Variation in the timing and duration of autumn leaf phenology among temperate deciduous trees, native shrubs and non-native shrubs.

The timing and duration of autumn leaf phenology marks important transitions in temperate deciduous forests, such as, start of senescence, declining productivity and changing nutrient cycling. Phenological research on temperate deciduous forests typically focuses on upper canopy trees, overlooking the contribution of other plant functional groups like shrubs. Yet shrubs tend to remain green longer than trees, while non-native shrubs, in particular, tend to exhibit an extended growing season that confers a competitive advantage over native shrubs. We monitored leaf senescence and leaf fall (2017-2020) of trees and shrubs (native and non-native) in an urban woodland fragment in Wisconsin, USA. Our findings revealed that, the start of leaf senescence did not differ significantly between vegetation groups, but leaf fall started (DOY 273) two weeks later in shrubs. Non-native shrubs exhibited a considerably delayed start (DOY 262) and end of leaf senescence (DOY 300), with leaf-fall ending (DOY 315) nearly four weeks later than native shrubs and trees. Overall, the duration of the autumn phenological season was longer for non-native shrubs than either native shrubs or trees. Comparison of the timing of spring phenophases with the start and end of leaf senescence revealed that when spring phenology in trees starts later in the season senescence also starts later and ends earlier. The opposite pattern was observed in native shrubs. In conclusion, understanding the contributions of plant functional groups to overall forest phenology requires future investigation to ensure accurate predictions of future ecosystem productivity and help address discrepancies with remote sensing phenometrics.

Fostering effective and sustainable scientific collaboration and knowledge exchange: a workshop-based approach to establish a national ecological observatory network (NEON) domain-specific user group.

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA's National Ecological Observatory Network's (NEON's) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON's first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG's kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

Timing of dietary zinc additions during gestation for improved piglet survival.

The objectives of this study were to determine a practical approach to feeding elevated dietary zinc (Zn) to gestating sows in a commercial setting and to confirm preweaning mortality could be reduced by feeding high Zn to sows during different periods of gestation. The study was conducted at a commercial sow farm in the upper Midwest. Mixed parity sows (n = 267) over three consecutive weekly farrowing groups (sows farrowing within 1 wk) were assigned randomly to one of the three dietary treatments within parity. Treatments consisted of: (1) control sows fed a corn-soybean meal diet containing 206 mg/kg total supplemental Zn supplied by zinc hydroxychloride; (2) breed-to-farrow: as control + 147 mg/kg supplemental Zn as ZnSO4 (353 mg/kg total supplemental Zn) fed from 5 d after breeding to farrowing; and (3) day 110-to-farrow: as control fed from breeding to farrowing + 4,079 mg/kg supplemental Zn as ZnSO4 (4,285 mg/kg total supplemental Zn) starting day 110 of gestation until farrowing. At farrowing, individual piglets were weighed and identified within 12 h of birth. Data were analyzed using PROC GLIMMIX of SAS and the model considered the fixed effect of dietary treatment and random effect of farrowing group. Dietary treatments did not affect number of total pigs born per litter. For breed-to-farrow sows, there was an increase in the percentage of pigs born alive compared to sows fed the control and day 110-to-farrow treatments (P < 0.001). The number of stillborn pigs expressed as a percentage of total litter size at birth decreased for breed-to-farrow sows (P < 0.001) compared with control or day 110-to-farrow sows. Mortality of low birth weight piglets from birth to weaning did not differ among dietary treatments (P = 0.305); however, a trend for decreasing post-natal mortality (P = 0.068) of normal birth weight pigs was observed for pigs born to sows fed elevated Zn 5 d before farrowing. In conclusion, feeding elevated Zn to sows throughout gestation increased the proportion of pigs born alive suggesting that elevated gestational Zn intake makes piglets more robust to endure the stresses of farrowing and decreases intrapartum mortality. Under the conditions of this study, elevated Zn intake of sows did not influence piglet post-natal survival. However, feeding high zinc throughout gestation may decrease piglet mortality during the parturition process.

Characterizing spring phenology in a temperate deciduous urban woodland fragment: trees and shrubs.

Phenological research in temperate-deciduous forests typically focuses on upper canopy trees, due to their overwhelming influence on ecosystem productivity and function. However, considering that shrubs leaf out earlier and remain green longer than trees, they play a pivotal role in ecosystem productivity, particularly at growing season extremes. Furthermore, an extended growing season of non-native shrubs provides a competitive advantage over natives. Here, we report spring phenology, budburst, leaf-out, and full-leaf unfolded (2017-2021) of a range of co-occurring species of tree (ash, American basswood, red oak, white oak, and boxelder) and shrub (native species: chokecherry, pagoda dogwood, nannyberry, American wild currant and Eastern wahoo, and non-native species: buckthorn, honeysuckle, European privet, and European highbush cranberry) in an urban woodland fragment in Wisconsin, USA, to determine how phenology differed between plant groups. Our findings show that all three spring phenophases of shrubs were 3 weeks earlier (p < 0.05) than trees. However, differences between shrubs groups were only significant for the later phenophase; full-leaf unfolded, which was 6 days earlier (p < 0.05) for native shrubs. The duration of the spring phenological season was 2 weeks longer (p < 0.05) for shrubs than trees. These preliminary findings demonstrate that native shrubs, at this site, start full-leaf development earlier than non-native species suggesting that species composition must be considered when generalizing whether phenologies differ between vegetation groups. A longer time series would be necessary to determine future implications on ecosystem phenology and productivity and how this might impact forests in the future, in terms of species composition, carbon sequestration, and overall ecosystem dynamics.

A landmark environmental law looks ahead.

In late December 1973, the United States enacted what some would come to call "the pitbull of environmental laws." In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, obliging agencies to draw upon the best available science to protect species and habitats. Yet human pressures continue to push the planet toward extinctions on a massive scale. With that prospect looming, and with scientific understanding ever changing, Science invited experts to discuss how the ESA has evolved and what its future might hold. -Brad Wible.

Integrating Community Health Workers' Dual Clinic-Community Role in Safety-Net Primary Care: Implementation Lessons from a Pragmatic Diabetes-Prevention Trial.

BACKGROUND: Over a third of US adults carry a diagnosis of prediabetes, 70% of whom may progress to type 2 diabetes mellitus ("diabetes"). Community health workers (CHWs) can help patients undertake healthy behavior to prevent diabetes. However, there is limited guidance to integrate CHWs in primary care, specifically to address CHWs' dual clinic-based and community-oriented role. OBJECTIVE: Using evidence from CHWs' adaptations of a diabetes-prevention intervention in safety-net hospitals in New York City, we examine the nature, intent, and possible consequences of CHWs' actions on program fidelity. We propose strategies for integrating CHWs in primary care. DESIGN: Case study drawing on the Model for Adaptation Design and Impact (MADI) to analyze CHWs' actions during implementation of CHORD (Community Health Outreach to Reduce Diabetes), a cluster-randomized pragmatic trial (2017-2022) at Manhattan VA and Bellevue Hospital. PARTICIPANTS: CHWs and clinicians in the CHORD study, with a focus in this analysis on CHWs. APPROACH: Semi-structured interviews and focus group discussion with CHWs (n=4); semi-structured interviews with clinicians (n=17). Interpretivist approach to explain CHWs' adaptations using a mix of inductive and deductive analysis. KEY RESULTS: CHWs' adaptations extended the intervention in three ways: by extending social assistance, healthcare access, and operational tasks. The adaptations were intended to improve fit, reach, and retention, but likely had ripple effects on implementation outcomes. CHWs' focus on patients' complex social needs could divert them from judiciously managing their caseload. CONCLUSIONS: CHWs' community knowledge can support patient engagement, but overextension of social assistance may detract from protocolized health-coaching goals. CHW programs in primary care should explicitly delineate CHWs' non-health support to patients, include multiprofessional teams or partnerships with community-based organizations, establish formal communication between CHWs and clinicians, and institute mechanisms to review and iterate CHWs' work to resolve challenges in their community-oriented role.

Control technologies to prevent aerosol-based disease transmission in animal agriculture production settings: a review of established and emerging approaches.

Transmission of infectious agents via aerosols is an ever-present concern in animal agriculture production settings, as the aerosol route to disease transmission can lead to difficult-to-control and costly diseases, such as porcine respiratory and reproductive syndrome virus and influenza A virus. It is increasingly necessary to implement control technologies to mitigate aerosol-based disease transmission. Here, we review currently utilized and prospective future aerosol control technologies to collect and potentially inactivate pathogens in aerosols, with an emphasis on technologies that can be incorporated into mechanically driven (forced air) ventilation systems to prevent aerosol-based disease spread from facility to facility. Broadly, we find that control technologies can be grouped into three categories: (1) currently implemented technologies; (2) scaled technologies used in industrial and medical settings; and (3) emerging technologies. Category (1) solely consists of fibrous filter media, which have been demonstrated to reduce the spread of PRRSV between swine production facilities. We review the mechanisms by which filters function and are rated (minimum efficiency reporting values). Category (2) consists of electrostatic precipitators (ESPs), used industrially to collect aerosol particles in higher flow rate systems, and ultraviolet C (UV-C) systems, used in medical settings to inactivate pathogens. Finally, category (3) consists of a variety of technologies, including ionization-based systems, microwaves, and those generating reactive oxygen species, often with the goal of pathogen inactivation in aerosols. As such technologies are typically first tested through varied means at the laboratory scale, we additionally review control technology testing techniques at various stages of development, from laboratory studies to field demonstration, and in doing so, suggest uniform testing and report standards are needed. Testing standards should consider the cost-benefit of implementing the technologies applicable to the livestock species of interest. Finally, we examine economic models for implementing aerosol control technologies, defining the collected infectious particles per unit energy demand.

Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study.

OBJECTIVES: This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS: We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS: We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS: We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

Social and Medical Determinants of Diabetes: A Time-Constrained Multiple Mediator Analysis.

Background A number of studies have shown an association between social determinants of health and the emergence of obesity and diabetes, but whether the relationship is causal is not clear. Objective To test whether social, environmental, and medical determinants directly or indirectly affect population-level diabetes prevalence after controlling for mediator-mediator interactions. Methods Data were obtained from the CDC and supplemented with nine other data sources for 3,109 US counties. The dependent variable was the prevalence of diabetes in 2017. Independent variables were a given county's 30 social, environmental, and medical characteristics in 2015 and 2016. A network multiple mediation analysis was conducted. First, we used Least Absolute Shrinkage and Selection Operator (LASSO) regression to relate the 2017 diabetes rate in each county to 30 predictors measured in 2016, identifying statistically significant and robust predictors as the mediators within the network model and as direct determinants of 2017 diabetes. Second, each of the direct causes of diabetes was taken as a new response variable and LASSO-regressed on the same 30 independent variables measured in 2015, identifying the indirect (mediated) causes of diabetes. Subsequently, these direct and indirect predictors were used to construct a network model. The completed network was then employed to estimate the direct and mediated impact of variables on diabetes. Results For 2017 diabetes rates, 63% of the variation was explained by five variables measured in 2016: the percentage of residents who were (1) obese, (2) African American, (3) physically inactive, (4) in poor health condition, and (5) had a history of diabetes. These five direct predictors, measured in 2016, mediated the effect of indirect variables measured in 2015, including the percentage of residents who were (1) Hispanic, (2) physically distressed, (3) smokers, (4) living with children in poverty, (5) experiencing limited access to healthy foods, and (6) had low income. Conclusion All of the direct predictors of diabetes prevalence, except the percentage of residents who were African American, were medical conditions potentially influenced by lifestyles. Counties characterized by higher levels of obesity, inactivity, and poor health conditions exhibited increased diabetes rates in the following year. The impact of social determinants of illness, such as low income, children in poverty, and limited access to healthy foods, had an indirect effect on the health of residents and, consequently, increased the prevalence of diabetes.

Ten best practices for effective phenological research.

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project's needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

Disentangling transport movement patterns of trucks either transporting pigs or while empty within a swine production system before and during the COVID-19 epidemic.

Transport of pigs between sites occurs frequently as part of genetic improvement and age segregation. However, a lack of transport biosecurity could have catastrophic implications if not managed properly as disease spread would be imminent. However, there is a lack of a comprehensive study of vehicle movement trends within swine systems in the Midwest. In this study, we aimed to describe and characterize vehicle movement patterns within one large Midwest swine system representative of modern pig production to understand movement trends and proxies for biosecurity compliance and identify potential risky behaviors that may result in a higher risk for infectious disease spread. Geolocation tracking devices recorded vehicle movements of a subset of trucks and trailers from a production system every 5 min and every time tracks entered a landmark between January 2019 and December 2020, before and during the COVID-19 pandemic. We described 6,213 transport records from 12 vehicles controlled by the company. In total, 114 predefined landmarks were included during the study period, representing 5 categories of farms and truck wash facilities. The results showed that trucks completed the majority (76.4%, 2,111/2,762) of the recorded movements. The seasonal distribution of incoming movements was similar across years (P > 0.05), while the 2019 winter and summer seasons showed higher incoming movements to sow farms than any other season, year, or production type (P < 0.05). More than half of the in-movements recorded occurred within the triad of sow farms, wean-to-market stage, and truck wash facilities. Overall, time spent at each landmark was 9.08% higher in 2020 than in 2019, without seasonal highlights, but with a notably higher time spent at truck wash facilities than any other type of landmark. Network analyses showed high connectivity among farms with identifiable clusters in the network. Furthermore, we observed a decrease in connectivity in 2020 compared with 2019, as indicated by the majority of network parameter values. Further network analysis will be needed to understand its impact on disease spread and control. However, the description and quantification of movement trends reported in this study provide findings that might be the basis for targeting infectious disease surveillance and control.

Comparison of Primary Care Patients' and Unannounced Standardized Patients' Perceptions of Care.

The objective of this study was to compare unannounced standardized patient (USP) and patient reports of care. Patient satisfaction surveys and USP checklist results collected at an urban, public hospital were compared to identify items included in both surveys. Qualitative commentary was reviewed to better understand USP and patient satisfaction survey data. Analyses included χ2 and Mann-Whitney U test. Patients provided significantly higher ratings on 10 of the 11 items when compared to USPs. USPs may provide a more objective perspective on a clinical encounter than a real patient, reinforcing the notion that real patients skew overly positive or negative.

Mediation of an association between neighborhood socioeconomic environment and type 2 diabetes through the leisure-time physical activity environment in an analysis of three independent samples.

INTRODUCTION: Inequitable access to leisure-time physical activity (LTPA) resources may explain geographic disparities in type 2 diabetes (T2D). We evaluated whether the neighborhood socioeconomic environment (NSEE) affects T2D through the LTPA environment. RESEARCH DESIGN AND METHODS: We conducted analyses in three study samples: the national Veterans Administration Diabetes Risk (VADR) cohort comprising electronic health records (EHR) of 4.1 million T2D-free veterans, the national prospective cohort REasons for Geographic and Racial Differences in Stroke (REGARDS) (11 208 T2D free), and a case-control study of Geisinger EHR in Pennsylvania (15 888 T2D cases). New-onset T2D was defined using diagnoses, laboratory and medication data. We harmonized neighborhood-level variables, including exposure, confounders, and effect modifiers. We measured NSEE with a summary index of six census tract indicators. The LTPA environment was measured by physical activity (PA) facility (gyms and other commercial facilities) density within street network buffers and population-weighted distance to parks. We estimated natural direct and indirect effects for each mediator stratified by community type. RESULTS: The magnitudes of the indirect effects were generally small, and the direction of the indirect effects differed by community type and study sample. The most consistent findings were for mediation via PA facility density in rural communities, where we observed positive indirect effects (differences in T2D incidence rates (95% CI) comparing the highest versus lowest quartiles of NSEE, multiplied by 100) of 1.53 (0.25, 3.05) in REGARDS and 0.0066 (0.0038, 0.0099) in VADR. No mediation was evident in Geisinger. CONCLUSIONS: PA facility density and distance to parks did not substantially mediate the relation between NSEE and T2D. Our heterogeneous results suggest that approaches to reduce T2D through changes to the LTPA environment require local tailoring.

Implementation fidelity to a behavioral diabetes prevention intervention in two New York City safety net primary care practices.

BACKGROUND: It is critical to assess implementation fidelity of evidence-based interventions and factors moderating fidelity, to understand the reasons for their success or failure. However, fidelity and fidelity moderators are seldom systematically reported. The study objective was to conduct a concurrent implementation fidelity evaluation and examine fidelity moderators of CHORD (Community Health Outreach to Reduce Diabetes), a pragmatic, cluster-randomized, controlled trial to test the impact of a Community Health Workers (CHW)-led health coaching intervention to prevent incident type 2 Diabetes Mellitus in New York (NY). METHODS: We applied the Conceptual Framework for Implementation Fidelity to assess implementation fidelity and factors moderating it across the four core intervention components: patient goal setting, education topic coaching, primary care (PC) visits, and referrals to address social determinants of health (SDH), using descriptive statistics and regression models. PC patients with prediabetes receiving care from safety-net patient-centered medical homes (PCMHs) at either, VA NY Harbor or at Bellevue Hospital (BH) were eligible to be randomized into the CHW-led CHORD intervention or usual care. Among 559 patients randomized and enrolled in the intervention group, 79.4% completed the intake survey and were included in the analytic sample for fidelity assessment. Fidelity was measured as coverage, content adherence and frequency of each core component, and the moderators assessed were implementation site and patient activation measure. RESULTS: Content adherence was high for three components with nearly 80.0% of patients setting ≥ 1 goal, having ≥ 1 PC visit and receiving ≥ 1 education session. Only 45.0% patients received ≥ 1 SDH referral. After adjusting for patient gender, language, race, ethnicity, and age, the implementation site moderated adherence to goal setting (77.4% BH vs. 87.7% VA), educational coaching (78.9% BH vs. 88.3% VA), number of successful CHW-patient encounters (6 BH vs 4 VA) and percent of patients receiving all four components (41.1% BH vs. 25.7% VA). CONCLUSIONS: The fidelity to the four CHORD intervention components differed between the two implementation sites, demonstrating the challenges in implementing complex evidence-based interventions in different settings. Our findings underscore the importance of measuring implementation fidelity in contextualizing the outcomes of randomized trials of complex multi-site behavioral interventions. TRIAL REGISTRATION: The trial was registered with ClinicalTrials.gov on 30/12/2016 and the registration number is NCT03006666 .

Mapping mitonuclear epistasis using a novel recombinant yeast population.

Genetic variation in mitochondrial and nuclear genomes can perturb mitonuclear interactions and lead to phenotypic differences between individuals and populations. Despite their importance to most complex traits, it has been difficult to identify the interacting mitonuclear loci. Here, we present a novel advanced intercrossed population of Saccharomyces cerevisiae yeasts, called the Mitonuclear Recombinant Collection (MNRC), designed explicitly for detecting mitonuclear loci contributing to complex traits. For validation, we focused on mapping genes that contribute to the spontaneous loss of mitochondrial DNA (mtDNA) that leads to the petite phenotype in yeast. We found that rates of petite formation in natural populations are variable and influenced by genetic variation in nuclear DNA, mtDNA and mitonuclear interactions. We mapped nuclear and mitonuclear alleles contributing to mtDNA stability using the MNRC by integrating a term for mitonuclear epistasis into a genome-wide association model. We found that the associated mitonuclear loci play roles in mitotic growth most likely responding to retrograde signals from mitochondria, while the associated nuclear loci with main effects are involved in genome replication. We observed a positive correlation between growth rates and petite frequencies, suggesting a fitness tradeoff between mitotic growth and mtDNA stability. We also found that mtDNA stability was correlated with a mobile mitochondrial GC-cluster that is present in certain populations of yeast and that selection for nuclear alleles that stabilize mtDNA may be rapidly occurring. The MNRC provides a powerful tool for identifying mitonuclear interacting loci that will help us to better understand genotype-phenotype relationships and coevolutionary trajectories.

Assessing the role of sow parity on PRRSv detection by RT-qPCR through weekly processing fluids monitoring in breeding herds.

The use of processing fluids to monitor the breeding herd's porcine reproductive and respiratory syndrome (PRRS) status has gained industry acceptance. However, little is known about PRRS virus RT-qPCR detection dynamics in processing fluids and factors that may contribute to maintain PRRS virus in the herd after an outbreak. This study aimed to describe weekly RT-qPCR processing fluid results in breeding herds after an outbreak and to evaluate the proportion of RT-qPCR positive results among parity groups. Processing tissues of 15 first parity (P1), 15 second parity (P2), and 15 third parity or higher (P3+) litters (parity groups) were collected weekly for between 19 and 46 weeks in nine breeding herds. Processing fluids were aggregated, and RT-qPCR tested by parity group weekly. Additionally, a subset of 743 processing fluid samples of litters that formed 50 parity groups, as previously described, were RT-qPCR tested individually at the litter level. The agreement between RT-qPCR results of processing fluid samples of parity groups (15 litters) and results based on individual litter testing was assessed using overall percent of agreement, Kappa statistic, and McNemar test. The association between RT-qPCR results and the parity group was evaluated using a generalized estimating equations model, after accounting for the effects of sampling week, breeding herd PRRS control strategy (i.e., open to replacements v/s closed) and herd. An autoregressive correlation structure was used to account for the repeated samplings within a herd in time. The overall agreement was 98 %, and Kappa statistic 0.955 (McNemar p = 1.0). Sensitivity of parity group processing fluid samples was estimated at 100 % (95 % CI 89-100 %), while specificity was estimated at 94 % (95 % CI 71-100 %). Although P1 aggregated litters had on average a higher proportion of RT-qPCR positive results from outbreak week 25 onwards, the proportion was not significantly different to the one observed for P2 and P3+ aggregated litters (p > 0.13). Additionally, herds that interrupted gilt entry had lower odds of PRRS RT-qPCR positivity than herds that continued entering gilts (OR = 0.35, 95 % CI 0.16-0.78). PRRS virus persistence in processing fluids was not affected by the sow parity effect in most of the breeding herds studied. No evidence of disagreement between RT-qPCR results of an aggregated sample of 15 litters and those of individual litters was observed. This level of litter aggregation testing strategy may be of particular use at the last stages of an elimination program under low PRRS virus prevalence.

Predicting 6-month mortality of patients from their medical history: Comparison of multimorbidity index to Deyo-Charlson index.

While every disease could affect a patient's prognosis, published studies continue to use indices that include a selective list of diseases to predict prognosis, which may limit its accuracy. This paper compares 6-month mortality predicted by a multimorbidity index (MMI) that relies on all diagnoses to the Deyo version of the Charlson index (DCI), a popular index that utilizes a selective set of diagnoses. In this retrospective cohort study, we used data from the Veterans Administration Diabetes Risk national cohort that included 6,082,018 diabetes-free veterans receiving primary care from January 1, 2008 to December 31, 2016. For the MMI, 7805 diagnoses were assigned into 19 body systems, using the likelihood that the disease will increase risk of mortality. The DCI used 17 categories of diseases, classified by clinicians as severe diseases. In predicting 6-month mortality, the cross-validated area under the receiver operating curve for the MMI was 0.828 (95% confidence interval of 0.826-0.829) and for the DCI was 0.749 (95% confidence interval of 0.748-0.750). Using all available diagnoses (MMI) led to a large improvement in accuracy of predicting prognosis of patients than using a selected list of diagnosis (DCI).

Disparities in routine healthcare utilization disruptions during COVID-19 pandemic among veterans with type 2 diabetes.

BACKGROUND: While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS: We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS: In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS: Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

The effect of gilt flow management during acclimation on Mycoplasma hyopneumoniae detection.

The objective of this study was to characterize the Mycoplasma hyopneumoniae (M. hyopneumoniae) detection and seroconversion patterns in recently acclimated gilts to be introduced to endemically infected farms using different types of replacement management. Three gilt developing units (GDUs) belonging to sow farms were included in this investigation: two farms managed gilts in continuous flow, and one farm managed gilts all-in/all-out. Two replicates of 35 gilts each were selected per GDU and sampled approximately every 60 days for a total of four or five samplings, per replicate and per GDU. Detection of M. hyopneumoniae was evaluated by PCR, while antibodies were measured using a commercial ELISA assay. Also, M. hyopneumoniae genetic variability was evaluated using Multiple-Locus Variable number tandem repeat Analysis. Detection of M. hyopneumoniae was similar across GDUs. Although a significant proportion of gilts was detected positive for M. hyopneumoniae after acclimation, an average of 30.3 % of gilts was negative at any point during the study. Detection of M. hyopneumoniae antibodies was similar among GDUs regardless of flow type or vaccination protocol. The genetic variability analysis revealed a limited number of M. hyopneumoniae types within each GDU. Results of this study showed a similar pattern of M. hyopneumoniae detection by PCR and seroconversion by ELISA among GDUs, regardless of the type of flow management strategies applied to gilts.