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We explore whether staging (a combination of symbols, drawings, paintings, and re-creating action using Playmobil figures) used as a communicative activity of shared experiences influences the sense of fellowship. This study is part of a combined research and development project, and the findings are canalised back into the daily work. The assistants are interviewed, and the data are analysed in a coding process. We found that (1) ‘being confident’ is important for belongingness. Staging supports a shared understanding and a shared feeling of belonging. We also found that (2) developing a shared repertoire of concepts is possible when staging, and this scaffolds the fellowship. However, the concepts and the communication must (3) be meaningful to all parties. One does not take part in communication without meaning, and when one does not participate, one is not part of the fellowship. Staging enabled Magne, the main person in this study, to express himself better. Moreover, when discussing a shared experience with the personal assistants, Magne seemed to communicate well and showed signs of belonging. We conclude that communication about shared activities and experiences leads to interest and engagement and fosters a shared feeling of ‘doing something together’ and being part of a fellowship.

Antimicrobial drugs are a precious resource, responsible for saving millions of lives since their discovery. Unfortunately, some antimicrobials are rapidly losing their effectiveness due to the development and spread of antimicrobial resistance (AMR), a multi-faceted and complex problem affecting humans, animals, plants and the environment. While AMR is a global problem, in this paper, the authors briefly highlight some ongoing efforts in the United States of America aimed at integrating a One Health approach into policies and programmes that address this important health threat.

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.

Antimicrobial use in agriculture is considered a pathway for the selection and dissemination of resistance determinants among animal and human populations. From 1997 through 2003 the U.S. National Antimicrobial Resistance Monitoring System (NARMS) tested clinical Salmonella isolates from multiple animal and environmental sources throughout the United States for resistance to panels of 16-19 antimicrobials. In this study we applied two mixed effects models, the generalized linear mixed model (GLMM) and accelerated failure time frailty (AFT-frailty) model, to susceptible/resistant and interval-censored minimum inhibitory concentration (MIC) metrics, respectively, from Salmonella enterica subspecies enterica serovar Typhimurium isolates from livestock and poultry. Objectives were to compare characteristics of the two models and to examine the effects of time, species, and multidrug resistance (MDR) on the resistance of isolates to individual antimicrobials, as revealed by the models. Fixed effects were year of sample collection, isolate source species and MDR indicators; laboratory study site was included as a random effect. MDR indicators were significant for every antimicrobial and were dominant effects in multivariable models. Temporal trends and source species influences varied by antimicrobial. In GLMMs, the intra-class correlation coefficient ranged up to 0.8, indicating that the proportion of variance accounted for by laboratory study site could be high. AFT models tended to be more sensitive, detecting more curvilinear temporal trends and species differences; however, high levels of left- or right-censoring made some models unstable and results uninterpretable. Results from GLMMs may be biased by cutoff criteria used to collapse MIC data into binary categories, and may miss signaling important trends or shifts if the series of antibiotic dilutions tested does not span a resistance threshold. Our findings demonstrate the challenges of measuring the AMR ecosystem and the complexity of interacting factors, and have implications for future monitoring. We include suggestions for future data collection and analyses, including alternative modeling approaches., (Published by Elsevier B.V.)

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.

Background: A large multistate outbreak of equine herpesvirus myeloencephalopathy (EHM) occurred in May 2011 among horses that participated in a competitive event., Objective: To identify EHM risk factors among horses with a common exposure venue., Animals: A total of 123 horses: 19 horses with EHM, 14 equine herpesvirus-1 cases with no reported neurologic signs, and 90 control horses., Methods: EHM case survey data were compared with data from EHV-1 cases with no neurologic signs and healthy controls using univariable and multivariable methods., Results: Significant factors associated with higher risk for EHM compared with EHV-1 cases with no neurologic signs were (1) greater number of biosecurity risks at the event, (2) female sex, (3) increasing number of classes competed in at the event, and (4) an interaction between sex and number of classes competed in. In the EHM versus controls comparison, in addition to sex and biosecurity risks, factors associated with higher EHM risk included EHV-1 vaccination in the 5 weeks before the event and increasing number of events attended in April 2011; zinc dietary supplementation was associated with decreased risk. An interaction between sex and the number of events attended in April 2011 also was significant., Conclusions and Clinical Importance: Findings from this study suggest that dietary zinc supplementation may be associated with decreased risk of EHM. Several factors were associated with increased risk of EHM. Additional investigations of factors associated with risk of EHM are warranted to evaluate the importance of these factors in this complex disease of horses., (Copyright © 2013 by the American College of Veterinary Internal Medicine.)

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.

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.

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.

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.

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.

Fecal samples from 33 lions (Panthera leo) in Serengeti National Park and Ngorongoro Crater Conservation Area in northern Tanzania contained 19 different parasites, 12 of which, including Aelurostrongylus sp., a species of Acanthocephala, a species of Anoplocephalidae, Capillaria sp., Demodex sp., Eimeria sp., Habronema sp., Isospora felis, Isospora rivolta, one species of Isospora that was previously undescribed from lions, one species of Trematoda that was previously undescribed from lions, and Trichuris sp., were new reports for lions. Seven other species had been previously reported from lions.

Lions (Panthera leo) and cheetah (Acinonyx jubatus) from the Serengeti National Park and Ngorongoro Crater Conservation Area, Tanzania were examined for the presence of blood protozoans. Twenty-eight percent of the lions were infected with Trypanosoma sp. and the prevalence of trypanosome infection varied significantly between adjacent habitats. All of the animals were infected with Hepatozoon sp. and a Theileria sp.-like piroplasm that was morphologically indistinguishable from Theileria felis.