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Colleges and universities around the world engaged diverse strategies during the COVID-19 pandemic. Baylor University, a community of ˜22,700 individuals, was one of the institutions which resumed and sustained operations. The key strategy was establishment of multidisciplinary teams to develop mitigation strategies and priority areas for action. This population-based team approach along with implementation of a “Swiss Cheese” risk mitigation model allowed small clusters to be rapidly addressed through testing, surveillance, tracing, isolation, and quarantine. These efforts were supported by health protocols including face coverings, social distancing, and compliance monitoring. As a result, activities were sustained from 1 August to 8 December 2020. There were 62,970 COVID-19 tests conducted with 1,435 people testing positive for a positivity rate of 2.28%. A total of 1,670 COVID-19 cases were identified with 235 self-reports. The mean number of tests per week was 3,500 with approximately 80 of these positive (11 per day). More than 60 student tracers were trained with over 120 personnel available to contact trace, at a ratio of one per 400 university members. The successes and lessons learned provide a framework and pathway for similar institutions to mitigate the ongoing impacts of COVID-19 and sustain operations during a global pandemic.
The past few decades have seen the burgeoning of wide-field, high-cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy; however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO) whose primary science objective is the optical follow-up of gravitational wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near-real time to fully exploit the time domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this ‘off-the-shelf’ pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to subpixel levels, and that measured L-band photometries are accurate to $\sim50$ mmag at $m_L\sim16$ and $\sim200$ mmag at $m_L\sim18$. These values compare favourably to those obtained using GOTO’s primary, in-house pipeline, gotophoto, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic ‘obs package’ that others can build upon, should they wish to use the LSST Science Pipelines to process data from other facilities.
New technologies have always brought new challenges even as they solve old problems. The 21st century is seeing a revolution in scientific, technical and medical publishing. The stage was set a few years ago, when publishers began migrating their content to the online environment, in parallel with continued print publication, first journals, then books. Initially, the premise was still that the print product was primary and the electronic version just a way of reaching a larger audience. As new functionality was introduced, expectations were raised and content now has to be much more than an electronic version of a printed page: it must include easy cross-referencing both internally within a document and to external sources, without regard to the owner or publisher of those sources; it must accommodate audiovisual material; and all this must be done rapidly and seamlessly.
But the target has already moved further away: the real challenge now is to deliver the interactivity that will be expected from the generation that communicates through MySpace and Facebook. How do we maintain the status of the textbook when students look for answers on Wikipedia? Who will read a journal paper describing a particular gene when they can log into GenBank? What is the role of the clinical reference work when doctors carry PDAs loaded with guidelines and treatment algorithms? The publishing house that successfully answers these questions will be the one that survives to face the challenges of the next decade.
Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
Iron-rich meteorites are significantly underrepresented in collection statistics from Antarctica. This has led to a hypothesis that there is a sparse layer of iron-rich meteorites hidden below the surface of the ice, thereby explaining the apparent shortfall. As standard Antarctic meteorite collecting techniques rely upon a visual surface search approach, the need has thus arisen to develop a system that can detect iron objects under a few tens of centimetres of ice, where the expected number density is of the order one per square kilometre. To help answer this hypothesis, a large-scale pulse induction metal detector array has been constructed for deployment in Antarctica. The metal detector array is 6 m wide, able to travel at 15 km h-1 and can scan 1 km2 in ~11 hours. This paper details the construction of the metal detector system with respect to design criteria, notably the ruggedization of the system for Antarctic deployment. Some preliminary results from UK and Antarctic testing are presented. We show that the system performs as specified and should reach the pre-agreed target of the detection of a 100 g iron meteorite at 300 mm when deployed in Antarctica.
Knowledge of the intra-individual spatial and regional distribution of intestinal microbial populations is essential to understand gut host–microbial interactions. In this study, we performed a compositional analysis of luminal and mucosal samples from the small and large intestine of four organ donors by 16S rRNA amplicon sequencing and high-throughput quantitative polymerase chain reaction. Since the human microbiota is subject to selection pressure at lower taxonomic levels, we isolated over 400 bacterial strains and investigated strain-level variation of 11 Lactobacillus rhamnosus from different intestinal regions. Results substantiate reported inter-individual variability as well as intra-individual differences along the gastrointestinal tract. Although the luminal and mucosal-associated communities were similar within individuals, relative abundance reflected the donors’ demographic and potential pathologies. The total bacterial load of all donors increased from small intestine to colon, while Bifidobacterium was in greater abundance in the small intestine. Comparative genomic analysis of L. rhamnosus showed the strains segregated into two distinct clusters and identified no features specific to location. Analysis revealed genetic differences for exopolysaccharide production, carbohydrate utilization, pilus formation and vitamin K biosynthesis between clusters. This study contributes to the understanding of niche-specific microbial communities, encouraging subsequent studies to better understand microbial signatures at lower taxonomic levels.
The Late Formative period immediately precedes the emergence of Tiwanaku, one of the earliest South American states, yet it is one of the most poorly understood periods in the southern Lake Titicaca Basin (Bolivia). In this article, we refine the ceramic chronology of this period with large sets of dates from eight sites, focusing on temporal inflection points in decorated ceramic styles. These points, estimated here by Bayesian models, index specific moments of change: (1) cal AD 120 (60–170, 95% probability): the first deposition of Kalasasaya red-rimmed and zonally incised styles; (2) cal AD 240 (190–340, 95% probability): a tentative estimate of the final deposition of Kalasasaya zonally incised vessels; (3) cal AD 420 (380–470, 95% probability): the final deposition of Kalasasaya red-rimmed vessels; and (4) cal AD 590 (500–660, 95% probability): the first deposition of Tiwanaku Redwares. These four modeled boundaries anchor an updated Late Formative chronology, which includes the Initial Late Formative phase, a newly identified decorative hiatus between the Middle and Late Formative periods. The models place Qeya and transitional vessels between inflection points 3 and 4 based on regionally consistent stratigraphic sequences. This more precise chronology will enable researchers to explore the trajectories of other contemporary shifts during this crucial period in Lake Titicaca Basin's prehistory.
OBJECTIVES/SPECIFIC AIMS: Background: The importance of engaging community in research and fostering community-academic research partnerships is increasingly acknowledged by Clinical and Translational Science Award (CTSA) institutes. However, forming and maintaining such collaborations is often hampered by numerous challenges. It is critical to investigate the barriers to effective community-academic partnerships and to develop novel approaches to overcome these barriers. Objective: To explore community and academic perspectives of the challenges faced by community-academic research partnerships and potential solutions to these identified challenges. METHODS/STUDY POPULATION: Methods: In an effort to explore creative approaches to address these issues, the Community Engagement Program at the Michigan Institute for Clinical & Health Research (MICHR), the CTSA site that serves Michigan, hosted a retreat to elicit the input of community members and academics from across the state. There was a mix of participants ranging from those with established community-academic partnerships to others who were new to community-engaged research and in early stages of forming partnerships. At the retreat, attendees were randomly divided into groups and asked to answer the specific question, “What are your barriers to partnering in research?” After each group identified a set of barriers and reported their findings to the entire room, attendees were asked to work again in their small groups to discuss potential solutions to these barriers. Ideas for solutions were also shared with the entire room. As part of the process of brainstorming about these questions, attendees were asked to document their ideas --- for both barriers and solutions --- on post-it notes which were then grouped by category. Artifacts from the retreat were saved digitally and transcripts made from these records. The findings were then analyzed to identify common themes. RESULTS/ANTICIPATED RESULTS: Results: Eighty-six participants attended the retreat from across the state of Michigan. Forty-three represented community organizations that focus on addressing a wide array of social determinants of health issues. The remaining forty-three participants represented various academic institutions. The most frequently mentioned challenges to community-academic partnerships were related to communication and relationship building. To overcome barriers in these areas, participants noted that it is critical to collaboratively and explicitly identify shared goals, values and norms in the early stages of partnership development. This was closely linked to the need for additional funding to help foster and strengthen relationships by allowing partners to spend time together to both work and socialize informally, preferably in face-to-face settings. These were deemed crucial for building trust and common ground. In addition, more equitable funding and role distribution --- including shared leadership and governance of research projects between community and academia--- that recognizes and supports the true costs of involvement in research for community members was viewed as important. Other frequently noted issues on the part of community members were the need for greater respect for community partners and for more training opportunities to build capacity within communities to participate in research. Participants from academic institutions emphasized that the current requirements and timeline for promotion in academia make it harder for them to participate in community-engaged research, especially as early career researchers. They maintained that wider recognition of the value of community-engaged research is necessary and that this requires the support of home departments. Finally, participants underscored the importance of building infrastructure to better connect potential partners from the community and academia by making it easier to identify common interests and reciprocal strengths. DISCUSSION/SIGNIFICANCE OF IMPACT: Conclusion: The problems faced by community-academic partnerships may be alleviated by working with community and academic members to identify potential solutions. Further work is needed to systematically examine barriers and the efficacy of solutions to enhance community-academic partnerships. Acknowledgements: We thank all attendees of the MICHR Community Engagement retreat for their participation in this activity that explored barriers to effective community-academic partnerships. Their honest and frank feedback was essential to broaching sensitive topics related to partnership development, and to identify realistic and practical solutions. We also thank all members of the planning committee and our colleagues in the Community Engagement Program for their work on bringing together community and academic members for this retreat. This project was supported by grant number UL1TR002240 from the National Center for Advancing Translational Sciences (NCATS).
Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.
We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.
Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.
Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.
While learning, students make a lot of errors, so an important goal of education research is to discover the most effective techniques for correcting their errors. In this chapter, we discuss the methods to study error correction, describe empirical evidence to highlight what works best, and offer advice for educators on how to correct students' errors.
Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.
To evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics.
Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit.
A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15–3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98–10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7–15) (OR = 0.96; 95% CI = 0.56–1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26–0.97).
The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.
Declaration of interest
Drs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the original sponsor of the development of the PHQ-9, which is now in the public domain. Dr Chan is a steering committee member or consultant of Astra Zeneca, Bayer, Lilly, MSD and Pfizer. She has received sponsorships and honorarium for giving lectures and providing consultancy and her affiliated institution has received research grants from these companies. Dr Hegerl declares that within the past 3 years, he was an advisory board member for Lundbeck, Servier and Otsuka Pharma; a consultant for Bayer Pharma; and a speaker for Medice Arzneimittel, Novartis, and Roche Pharma, all outside the submitted work. Dr Inagaki declares that he has received grants from Novartis Pharma, lecture fees from Pfizer, Mochida, Shionogi, Sumitomo Dainippon Pharma, Daiichi-Sankyo, Meiji Seika and Takeda, and royalties from Nippon Hyoron Sha, Nanzando, Seiwa Shoten, Igaku-shoin and Technomics, all outside of the submitted work. Dr Yamada reports personal fees from Meiji Seika Pharma Co., Ltd., MSD K.K., Asahi Kasei Pharma Corporation, Seishin Shobo, Seiwa Shoten Co., Ltd., Igaku-shoin Ltd., Chugai Igakusha and Sentan Igakusha, all outside the submitted work. All other authors declare no competing interests. No funder had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.
The market structure and recipes for beer has been rapidly changing with craft beers attracting more consumers. Perceived hops quality (hoppiness) is one of the main attributes that microbrewers alter to differentiate their products to satisfy consumers’ changing tastes and preferences. We hypothesize that, in addition to manipulating beer-processing conditions, the conditions under which the hops are grown may also influence the final sensory properties of the beer. Using hops from a field experiment coupled with sensory attributes and sociodemographic characteristics from a contingent valuation survey, we analyzed the impact of under-fertilized hop treatments during the growing season on consumers’ willingness to pay for beer. The results indicate that uninformed consumers in a blind tasting could identify the differences in beer made from hops across the fertilization treatments and, thus, implying that all else equal sufficient fertilizer is required to achieve satisfactory hoppiness for which consumers are willing to pay. (JEL Classifications: C91, D12, L66, Q11)
Because the 14C calibration curves IntCal and SHCal are based on data from temperate latitudes, it remains unclear which curve is more suitable for archaeological and paleoenvironmental records from tropical South America. A review of climate dynamics reveals a significant influx of Northern Hemisphere air masses and moisture over a substantial part of the continent during the South American Summer Monsoon (SASM). Areas affected by the SASM receive unknown amounts of input from both hemispheres, where an argument could be made for either curve. Until localized tree-ring data can resolve this, we suggest using a mixed calibration curve, which accounts for inputs from both hemispheres, as a third calibration option. We present a calibration example from a crucial period of environmental and cultural change in the southern Lake Titicaca. Given our current lack of data on past ∆14C variation in South America, our calibrations and chronologies will likely change in the future. We hope this paper spurs new research into this topic and encourages researchers to make an informed and explicit choice of which curve to use, which is particularly relevant in research on past human–environmental relationships.
Objectives: Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered.
Methods: This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences.
Results: The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported.
Conclusions: The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.
Norovirus is the leading cause of acute gastroenteritis in the USA. Although secondary household transmission of norovirus is frequently reported in outbreaks, little is known about specific risk factors for susceptibility and infectiousness in the household. Three norovirus outbreaks were investigated and data were collected on individuals exposed in the primary outbreak setting and their household members. Potential individual- and household-level risk factors for susceptibility and infectiousness were assessed using univariate and multivariate generalised linear mixed models. In the univariate models, the secondary attack rate (SAR) was significantly higher when living in a household with two or more primary cases (incidence rate ratio (IRR) = 2·1; 95% confidence interval (CI) 1·37–3·29), more than one primary case with vomiting (IRR = 1·9; CI 1·11–3·37), and at least one primary case with diarrhoea (IRR = 3·0; CI 1·46–6·01). After controlling for other risk factors in the multivariate models, the SAR was significantly higher among those living in a household with two or more primary cases (adjusted IRR = 2·0; CI 1·17–3·47) and at least one primary case with diarrhoea (adjusted IRR = 2·8; CI 1·35–5·93). These findings underscore the importance of maintaining proper hygiene and isolating ill household members to prevent norovirus transmission in the household.
Tidal flexure in ice shelf grounding zones has been used extensively in the past to determine grounding line position and ice properties. Although the rheology of ice is viscoelastic at tidal loading frequencies, most modelling studies have assumed some form of linear elastic beam approximation to match observed flexure profiles. Here we use density, radar and DInSAR measurements in combination with full-Stokes viscoelastic modelling to investigate a range of additional controls on the flexure of the Southern McMurdo Ice Shelf. We find that inclusion of observed basal crevasses and density dependent ice stiffness can greatly alter the flexure profile and yet fitting a simple elastic beam model to that profile will still produce an excellent fit. Estimates of the effective Young's modulus derived by fitting flexure profiles are shown to vary by over 200% depending on whether these factors are included, even when the local thickness is well constrained. Conversely, estimates of the grounding line position are relatively insensitive to these considerations for the case of a steep bed slope in our study region. By fitting tidal amplitudes only, and ignoring phase information, elastic beam theory can provide a good fit to observations in a wide variety of situations. This should, however, not be taken as an indication that the underlying rheological assumptions are correct.
Motivated by disease outbreaks and trade shocks, a dynamic equilibrium displacement model is calibrated for the U.S. pear industry to simulate welfare from various shocks compared to a baseline. Our contribution is assessing the impact to intermediary packers for fresh fruit and processors for processed fruit in addition to growers and consumers. The processed market is more sensitive than the fresh market generally, and supply shocks induce larger impacts on both markets than trade sanctions. Impacts to intermediaries are on par with growers, indicating that not considering them misstates the distribution of damages to the industry from a shock.
Modelling of Solar Energetic Particles (SEPs) is usually carried out by means of the 1D focused transport equation and the same approach is adopted within several SEP Space Weather forecasting frameworks. We present an alternative approach, based on test particle simulations, which naturally describes 3D particle propagation. The SPARX forecasting system is an example of how test particle simulations can be used in real time in a Space Weather context. SPARX is currently operational within the COMESEP Alert System. The performance of the system, which is triggered by detection of a solar flare of class >M1.0 is evaluated by comparing forecasts for flare events between 1997 and 2017 with actual SEP data from the GOES spacecraft.
Grounding zones are vital to ice-sheet mass balance and its coupling to the global ocean circulation. Processes here determine the mass discharge from the grounded ice sheet, to the floating ice shelves. The response of this transition zone to tidal forcing has been described by both elastic and viscoelastic models. Here we examine the validity of these models for grounding zone flexure over tidal timescales using field data from the Southern McMurdo Ice Shelf (78° 15′S, 167° 7′E). Observations of tidal movement were carried out by simultaneous tiltmeter and GPS measurements along a profile across the grounding zone. Finite-element simulations covering a 64 d period reveal that the viscoelastic model fits best the observations using a Young's modulus of 1.6 GPa and a viscosity of 1013.7 Pa s (≈ 50.1 TPa s). We conclude that the elastic model is only well-constrained for tidal displacements >35% of the spring-tidal amplitude using a Young's modulus of 1.62 ± 0.69 GPa, but that a viscoelastic model is necessary to adequately capture tidal bending at amplitudes below this threshold. In grounding zones where bending stresses are greater than at the Southern McMurdo Ice Shelf or ice viscosity is lower, the threshold would be even higher.
The chronology of the Inca Empire has traditionally relied on ethnohistoric dates, which suggest that a northern expansion into modern Ecuador began in AD 1463 and a southern expansion into modern Argentina began in AD 1471. We test the validity of these dates with two Bayesian models, which show that the ethnohistoric dates are incorrect and that the southern expansion began before the northern one. The first model of seven dates shows that the site of Chamical, Ecuador, was first occupied cal AD 1410–1480 (95% probability) and has a high probability of being built prior to the ethnohistoric date. The second is an outlier model of 26 14C dates and 19 thermoluminescence (TL) dates from 10 sites along the empire’s southeastern limit in northwestern Mendoza, Argentina. Here, the Inca occupation began cal AD 1350–1440 (95% probability), also earlier than the ethnohistoric date. The model also suggests that the Inca occupation of Mendoza lasted 70–230 yr (95% probability), longer than previously thought, which calls for new perspectives on the timing and nature of Inca conquests and relationships with local groups. Based on these results, we argue it is time to abandon the traditional chronology in favor of Inca chronologies based on Bayesian models.