Predicting the Storm Surge Threat of Hurricane Sandy with the National Weather Service SLOSH Model

Numerical simulations of the storm tide that flooded the US Atlantic coastline during Hurricane Sandy (2012) are carried out using the National Weather Service (NWS) Sea Lakes and Overland Surges from Hurricanes (SLOSH) storm surge prediction model to quantify its ability to replicate the height, timing, evolution and extent of the water that was driven ashore by this large, destructive storm. Recent upgrades to the numerical model, including the incorporation of astronomical tides, are described and simulations with and without these upgrades are contrasted to assess their contributions to the increase in forecast accuracy. It is shown, through comprehensive verifications of SLOSH simulation results against peak water surface elevations measured at the National Oceanic and Atmospheric Administration (NOAA) tide gauge stations, by storm surge sensors deployed and hundreds of high water marks collected by the U.S. Geological Survey (USGS), that the SLOSH-simulated water levels at 71% (89%) of the data measurement locations have less than 20% (30%) relative error. The RMS error between observed and modeled peak water levels is 0.47 m. In addition, the model’s extreme computational efficiency enables it to run large, automated ensembles of predictions in real-time to account for the high variability that can occur in tropical cyclone forecasts, thus furnishing a range of values for the predicted storm surge and inundation threat

Guest Editors\u27 Introduction: Best of RESPECT, Part 2

The guest editors introduce best papers on broadening participation in computing from the RESPECT\u2715 conference. The five articles presented here are part two of a two-part series representing research on broadening participation in computing. These articles study participation in intersectional ways, through the perceptions and experiences of African-American middle school girls, the sense of belonging in computing for LGBTQ students, the impact of a STEM scholarship and community development program for low-income and first-generation college students, a leadership development program, and how African-American women individually take leadership to enable their success in computing

Prospectus, November 21, 1988

https://spark.parkland.edu/prospectus_1988/1029/thumbnail.jp

Prospectus, December 15, 1988

https://spark.parkland.edu/prospectus_1988/1032/thumbnail.jp

Inconsistent relationships between area, heterogeneity and plant species richness in temperate farmed landscapes

Relationships between area, heterogeneity and species richness are fundamental concepts in ecology yet questions remain about how area and heterogeneity trade-off (AHTO) to constrain biodiversity. Although there is growing evidence for unimodal heterogeneity diversity relationships (HDR’s) and an AHTO, tests of the concept and consequences for species richness across a landscape-scale gradient of human-modified ecosystems are rare. Using data from a national (Wales) field survey we analysed relationships between environmental heterogeneity and plant species richness (α and γ). We used ordination to produce a composite metric of heterogeneity and compared this to commonly used metrics. We used niche hypervolumes to categorise the breadth of plant species’ ecological preferences and analysed relationships between species richness, niche width and heterogeneity. The HDR was unimodal with α diversity at the smallest scale and positive with α and γ diversity (non-linear) at the 1 km scale although in low intensity landscapes the HDR with γ diversity was unimodal. There was a unimodal relationship between habitat diversity and γ diversity. Land use intensity was unimodally related to diversity. There were significant interactions between niche width and heterogeneity. Richness of broad niche species increased with heterogeneity with flattening of the curve at higher levels. Narrow niche species were rare and mostly unresponsive. The expected decline in narrow niche species with increasing heterogeneity was not found although they did decline with land-use intensity. Using a unique dataset, an analysis of a large-scale mosaic of ecosystems found that the shape of the HDR varies with land use intensity, the heterogeneity metric, spatial scale, diversity type and niche width. Although heterogeneity can increase species richness, there may be trade-offs at higher heterogeneity. A fundamental constraint on realising the benefit of heterogeneity is the low availability of narrower niche species in local species pools in modified landscapes

Phenotype execution and modeling architecture to support disease surveillance and real-world evidence studies: English sentinel network evaluation

Objective To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Quality Language (CQL) and intensional Systematised Nomenclature of Medicine (SNOMED) Clinical Terms (CT) Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor, and surveillance phenotypes. Method We curated 3 phenotypes: Type 2 diabetes mellitus (T2DM), excessive alcohol use, and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED’s hierarchy and expression constraint language, and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. We assessed our new approach against published desiderata for phenotypes. Results The T2DM phenotype could be defined as 2 intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26-38) from 0.95 cases to 1.11 cases per 100 000 people. Conclusions Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy. Our new process fulfilled a greater number of phenotype desiderata than the one that we had used previously, mostly in the modeling domain. More work is needed to implement that sharing and warehousing domains

Hepatitis A vaccination coverage among people with chronic liver disease in England (HEALD): protocol for a retrospective cohort study

Background: Hepatitis A outbreaks in the United Kingdom are uncommon. Most people develop mild to moderate symptoms that resolve, without sequelae, within months. However, in high-risk groups, including those with underlying chronic liver disease (CLD), hepatitis A infection can be severe, with a higher risk of mortality and morbidity. The Health Security Agency and the National Institute of Health and Care Excellence recommend preexposure hepatitis A vaccination given in 2 doses to people with CLD, regardless of its cause. There are currently no published reports of vaccination coverage for people with CLD in England or internationally. Objective: This study aims to describe hepatitis A vaccination coverage in adults with CLD in a UK primary care setting and compare liver disease etiology, sociodemographic characteristics, and comorbidities in people who are and are not exposed to the hepatitis A vaccine. Methods: We will conduct a retrospective cohort study with data from the Primary Care Sentinel Cohort of the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub database, which is nationally representative of the English population. We will include people aged 18 years and older who have been registered in general practices in the Research and Surveillance Centre network and have a record of CLD between January 1, 2012, and December 31, 2022, including those with alcohol-related liver disease, chronic hepatitis B, chronic hepatitis C, nonalcohol fatty liver disease, Wilson disease, hemochromatosis, and autoimmune hepatitis. We will carefully curate variables using the Systematized Nomenclature of Medicine Clinical Terms. We will report the sociodemographic characteristics of those who are vaccinated. These include age, gender, ethnicity, population density, region, socioeconomic status (measured using the index of multiple deprivation), obesity, alcohol consumption, and smoking. Hepatitis A vaccination coverage for 1 and 2 doses will be calculated using an estimate of the CLD population as the denominator. We will analyze the baseline characteristics using descriptive statistics, including measures of dispersion. Pairwise comparisons of case-mix characteristics, comorbidities, and complications will be reported according to vaccination status. A multistate survival model will be fitted to estimate the transition probabilities among four states: (1) diagnosed with CLD, (2) first dose of hepatitis A vaccination, (3) second dose of hepatitis A vaccination, and (4) death. This will identify any potential disparities in how people with CLD get vaccinated. Results: The Research and Surveillance Centre population comprises over 8 million people. The reported incidence of CLD is 20.7 cases per 100,000. International estimates of hepatitis A vaccine coverage vary between 10% and 50% in this group. Conclusions: This study will describe the uptake of the hepatitis A vaccine in people with CLD and report any disparities or differences in the characteristics of the vaccinated population. International Registered Report Identifier (IRRID): PRR1-10.2196/5186

AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: the RAVEN cohort study

Objectives Despite being prioritized during initial COVID-19 vaccine rollout, vulnerable individuals at high risk of severe COVID-19 (hospitalization, intensive care unit admission, or death) remain underrepresented in vaccine effectiveness (VE) studies. The RAVEN cohort study (NCT05047822) assessed AZD1222 (ChAdOx1 nCov-19) two-dose primary series VE in vulnerable populations. Methods Using the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub, linked to secondary care, death registration, and COVID-19 datasets in England, COVID-19 outcomes in 2021 were compared in vaccinated and unvaccinated individuals matched on age, sex, region, and multimorbidity. Results Over 4.5 million AZD1222 recipients were matched (mean follow-up ∼5 months); 68% were ≥50 years, 57% had high multimorbidity. Overall, high VE against severe COVID-19 was demonstrated, with lower VE observed in vulnerable populations. VE against hospitalization was higher in the lowest multimorbidity quartile (91.1%; 95% CI: 90.1, 92.0) than the highest quartile (80.4%; 79.7, 81.1), and among individuals ≥65 years, higher in the ‘fit’ (86.2%; 84.5, 87.6) than the frailest (71.8%; 69.3, 74.2). VE against hospitalization was lowest in immunosuppressed individuals (64.6%; 60.7, 68.1). Conclusions Based on integrated and comprehensive UK health data, overall population-level VE with AZD1222 was high. VEs were notably lower in vulnerable groups, particularly the immunosuppressed

Can understanding reward help illuminate anhedonia?

Purpose of review: The goal of this paper is to examine how reward processing might help us understand the symptom of anhedonia. Recent findings: There are extensive reviews exploring the relationship between responses to rewarding stimuli and depression. These often include a discussion on anhedonia and how this might be underpinned in particular by dysfunctional reward processing. However, there is no specific consensus on whether studies to date have adequately examined the various sub-components of reward processing or how these might relate in turn to various aspects of anhedonia symptoms. Summary: The approach to understanding the symptom of anhedonia should be to examine all the sub-components of reward processing at the subjective and objective behavioural and neural level, with well validated tasks that can be replicated. Investigating real life experiences of anhedonia and how theses might be predicted by objective lab measures is also needed in future research