Modelling the High Mercury Wet deposition in the Southeastern US by WRF-GC

High mercury wet deposition in southeastern United States has been noticed for many years. Previous studies came up with a theory that it was associated with high-altitude divalent mercury scavenged by convective precipitation. Given the coarse resolution of previous models (e.g. GEOS-Chem), this theory is still not fully tested. Here we employed a newly developed WRF-GEOS-Chem (WRF-GC) model implemented with mercury simulation. We conduct extensive model benchmarking by comparing WRF-GC with different resolutions (from 50 km to 25 km) to GEOS-Chem output (4° × 5°) and data from Mercury Deposition Network (MDN) in July–September 2013. The comparison of mercury wet deposition from two models both present high mercury wet deposition in southeastern United States. We divided simulation results by heights, different types of precipitation and combination of these two variations together and find most of mercury wet deposition concentrates on higher space and caused by convective precipitation. Therefore, we conclude that it is the deep convection caused enhanced mercury wet deposition in the southeastern United States.

Geographic distribution of Pythium insidiosum infections in the United States

OBJECTIVE To describe the geographic distribution of infections caused by Pythium insidiosum in dogs, horses, and other animal species in the US. ANIMALS For the last 20 years, we have collected data from cases of pythiosis in 1,150 horses, 467 dogs, and other species (59) from various geographic locations in the US. PROCEDURES Due to lost data (from 2006 to 2016), the selected cases include years 2000 to 2005 and 2016 to 2020. The selection of cases was based on infected host clinical features, serum samples demonstrating strong positive anti–P insidiosum IgG titers in serologic assays, and positive results on ≥ 1 of the following diagnostic modalities: microbial culture on 2% Sabouraud dextrose agar, histologic evaluation, PCR assay, and wet mount cytologic evaluation (with potassium hydroxide). RESULTS Most confirmed P insidiosum infections were found in horses and dogs in the southeastern US. Interestingly, in Texas, no cases were found west of longitude 100°W. Few pythiosis cases were diagnosed in west-coast states. Equine cases were more often diagnosed during summer and fall months, but canine cases were more often diagnosed between September and February. Cases in other species were discovered in the same geographic areas as those in dogs and horses. CLINICAL RELEVANCE To our knowledge, this is the first report providing the ecological distribution of P insidiosum infection in affected species in the US. Results of this study illustrated the importance of including P insidiosum in the differential diagnostic scheme of nonhealing skin lesions or intestinal granulomatous masses, particularly in dogs and horses inhabiting or having visited endemic areas.

COVID-19 symptoms at time of testing and association with positivity among outpatients tested for SARS-CoV-2

Introduction Symptoms associated with SARS-CoV-2 infection remain incompletely understood, especially among ambulatory, non-hospitalized individuals. With host factors, symptoms predictive of SARS-CoV-2 could be used to guide testing and intervention strategies. Methods Between March 16 and September 3, 2020, we examined the characteristics and symptoms reported by individuals presenting to a large outpatient testing program in the Southeastern US for nasopharyngeal SARS-CoV-2 RNA RT-PCR testing. Using self-reported symptoms, demographic characteristics, and exposure and travel histories, we identified the variables associated with testing positive using modified Poisson regression. Results Among 20,177 tested individuals, the proportion positive was 9.4% (95% CI, 9.0–9.8) and was higher for men, younger individuals, and racial/ethnic minorities (all P<0.05); the positivity proportion was higher for Hispanics (26.9%; 95% CI. 24.9–29.0) compared to Blacks (8.6%; 95% CI, 7.6–9.7) or Whites (5.8%; 95% CI, 5.4–6.3). Individuals reporting contact with a COVID-19 case had the highest positivity proportion (22.8%; 95% CI, 21.5–24.1). Among the subset of 8,522 symptomatic adults who presented for testing after May 1, when complete symptom assessments were performed, SARS-CoV-2 RNA PCR was detected in 1,116 (13.1%). Of the reported symptoms, loss of taste or smell was most strongly associated with SARS-CoV-2 RNA detection with an adjusted risk ratio of 3.88 (95% CI, 3.46–4.35). The presence of chills, fever, cough, aches, headache, fatigue and nasal congestion also significantly increased the risk of detecting SARS-CoV-2 RNA, while diarrhea or nausea/vomiting, although not uncommon, were significantly more common in those with a negative test result. Symptom combinations were frequent with 67.9% experiencing ≥4 symptoms, including 19.8% with ≥8 symptoms; report of greater than three symptoms increased the risk of SARS-CoV-2 RNA detection. Conclusions In a large outpatient population in the Southeastern US, several symptoms, most notably loss of taste or smell, and greater symptom burden were associated with detection of SARS-CoV-2 RNA. Persons of color and those with who were a contact of a COVID-19 case were also more likely to test positive. These findings suggest that, given limited SARS-CoV-2 testing capacity, symptom presentation and host characteristics can be used to guide testing and intervention prioritization.

Rapid Ecological Integrity Assessment Metrics to Restore Wildlife Habitat and Biodiversity for Shortleaf Pine–Oak Ecosystems

Open woodlands dominated by shortleaf pine (Pinus echinata Mill.) and oak are historically an important component of the landscape across the southeastern United States. These ecosystems support numerous wildlife species, many of which have declined in recent years as the amount and condition of their habitat have declined. Land managers and private landowners need guidance on how to efficiently and accurately quantify the condition and wildlife habitat value of the pine stands that they manage. Here we provide a set of rapid assessment metrics, based on NatureServe’s ecological integrity assessment (EIA) method, to (a) identify exemplary tracts that provide the best habitat for key wildlife species, and (b) monitor restoration efforts to assess progress toward the improved quality of existing tracts. To ensure an ecologically appropriate scaling of metrics, we distinguished six types of shortleaf pine–oak woodland: A.—Interior Highlands shortleaf pine–oak (including A.1—shortleaf pine–oak forest and woodlands; A.2—shortleaf pine–bluestem woodlands); B—montane longleaf pine–shortleaf pine woodlands; C—southern Appalachian pine–oak woodlands; D—West Gulf coastal plain shortleaf pine–oak woodlands; and E—southeast coastal plain and Piedmont shortleaf pine–oak woodlands. We relied on a narrative conceptual model and peer review-based indicator selection to identify a core set of 15 stand-level metrics (two were optional). Individual assessment points (thresholds) and ratings (Excellent, Good, Fair, and Poor) were developed that were sensitive to the distinct attributes of each of the five shortleaf pine–oak and Appalachian pine–oak types. Values for the metrics can all be collected using rapid field methods, such as using basal area prisms and ocular (visual) estimates of cover. Protocols for the consistent application of these EIA methods are provided. A case study is presented from the Cherokee National Forest in Tennessee. These methods provide improved and rapid EIA metrics for all shortleaf pine–oak ecosystems in the southeastern US to help guide conservation-minded landowners in assessing the biodiversity and priority wildlife values of shortleaf pine–oak and southern Appalachian pine–oak ecosystems.

Perceived Stress as a Pathway for the Relationship Between Neighborhood Factors and Glycemic Control in Adults With Diabetes

Purpose Neighborhood factors such as crime, discrimination, and violence are increasingly recognized as correlates of poor glycemic control. However, pathways for these relationships are unclear. This study examined stress and self-efficacy as potential pathways for the relationship between neighborhood factors and glycemic control in adults with type 2 diabetes. Design Cross-sectional study. Setting Two primary care clinics in southeastern US. Participants 615 adults aged 18 years and older. Measures Validated measures were used to capture neighborhood factors, stress, and self-efficacy, while hemoglobin A1c (HbA1c) was abstracted from the electronic health record. Analysis Path analysis was used to investigate direct and indirect relationships between neighborhood factors, stress, self-efficacy, and glycemic control. Results In the final model, violence (r = .17, P = .024), discrimination (r = .46, P < .001), and crime (r = .36, P = .046) were directly associated with higher perceived stress. Stress (r = −.5, P < .001) was directly associated with lower self-efficacy. Self-efficacy was directly associated with better general diet (r = .12, P < .001), better specific diet (r = .04, P < .001), more exercise (r = .08, P < .001), and lower HbA1c (r = −.11, P < .001). Stress (r = .05, P < .001), crime (r = .20, P < .001), and discrimination (r = .08, P < .001) were indirectly associated with higher HbA1c. Conclusion Stress and self-efficacy are potential pathways for the relationship between neighborhood factors like violence, discrimination, and crime and glycemic control. Interventions aimed at mitigating stress and improving self-efficacy may improve self-care behaviors and glycemic control.

Estimating the Risk of Extreme Wind Gusts in Tropical Cyclones Using Idealized Large-Eddy Simulations and a Statistical-Dynamical Model

Recent studies have shown that extreme wind gusts are ubiquitous within the eyewall of intense tropical cyclones (TCs). These gusts pose a substantial hazard to human life and property, but both the short-term (i.e., during the passage of a single TC) and long-term (over many years) risk of encountering such a gust at a given location is poorly understood. Here, simulated tower data from large-eddy simulations of idealized TCs in a quiescent (i.e., no mean flow or vertical wind shear) environment are used to estimate these risks for the offshore region of the United States. For both a category 5 and category 3 TC, there is a radial region where nearly all simulated towers experience near-surface (the lowest 200 m) 3-s gusts exceeding 70 m s−1 within a 10-minute period; on average, these towers respectively sample peak 3-s gusts of 110 and 80 m s−1. Analysis of an observational dropsonde database supports the idealized simulations, and indicates that offshore structures (such as wind turbines) in the eyewall of a major hurricane are likely to encounter damaging wind speeds. This result is then incorporated into an estimate of the long-term risk, using analyses of the return period for major hurricanes from both a best-track database and a statistical-dynamical model forced by reanalysis. For much of the nearshore region of the Gulf of Mexico and southeastern US coasts, this analysis yields an estimate of a 30-60% probability of any given point experiencing at least one 70 m s−1 gust within a 30-year period.