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BackgroundA critical aspect of clinical and translational science (CTS) is interdisciplinary and collaborative research, which increasingly requires a wide range of computational and human resources. However, few studies have systematically analyzed such resource needs of CTS researchers. ObjectiveTo improve our understanding of CTS researchers’ needs for computational and human resources in order to build useful and useable supporting informatics tools. MethodsWe conducted semistructured interviews of 30 CTS researchers from the University of Michigan, followed by qualitative analysis of the interview transcripts. ResultsThe analysis identified three recurring themes: the need for the federation of information, the need to address information overload, and the need to humanize computing, including strong and well-informed views about the use of social networking tools for research collaboration. These findings helped us to narrow down the available design choices for assisting CTS researchers, and helped to identify potential deficiencies of well-known theoretical frameworks used to guide our study, with suggestions for future remedies. ConclusionsThe user needs identified through the study, along with concrete design suggestions, provided key design, methodological, and theoretical insights, which are being used to guide the design and development of a CTS resource portal. The results and interview instrument should be useful to other institutions with Clinical and Translational Science Awards that face similar challenges related to helping CTS researchers make more effective use of computational and human resources.

In an increasing number of countries, the Special Educational Needs Coordinator (SENCo) plays a key role in implementing inclusive provision for students with special educational needs. Existing literature on SENCos mainly focuses on the nature and enactment of the role, with few investigating SENCo identities. Hence, the study presented in this article aimed to navigate how personal and contextual factors influence SENCo identity. Utilising a qualitative interpretive case study approach, multiple sources of data were gathered from five primary school SENCos in Auckland, New Zealand, through semi-structured interviews, work shadowing and school documents. The findings revealed how SENCo identity was shaped by personal factors, including motivation/commitment and expertise/experience; and contextual factors such as the organisation of the SENCo role, support from senior leaders and other stakeholders, and national policies regarding the SENCo role. Drawing on the findings, we argue that formal recognition and targeted funding of the SENCo role by the government are vital for constructing and maintaining a strong SENCo identity. At the same time, it is important to sustain individual school autonomy and flexibility regarding the structural organisation of the SENCo role.

Background: Undergraduate research journals are a popular mechanism for inducting students into research, communication, and publication facets of academia. A thematic review of 17 review papers found little evidence for journal impact. Methods: A scoping review identified 91 journals. A systematic search identified the journal website, its International Standard Serial Number (if any), its citation rate on Google Scholar, its start year and end year (if applicable). Results: Seventy-five journals had both a Google Scholar h-index and a discoverable start year. Sixty-eight had been cited one or more times. The median h-index was 2, mode was h = 1, and the average h-index = 4.38. Correlation with start year was not statistically significant, neither was content field of journals. Conclusions: Surprisingly, almost all currently published journals have been cited at least once, showing that undergraduate research journals have some impact on the scholarly world. Further analyses are suggested to examine career impact of publication on students and faculty.

In recent years, “smart city” information and communication technologies have proliferated. For local government agencies, procuring and introducing these technologies offers the possibility to manage infrastructure assets more effectively, plan for preventive maintenance, and disseminate schedules and information about transit and other services. Many of these technologies are deployed by private firms in the context of local regulations and government-sponsored incentives. In the transportation sector, examples of “smart city” technology services provided by private firms include: electric vehicle (EV) chargers, micro-mobility (e.g., scooter and bike rentals), and transportation network company (TNC) services, such as Uber and Lyft. To understand variation in how private sector smart city transportation technologies are deployed across California, researchers at UC Berkeley webscraped and cross verified data on EV chargers, Uber services, and micro-mobility. EV charger data was obtained from the Department of Energy, and Uber and micromobility access data came from vendor websites.

Beginning the week of March 20–26, 2022, the Omicron BA.2 variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating variant in the United States, accounting for >50% of sequenced isolates.* Data from the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) were analyzed to describe recent COVID-19–associated hospitalization rates among adults aged ≥18 years during the period coinciding with BA.2 predominance (BA.2 period [Omicron BA.2 and BA.2.12.1; March 20–May 31, 2022]). Weekly hospitalization rates (hospitalizations per 100,000 population) among adults aged ≥65 years increased threefold, from 6.9 (week ending April 2, 2022) to 27.6 (week ending May 28, 2022); hospitalization rates in adults aged 18–49 and 50–64 years both increased 1.7-fold during the same time interval. Hospitalization rates among unvaccinated adults were 3.4 times as high as those among vaccinated adults. Among hospitalized nonpregnant patients in this same period, 39.1% had received a primary vaccination series and 1 booster or additional dose; 5.0% had received a primary series and ≥2 boosters or additional doses. All adults should stay up to date† with COVID-19 vaccination, and multiple nonpharmaceutical and medical prevention measures should be used to protect those at high risk for severe COVID-19 illness, irrespective of vaccination status§ (1).Beginning the week of March 20–26, 2022, the Omicron BA.2 variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating variant in the United States, accounting for >50% of sequenced isolates.* Data from the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET) were analyzed to describe recent COVID-19–associated hospitalization rates among adults aged ≥18 years during the period coinciding with BA.2 predominance (BA.2 period [Omicron BA.2 and BA.2.12.1; March 20–May 31, 2022]). Weekly hospitalization rates (hospitalizations per 100,000 population) among adults aged ≥65 years increased threefold, from 6.9 (week ending April 2, 2022) to 27.6 (week ending May 28, 2022); hospitalization rates in adults aged 18–49 and 50–64 years both increased 1.7-fold during the same time interval. Hospitalization rates among unvaccinated adults were 3.4 times as high as those among vaccinated adults. Among hospitalized nonpregnant patients in this same period, 39.1% had received a primary vaccination series and 1 booster or additional dose; 5.0% had received a primary series and ≥2 boosters or additional doses. All adults should stay up to date† with COVID-19 vaccination, and multiple nonpharmaceutical and medical prevention measures should be used to protect those at high risk for severe COVID-19 illness, irrespective of vaccination status§ (1).

Groundwater is by far the largest unfrozen freshwater resource on the planet. It plays a critical role as the bottom of the hydrologic cycle, redistributing water in the subsurface and supporting plants and surface water bodies. However, groundwater has historically been excluded or greatly simplified in global models. In recent years, there has been an international push to develop global scale groundwater modeling and analysis. This progress has provided some critical first steps. Still, much additional work will be needed to achieve a consistent global groundwater framework that interacts seamlessly with observational datasets and other earth system and global circulation models. Here we outline a vision for a global groundwater platform for groundwater monitoring and prediction and identify the key technological and data challenges that are currently limiting progress. Any global platform of this type must be interdisciplinary and cannot be achieved by the groundwater modeling community in isolation. Therefore, we also provide a high-level overview of the groundwater system, approaches to groundwater modeling and the current state of global groundwater representations, such that readers of all backgrounds can engage in this challenge.

In recent years, “smart city” technologies have emerged that allow cities, counties, and other agencies to manage their infrastructure assets more effectively, make their services more accessible to the public, and allow citizens to interface with new web-and mobile-based alternative service providers. This project developed an innovative user-friendly web interface for local and state policymakers that tracks and displays information on the adoption of such technologies in California across the policing, transportation, and water and wastewater sectors for a comprehensive set of local service providers: connectedgov.berkeley.edu. Contrary to conventional smart city indices, our platform allows users to view rates of adoption in maps that attribute adoption to the local public agencies or service providers actually procuring or regulating the technologies in question. Users can construct indices or view technologies one by one. Users can also explore the relationship between technology adoption and local service area conditions and demographics, or download the raw data and scripts used to collect it. This report illustrates the utility of the data we have collected, and the analytics one can perform using our web interface through an analysis of the rollout of three technologies in the transportation sector: electric vehicle (EV) chargers, transportation network company (TNC) service areas, and micromobility services across California.

BackgroundThe COVID-19 pandemic has caused substantial morbidity and mortality.ObjectiveTo describe monthly clinical trends among adults hospitalized with COVID-19.DesignPooled cross-sectional study.Setting99 counties in 14 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET).PatientsU.S. adults (aged ≥18 years) hospitalized with laboratory-confirmed COVID-19 during 1 March to 31 December 2020.MeasurementsMonthly hospitalizations, intensive care unit (ICU) admissions, and in-hospital death rates per 100 000 persons in the population; monthly trends in weighted percentages of interventions, including ICU admission, mechanical ventilation, and vasopressor use, among an age- and site-stratified random sample of hospitalized case patients.ResultsAmong 116 743 hospitalized adults with COVID-19, the median age was 62 years, 50.7% were male, and 40.8% were non-Hispanic White. Monthly rates of hospitalization (105.3 per 100 000 persons), ICU admission (20.2 per 100 000 persons), and death (11.7 per 100 000 persons) peaked during December 2020. Rates of all 3 outcomes were highest among adults aged 65 years or older, males, and Hispanic or non-Hispanic Black persons. Among 18 508 sampled hospitalized adults, use of remdesivir and systemic corticosteroids increased from 1.7% and 18.9%, respectively, in March to 53.8% and 74.2%, respectively, in December. Frequency of ICU admission, mechanical ventilation, and vasopressor use decreased from March (37.8%, 27.8%, and 22.7%, respectively) to December (20.5%, 12.3%, and 12.8%, respectively); use of noninvasive respiratory support increased from March to December.LimitationCOVID-NET covers approximately 10% of the U.S. population; findings may not be generalizable to the entire country.ConclusionRates of COVID-19-associated hospitalization, ICU admission, and death were highest in December 2020, corresponding with the third peak of the U.S. pandemic. The frequency of intensive interventions for management of hospitalized patients decreased over time. These data provide a longitudinal assessment of clinical trends among adults hospitalized with COVID-19 before widespread implementation of COVID-19 vaccines.Primary funding sourceCenters for Disease Control and Prevention.

BackgroundCurrently, the United States has the largest number of reported coronavirus disease 2019 (COVID-19) cases and deaths globally. Using a geographically diverse surveillance network, we describe risk factors for severe outcomes among adults hospitalized with COVID-19.MethodsWe analyzed data from 2491 adults hospitalized with laboratory-confirmed COVID-19 between 1 March-2 May 2020, as identified through the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network, which comprises 154 acute-care hospitals in 74 counties in 13 states. We used multivariable analyses to assess associations between age, sex, race and ethnicity, and underlying conditions with intensive care unit (ICU) admission and in-hospital mortality.ResultsThe data show that 92% of patients had ≥1 underlying condition; 32% required ICU admission; 19% required invasive mechanical ventilation; and 17% died. Independent factors associated with ICU admission included ages 50-64, 65-74, 75-84, and ≥85 years versus 18-39 years (adjusted risk ratios [aRRs], 1.53, 1.65, 1.84, and 1.43, respectively); male sex (aRR, 1.34); obesity (aRR, 1.31); immunosuppression (aRR, 1.29); and diabetes (aRR, 1.13). Independent factors associated with in-hospital mortality included ages 50-64, 65-74, 75-84, and ≥ 85 years versus 18-39 years (aRRs, 3.11, 5.77, 7.67, and 10.98, respectively); male sex (aRR, 1.30); immunosuppression (aRR, 1.39); renal disease (aRR, 1.33); chronic lung disease (aRR 1.31); cardiovascular disease (aRR, 1.28); neurologic disorders (aRR, 1.25); and diabetes (aRR, 1.19).ConclusionsIn-hospital mortality increased markedly with increasing age. Aggressive implementation of prevention strategies, including social distancing and rigorous hand hygiene, may benefit the population as a whole, as well as those at highest risk for COVID-19-related complications.

Although COVID-19-associated hospitalizations and deaths have occurred more frequently in adults,† COVID-19 can also lead to severe outcomes in children and adolescents (1,2). Schools are opening for in-person learning, and many prekindergarten children are returning to early care and education programs during a time when the number of COVID-19 cases caused by the highly transmissible B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, is increasing.§ Therefore, it is important to monitor indicators of severe COVID-19 among children and adolescents. This analysis uses Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET)¶ data to describe COVID-19-associated hospitalizations among U.S. children and adolescents aged 0-17 years. During March 1, 2020-August 14, 2021, the cumulative incidence of COVID-19-associated hospitalizations was 49.7 per 100,000 children and adolescents. The weekly COVID-19-associated hospitalization rate per 100,000 children and adolescents during the week ending August 14, 2021 (1.4) was nearly five times the rate during the week ending June 26, 2021 (0.3); among children aged 0-4 years, the weekly hospitalization rate during the week ending August 14, 2021, was nearly 10 times that during the week ending June 26, 2021.** During June 20-July 31, 2021, the hospitalization rate among unvaccinated adolescents (aged 12-17 years) was 10.1 times higher than that among fully vaccinated adolescents. Among all hospitalized children and adolescents with COVID-19, the proportions with indicators of severe disease (such as intensive care unit [ICU] admission) after the Delta variant became predominant (June 20-July 31, 2021) were similar to those earlier in the pandemic (March 1, 2020-June 19, 2021). Implementation of preventive measures to reduce transmission and severe outcomes in children is critical, including vaccination of eligible persons, universal mask wearing in schools, recommended mask wearing by persons aged ≥2 years in other indoor public spaces and child care centers,†† and quarantining as recommended after exposure to persons with COVID-19.§§.

Continental-to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth system above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths, and limitations, so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities, and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when, or where large-scale models achieve their purpose or where opportunities for improvements exist so that such models better achieve their purpose. We suggest that reproducing the spatiotemporal details of regional-scale models and matching local data are not relevant goals. Instead, it is important to decide on reasonable model expectations regarding when a large-scale model is performing "well enough"in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria are quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental-to global-scale models. We describe current modeling strategies and evaluation practices, and we subsequently discuss the value of three evaluation strategies: (1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation), (2) comparing several models with each other with or without reference to actual observations (model-based evaluation), and (3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning, and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models, thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

Twice-exceptional (2e) students face many barriers to learning opportunities due to their combinations of giftedness and learning disabilities. If 2e students are referred to special education teachers such as resource teachers of learning and behaviour (RTLB), challenges may be encountered when RTLB lack knowledge of twice-exceptionality. This article provides insight into the barriers RTLB face when identifying 2e students, and how RTLB provide learning programmes that promote and strengthen 2e students' talents while scaffolding support for their learning disabilities. It draws upon a small exploratory qualitative study of RTLB knowledge of 2e concepts, how they identified these students, and the common intervention approaches used when working with 2e students.

A growing number of countries have implemented the role of Special Educational Needs Coordinator (SENCo) as a strategy for providing quality inclusive education. While studies have examined general education teachers and/or special education teachers' identities in inclusive educational settings, little research has investigated SENCos' identities. Even fewer studies have examined SENCo identity through the lens of emotion. Hence, the aim of this study was to develop an in-depth understanding of how emotions contribute to SENCo identity construction. Adopting a qualitative multiple case study approach, data were collected from five primary school SENCos in Auckland, New Zealand, via semi-structured interviews, work shadowing and school documents. The findings showed that SENCos, despite dealing with a range of emotions from passion to frustration, all saw themselves as being advocates, problem solvers, learners, collaborators and fighters for children with special educational needs. Drawing on the findings, it is argued that emotions form an indispensable part of SENCo identity and also act as a vital means through which SENCo identity is constructed and enacted. Implications for policy and practice are suggested to inform the recruitment of SENCos and provide SENCos emotional support.

Most reported cases of coronavirus disease 2019 (COVID-19) in children aged

Our purpose is to provide an exploratory statistical representation of initial teacher education as a complex system comprised of dynamic influential elements. More precisely, we reveal what the system looks like for differently-positioned teacher education stakeholders based on our framework for gathering, statistically analyzing, and graphically representing the results of a unique exercise wherein the participants literally mapped the system as they perceived it. Through an iterative series of inter-related studies employing cluster analysis and multidimensional scaling procedures, we demonstrate how initial teacher education may be represented as a complex system comprised of interactive agents and attributes whose perceived relationships are a function of nested stakeholder-dependent simplex systems. Furthermore, we illustrate how certain propositions of complexity theory, such as boundaries, heterogeneity, multidimensionality and emergence, may be investigated and represented quantitatively.