. Our results indicate that a trigger to detect a drop in egg production would be useful for HPAI virus strains with long infectious periods (6-8 days) and including an egg-drop detection trigger in emergency response plans would lead to earlier and consistent reporting in some cases. We discuss implications for outbreak control and risk of HPAI spread attributed to different HPAI strain characteristics where an increase in mortality or a drop in egg production or both would be among the first clinical signs observed in an infected flock.

Moving-average trigger for early detection of rapidly increasing mortality in caged table-egg layers.

Rapidly increasing and unexplained mortality in commercial poultry flocks may signal the presence of a highly transmissible and reportable disease. Activation of an infectious-disease surveillance system occurs when a key production parameter, i.e., mortality, changes. Various triggers have been proposed to alert producers when mortality exceeds normal limits for a given production system to enable early detection of such diseases. In this article we demonstrate that a simple moving-average trigger is useful for detecting any disease syndrome in caged table-egg layer flocks that manifests itself as sudden, rapidly increasing mortality. We superimposed HPAI disease mortality output data derived from a disease transmission model and from a naturally occurring HPAI outbreak onto normal mortality data from 12 healthy commercial egg-layer flocks, and compared the performance of 7-day moving-average triggers to previously proposed triggers. The moving-average trigger is more efficient, resulting in fewer false-positive alerts and an earlier time to disease detection. It can be easily calculated by using a computer spreadsheet providing only 7 days of mortality data and can be practically and inexpensively implemented by large commercial poultry integrators. A moving-average trigger can be an active component of a production-based surveillance system.

Systematic order-dependent effect in expression values, variance, detection calls and differential expression in Affymetrix GeneChips.

MOTIVATION: Affymetrix GeneChips are common 3' profiling platforms for quantifying gene expression. Using publicly available datasets of expression profiles from human and mouse experiments, we sought to characterize features of GeneChip data to better compare and evaluate analyses for differential expression, regulation and clustering. We uncovered an unexpected order dependence in expression data that holds across a variety of chips in both human and mouse data. RESULTS: Order dependence among GeneChips affected relative expression measures pre-processed and normalized with the Affymetrix MAS5.0 algorithm and the robust multi-array average summarization method. The effect strongly influenced detection calls and tests for differential expression and can potentially significantly bias experimental results based on GeneChip profiling.

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.