Identifying Priority Areas for Chronic Wasting Disease Surveillance in Montana

Chronic Wasting Disease is a fatal prion disease affecting ungulate species throughout North America.  As of 2013, no CWD positive deer have been found in the state of Montana, however, several surrounding states and provinces have identified multiple cases of the disease.  We used information on mule deer habitat selection, abundance, and locations of CWD cases in surrounding states to identify priority areas in Montana for CWD surveillance. The habitat selection models were based on over 10000 VHF and GPS locations collected from mule deer from 1975-2011, and predicted resource selection function (RSF) values for winter and summer in 5 of the 7 wildlife management regions in the state of Montana. We estimated mule deer density using the aerial survey counts weighted by the value of the RSF for each pixel. High priority areas were those that contained the highest densities of mule deer and were closest to locations with CWD positive deer. This information can be used to inform Montana’s CWD surveillance program for mule deer. We concluded that based on mule deer distribution and movement patterns several mule deer herds in Montana were at risk of coming into contact with deer from known infected herds

Combining Hunter Surveys and Territorial Dynamics to Monitor Wolf Pack Abundance and Distribution in Montana

Carnivores are difficult to monitor on large spatial scales. We developed a patch occupancy model (POM) using hunter surveys to monitor gray wolves (Canis lupus) in Montana, and evaluated the ability of these models to provide wildlife managers with a time-and cost-efficient monitoring technique. We used hunter’s sightings of wolves as our index of occupancy and explored how classifying a patch as occupied based on different minimum number of wolves sighted (1,2,3,4, or 5) or different minimum number of hunters sighting wolves (1,2,3,4,or 5) affected results. We also evaluated how our definition of a “patch” influenced the occupancy estimates by creating POMs with 3 different patch sizes that corresponded to the variation in wolf territory sizes in Montana. We ran multiple models with different patch sizes predicting occupancy classified according to different levels of minimum wolf sightings and minimum hunters seeing wolves. We assessed model accuracy by comparing POM estimates to the Montana Fish, Wildlife, and Parks (FWP) minimum wolf pack count. Our preliminary results showed that patch size did not strongly influence occupancy estimates and that a patch should only be identified as occupied if ? 2 to ? 4 hunters each observed ? 2 to ? 4 wolves in that patch. Within this range, FWP’s minimum wolf pack count fell within the 95-percent confidence interval of POM estimates for 33 percent of the models

Importance Of Recruitment To Accurately Predict The Impacts Of Human-Caused Mortality On Wolf Populations

Reliable analyses can help wildlife managers make good decisions, which are particularly critical for controversial decisions such as wolf (Canis lupus) harvest. Creel and Rotella (2010) recently predicted substantial population declines in Montana wolf populations due to harvest, in contrast to predictions made by Montana Fish, Wildlife and Parks (MFWP). Here we replicate their analyses considering only those years in which field monitoring was consistent, and we consider the effect of annual variation in recruitment on wolf population growth. We also use model selection to evaluate models of recruitment and human-caused mortality rates in wolf populations in the Northern Rocky Mountains. Using data from 27 area-years of intensive wolf monitoring, we show that variation in both recruitment and human-caused mortality affect annual wolf population growth rates and that human-caused mortality rates have increased with the sizes of wolf populations. We also show that either recruitment rates have decreased with population sizes or that the ability of current field resources to document recruitment rates has recently become less successful as the number of wolves in the region has increased. Predictions of wolf population growth in Montana from our top models are consistent with field observations and estimates previously made by MFWP. Familiarity with limitations of raw data helps generate more reliable inferences and conclusions in analyses of publicly-available datasets. Additionally, development of efficient monitoring methods for wolves is a pressing need, so that analyses such as ours will be possible in future years when fewer resources will be available for monitoring

Assessing Organizational Readiness for Depression Care Quality Improvement: Relative Commitment and Implementation Capability

Background: Depression is a major cause of morbidity and cost in primary care patient populations. Successful depression improvement models, however, are complex. Based on organizational readiness theory, a practice’s commitment to change and its capability to carry out the change are both important predictors of initiating improvement. We empirically explored the links between relative commitment (i.e., the intention to move forward within the following year) and implementation capability. Methods: The DIAMOND initiative administered organizational surveys to medical and quality improvement leaders from each of 83 primary care practices in Minnesota. Surveys preceded initiation of activities directed at implementation of a collaborative care model for improving depression care. To assess implementation capability, we developed composites of survey items for five types of organizational factors postulated to be collaborative care barriers and facilitators. To assess relative commitment for each practice, we averaged leader ratings on an identical survey question assessing practice priorities. We used multivariable regression analyses to assess the extent to which implementation capability predicted relative commitment. We explored whether relative commitment or implementation capability measures were associated with earlier initiation of DIAMOND improvements. Results: All five implementation capability measures independently predicted practice leaders’ relative commitment to improving depression care in the following year. These included the following: quality improvement culture and attitudes (p = 0.003), depression culture and attitudes (p \u3c0.001), prior depression quality improvement activities (p \u3c0.001), advanced access and tracking capabilities (p = 0.03), and depression collaborative care features in place (p = 0.03). Higher relative commitment (p = 0.002) and prior depression quality improvement activities appeared to be associated with earlier participation in the DIAMOND initiative. Conclusions: The study supports the concept of organizational readiness to improve quality of care and the use of practice leader surveys to assess it. Practice leaders’ relative commitment to depression care improvement may be a useful measure of the likelihood that a practice is ready to initiate evidence-based depression care changes. A comprehensive organizational assessment of implementation capability for depression care improvement may identify specific barriers or facilitators to readiness that require targeted attention from implementers

The Effects of Patient-Centered Depression Care on Patient Satisfaction and Depression Remission

Background: While health systems are striving for patient-centered care, they have little evidence to guide them on how to engage patients in their care, or how this may affect patient experiences and outcomes. Objective: To explore which specific patient-centered aspects of care were best associated with depression improvement and care satisfaction. Methods: Design - observational. Setting - 83 primary care clinics across Minnesota. Subjects - Primary care patients with new prescriptions for antidepressants for depression were recruited from 2007 to 2009. Outcome measures - Patients completed phone surveys regarding demographics and self-rated health status and depression severity at baseline and 6 months. Patient centeredness was assessed via a modified version of the Patient Assessment of Chronic Illness Care. Differences in rates of remission and satisfaction between positive and negative responses for each care process were evaluated using chi-square tests. Results: At 6 months, 37% of 792 patients ages 18–88 achieved depression remission, and 79% rated their care as good-to-excellent. Soliciting patient preferences for care and questions or concerns, providing treatment plans, utilizing depression scales and asking about suicide risk were patient centered measures that were positively associated with depression remission in the unadjusted model; these associations were mildly weakened after adjustment for depression severity and health status. Nearly all measures of patient centeredness were positively associated with care ratings. Conclusion: The patient centeredness of care influences how patients experience and rate their care. This study identified specific actions providers can take to improve patient satisfaction and depression outcomes

The risk of progression to type 1 diabetes is highly variable in individuals with multiple autoantibodies following screening

Aims/hypothesis: Young children who develop multiple autoantibodies (mAbs) are at very high risk for type 1 diabetes. We assessed whether a population with mAbs detected by screening is also at very high risk, and how risk varies according to age, type of autoantibodies and metabolic status. Methods: Type 1 Diabetes TrialNet Pathway to Prevention participants with mAbs (n = 1815; age, 12.35 ± 9.39 years; range, 1-49 years) were analysed. Type 1 diabetes risk was assessed according to age, autoantibody type/number (insulin autoantibodies [IAA], glutamic acid decarboxylase autoantibodies [GADA], insulinoma-associated antigen-2 autoantibodies [IA-2A] or zinc transporter 8 autoantibodies [ZnT8A]) and Index60 (composite measure of fasting C-peptide, 60 min glucose and 60 min C-peptide). Cox regression and cumulative incidence curves were utilised in this cohort study. Results: Age was inversely related to type 1 diabetes risk in those with mAbs (HR 0.97 [95% CI 0.96, 0.99]). Among participants with 2 autoantibodies, those with GADA had less risk (HR 0.35 [95% CI 0.22, 0.57]) and those with IA-2A had higher risk (HR 2.82 [95% CI 1.76, 4.51]) of type 1 diabetes. Those with IAA and GADA had only a 17% 5 year risk of type 1 diabetes. The risk was significantly lower for those with Index60 <1.0 (HR 0.23 [95% CI 0.19, 0.30]) vs those with Index60 values ≥1.0. Among the 12% (225/1815) ≥12.0 years of age with GADA positivity, IA-2A negativity and Index60 <1.0, the 5 year risk of type 1 diabetes was 8%. Conclusions/interpretation: Type 1 diabetes risk varies substantially according to age, autoantibody type and metabolic status in individuals screened for mAbs. An appreciable proportion of older children and adults with mAbs appear to have a low risk of progressing to type 1 diabetes at 5 years. With this knowledge, clinical trials of type 1 diabetes prevention can better target those most likely to progress

Sheep Updates 2005 - Part 3

This session covers seven papers from different authors: CUSTOMER 1. Benefits VIAscanR to producers and WAMMCO, Rob Davidson, Supply Development Manager, David Pethick, School of Veterinary and Biomedical Studies, Murdock University. 2. Healthy fats in lamb: how WA lambs compare with others, C. F. Engelke Animal Biology, University of Western Australia, bCSIRO Livestock Industries, Western Australia B.D. Siebert, Department of Animal Science, University of Adelaide, South Australia, K. Gregg, Centre for High-Throughput Agricultural Genetic Analysis, Murdoch University, Western Australia. A-D.G. Wright CSIRO Livestock Industries, Western Australia, P.E Vercoe Animal Biology, University of Western Australia 3. Shelf life of fresh lamb meat: lamb age & electrical stimulation, Dr Robin Jacob, Department of Agriculture, Western Australia 4. Pastures from space - An evaluation of adoption of by Australian woolgrowers, Russell Barnett, Australian Venture Consultants, Joanne Sneddon, University of Western Australia 5. Your clients can learn from ASHEEP\u27s example, Sandra Brown Department of Agriculture Western Australia 6. Lifetime Wool - Farmers attitudes affect their adoption of recommended ewe management, G. Rose Department of Agriculture Western Australia, C. Kabore, Kazresearch, Lower Templestowe Vic, J. Dart, Clear Horizons, Hastings Vic 7. Sustainable certification of Australian Merino, what will customers be looking for? Stuart Adams, i-merino / iZWool International Pty Lt

Adaptive Wolf Management: The Regulated Public Harvest Component

Montana’s wolf (Canis lupus) conservation and management plan is based on adaptive management principles and includes regulated public harvest as a population management tool. The need and opportunity to implement public harvest in 2008, 2009, and 2010 required Montana Fish, Wildlife and Parks (FWP) to develop a stepped down adaptive management framework specific to harvest. For 2008 and 2009, FWP set modest objectives: implement a harvest, maintain a recovered population, and begin the learning process to inform development of future hunting regulations and quotas. In 2010, FWP used a formal Structured Decision Making Process to more clearly define priorities and challenges of setting a wolf season, outline objectives of a successful season, and evaluate consequences and trade-offs between alternative management actions. For all years, FWP used a modeling process to simulate a wide range of harvest rates across three harvest units and to predict harvest effects on the minimum number of wolves, packs and breeding pairs. Model inputs were derived from minimum wolf numbers observed in the field. Modeling allowed consideration of a range of harvest quotas, predicted outcomes, and risk that harvest could drive the population below federally-required minimums. It also facilitated explicit consideration of how well a particular quota achieved objectives and how to adapt future regulations and quotas. Legal challenges to federal delisting restricted implementation of the first fair chase hunting season to 2009. Montana’s wolf population is securely recovered, despite the dynamic political and legal environments. Regardless, FWP remains committed to a scientific, data-driven approach to adaptive management