Did Operating Speeds During COVID-19 Result in More Fatal and Injury Crashes on Urban Freeways?

Impacts of the COVID-19 pandemic in the transportation arena included less traffic, higher speeds, and higher fatal and injury crash frequencies. Many news media reported on speeding and its impact. However, the majority of these reporting are based on partial or incomplete information. The current study aims to understand the association between speed and crash on the freeways of Dallas (Texas) by collecting data from the National Performance Management Research Dataset, the Texas Department of Transportation?s (TxDOT?s) roadway inventory, and TxDOT?s crash database for 2018?2020. The results show decreasing traffic volume, increasing average operating speed, and increasing fatal and severe crash frequencies per 100?million vehicle miles traveled during 2020 (April?November). This study developed 8-month- and daily-level safety prediction models for fatal and injury crashes. The 8-month-level dataset contains speed measures as an aggregate for the 8-month period. The daily-level database includes operating speeds and fatal and injury crashes at the daily level where segments experiencing fatal and injury crashes were temporally matched with the same segment with the same day of the week and with no fatal and injury crash occurrences. For the 8-month models, average operating speed and speed variability are positively associated with fatal and injury crash frequencies during the COVID period. This association was also found for daily-level models. The findings of this study can help transportation agencies in developing strategies (for example, posted speed limit reconsideration, additional enforcement at specific locations) for crash reduction.

Virtual Delivery of Simulation Education to Undergraduate Medical Students During the COVID-19 Pandemic (preprint)

Background The COVID-19 pandemic has restricted in-person clinical training for medical students. Simulation-based teaching is a promising tool to introduce learners to the clinical environment. MacSim is a student-led simulation workshop for learners to develop clinical competencies. The objective of this study was to assess the impacts of MacSim and participants’ perspectives regarding simulation-based teaching. Methods A comprehensive simulation, representative of a virtual care scenario, was delivered to 42 pre-clerkship medical students via video conferencing. In pairs, participants obtained histories and carried out management plans for simulated patients. Participants were surveyed and interviewed. Survey data were analyzed using the Wilcoxon signed-ranks test. Interview transcript data were thematically analyzed. Results Post-simulation, participants (n=24) felt more prepared to make clinical decisions, collaborate, and communicate in a virtual setting. 92% of respondents agreed MacSim was a valuable learning experience and 96% agreed more simulation-based learning should be integrated into curricula. Emergent themes from interviews (n=12) included: 1) value of simulation fidelity, 2) value of physician feedback, and 3) effectiveness of MacSim in improving virtual clinical skills. Conclusion Simulation-based teaching is of importance and educational value to medical students. It may play an increasingly prevalent role in education as virtual care is likely to become more prevalent.

Rapidly Remote: Providing Seamless Library Support during a Pandemic

This column describes efforts adapting services and programming to meet the changing needs of users during the COVID-19 pandemic. More specifically, the column outlines strategies for engaging patrons in both synchronous and asynchronous learning environments, details of the technologies used coupled with free or low-cost technology alternatives, and insight to lessons learned throughout the process that may be relevant to practicing hospital librarians.

Content analysis and characterization of medical tweets during the early Covid-19 pandemic (preprint)

ObjectiveThe novel coronavirus disease 2019 (Covid-19) has infected millions worldwide and impacted the lives of many folds more. Many clinicians share new Covid-19 related resources, research, and ideas within the online Free Open Access to Medical Education (FOAM) community of practice. This study provides a detailed content and contributor analysis of Covid-19 related tweets among the FOAM community. Design, Setting, ParticipantsTwitter was searched from November 1st, 2019 to March 21st, 2020 for English tweets discussing Covid-19 in the FOAM community. Tweets were classified into one of 13 pre-specified content categories: original research, editorials, FOAM resource, public health, podcast or video, learned experience, refuting false information, policy discussion, emotional impact, blatantly false information, other Covid-19, and non-Covid-19. Further analysis of linked original research and FOAM resources was performed. 1000 randomly selected contributor profiles and those deemed to have contributed false information were analyzed. ResultsThe search yielded 8541 original tweets from 4104 contributors. The number of tweets in each content category were: 1557 other Covid-19 (18{middle dot}2%), 1190 emotional impact (13{middle dot}9%), 1122 FOAM resources (13{middle dot}1%), 1111 policy discussion (13{middle dot}0%), 928 advice (10{middle dot}9%), 873 learned experience (10{middle dot}2%), 424 non-Covid-19 (5{middle dot}0%), 410 podcast or video (4{middle dot}8%), 304 editorials (3{middle dot}6%), 275 original research (3{middle dot}2%), 245 public health (2{middle dot}9%), 83 refuting false information (1{middle dot}0%), and 19 blatantly false (0{middle dot}2%). ConclusionsEarly in the Covid-19 pandemic, the FOAM community used Twitter to share Covid-19 learned experiences, online resources, crowd-sourced advice, research, and to discuss the emotional impact of Covid-19. Twitter also provided a forum for post-publication peer review of new research. Sharing blatantly false information within this community was infrequent. This study highlights several potential benefits from engaging with the FOAM community on Twitter.

Analysis of 46,046 SARS-CoV-2 whole-genomes leveraging principal component analysis (PCA) (preprint)

Since the beginning of the global SARS-CoV-2 pandemic, there have been a number of efforts to understand the mutations and clusters of genetic lines of the SARS-CoV-2 virus. Until now, phylogenetic analysis methods have been used for this purpose. Here we show that Principal Component Analysis (PCA), which is widely used in population genetics, can not only help us to understand existing findings about the mutation processes of the virus, but can also provide even deeper insights into these processes while being less sensitive to sequencing gaps. Here we describe a comprehensive analysis of a 46,046 SARS-CoV-2 genome sequence dataset downloaded from the GISAID database in June of this year. SummaryPCA provides deep insights into the analysis of large data sets of SARS-CoV-2 genomes, revealing virus lineages that have thus far been unnoticed.