Libraries and Diminished Patron Privacy During the COVID-19 Health Crisis

The COVID-19 health crisis has ushered in an era of great change in the way individuals and institutions function. With the contagious and deadly nature of COVID-19, libraries geared their efforts to increase access to and use of digital collections. With the introduction of stay-home orders, the option of adopting full virtual services became the go-to solution as a way of protecting library staff and users. Collaboration with third-party vendors that provide online library services heightened like never before. As libraries reopened at a later point in the global pandemic, library staff were asked to conduct health screenings for patrons entering the library and actively monitor whether patrons were socially distanced in the library. The drastic change to library operations due to the pandemic resulted in the increased collection of patrons' personal information ranging from health information to location data coupled with library records. Much as librarians are traditionally and professionally committed to protecting their patrons' privacy, undertaking activities like health screening in the absence of data transparency practices can potentially impact library users' privacy. In this study, we investigated whether the 25 Association of Research Libraries (ARL) members with the largest number of titles held developed or modified their privacy policies in response to the increase in data collection during the COVID-19 health crisis. Privacy policies are living documents that should evolve with the times and thus should be updated or modified to reflect the current realities. We also examined whether pre-pandemic privacy policies, if any, of the surveyed 25 ARL member libraries are aligned with the privacy requirements outlined in the American Library Association (ALA) Privacy Toolkit (ALA 2014). Our results show that of the surveyed 25 ARL libraries, none of them developed a new library privacy policy or modified an existing one to reflect their data practices with specific regard to the new realities presented by the COVID-19 pandemic. The disregard for such adjustments to their privacy policies violated the principle of data transparency. Our results also show that, at the time of the survey, 4 of the surveyed 25 ARL members did not have library privacy policies.

Understanding information needs during COVID-19: A comparison study between an online health community and a Q&A platform.

This paper aims at identifying user's information needs on Coronavirus and the differences of user's information needs between the online health community MedHelp and the question-and-answer forum Quora during the COVID-19 global pandemic. We obtained the posts in the sub-community Coronavirus on MedHelp (195 posts with 1627 answers) and under the topic of COVID-19(2019-2020) on Quora (263 posts with 8401 answers) via web scraping built on Selenium WebDriver. After preprocessing, we conducted topic modeling on both corpora and identified the best topic model for each corpus based on the diagnostic metrics. Leveraging the improved sqrt-cosine similarity measurement, we further compared the topic similarity between these two corpora. This study finds that there are common information needs on both platforms about vaccination and the essential elements of the disease including the onset symptoms, transmission routes, preventive measures, treatment and control of COVID-19. Some unique discussions on MedHelp are about psychological health, and therapeutic management of patients. Users on Quora have special interests of information about the association between vaccine and Luciferase, and attacks on Fauci after email trove released. The work is beneficial for researchers who aim to provide accurate information assistance and build effective online emergence response programs during the pandemic.

Validation of a Crisis Standards of Care Model for Prioritization of Limited Resources During the Coronavirus Disease 2019 Crisis in an Urban, Safety-Net, Academic Medical Center.

OBJECTIVES: The coronavirus disease 2019 pandemic has overwhelmed healthcare resources even in wealthy nations, necessitating rationing of limited resources without previously established crisis standards of care protocols. In Massachusetts, triage guidelines were designed based on acute illness and chronic life-limiting conditions. In this study, we sought to retrospectively validate this protocol to cohorts of critically ill patients from our hospital. DESIGN: We applied our hospital-adopted guidelines, which defined severe and major chronic conditions as those associated with a greater than 50% likelihood of 1- and 5-year mortality, respectively, to a critically ill patient population. We investigated mortality for the same intervals. SETTING: An urban safety-net hospital ICU. PATIENTS: All adults hospitalized during April of 2015 and April 2019 identified through a clinical database search. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 365 admitted patients, 15.89% had one or more defined chronic life-limiting conditions. These patients had higher 1-year (46.55% vs 13.68%; p < 0.01) and 5-year (50.00% vs 17.22%; p < 0.01) mortality rates than those without underlying conditions. Irrespective of classification of disease severity, patients with metastatic cancer, congestive heart failure, end-stage renal disease, and neurodegenerative disease had greater than 50% 1-year mortality, whereas patients with chronic lung disease and cirrhosis had less than 50% 1-year mortality. Observed 1- and 5-year mortality for cirrhosis, heart failure, and metastatic cancer were more variable when subdivided into severe and major categories. CONCLUSIONS: Patients with major and severe chronic medical conditions overall had 46.55% and 50.00% mortality at 1 and 5 years, respectively. However, mortality varied between conditions. Our findings appear to support a crisis standards protocol which focuses on acute illness severity and only considers underlying conditions carrying a greater than 50% predicted likelihood of 1-year mortality. Modifications to the chronic lung disease, congestive heart failure, and cirrhosis criteria should be refined if they are to be included in future models.

Binding Strength and Hydrogen Bond Numbers between COVID-19 RBD and HVR of Antibody

The global battle against the COVID-19 pandemic relies strongly on the human defense of antibody, which is assumed to bind the antigen’s receptor binding domain (RBD) with its hypervariable region (HVR). Due to the similarity to other viruses such as SARS, however, our understanding of the antibody-virus interaction has been largely limited to the genomic sequencing, which poses serious challenges to containment and rapid serum testing. Based on the physical/chemical nature of the interaction, infrared spectroscopy was employed to reveal the binding disparity, the real cause of the antibody-virus specificity at the molecular level, which is inconceivable to be investigated otherwise. Temperature dependence was discovered in the absorption value from the 1550 cm−1 absorption band, attributed to the hydrogen bonds by carboxyl/amino groups, binding the SARS-CoV-2 spike protein and closely resembled SARS-CoV-2 or SARS-CoV-1 antibodies. The infrared absorption intensity, associated with the number of hydrogen bonds, was found to increase sharply between 27 °C and 31 °C, with the relative absorbance matching the hydrogen bonding numbers of the two antibody types (19 vs. 12) at 37 °C. Meanwhile, the ratio of bonds at 27 °C, calculated by thermodynamic exponentials, produces at least 5% inaccuracy. Beyond genomic sequencing, the temperature dependence, as well as the bond number match at 37 °C between relative absorbance and the hydrogen bonding numbers of the two antibody types, is not only of clinical significance in particular but also as a sample for the physical/chemical understanding of vaccine–antibody interactions in general.

The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic.

Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data-driven knowledge discovery and more sophisticated spatial analysis central to the COVID-19 pandemic. We implement a new, open source spatial middleware component (libgeoda) and system design to scale development quickly to effectively meet the need for surveilling county-level metrics in a rapidly changing pandemic landscape. We incorporate, wrangle, and analyze multiple data streams from volunteered and crowdsourced environments to leverage multiple data perspectives. We integrate explorative spatial data analysis (ESDA) and statistical hotspot standards to detect infectious disease clusters in real time, building on decades of research in GIScience and spatial statistics. We scale the computational infrastructure to provide equitable access to data and insights across the entire USA, demanding a basic but high-quality standard of ESDA techniques. Finally, we engage a research coalition and incorporate principles of user-centered design to ground the direction and design of Atlas application development.

Abdominal Organ Transplantation: Noteworthy Literature in 2020.

In 2020, we identified and screened over 490 peer-reviewed publications on pancreatic transplantation, over 500 on intestinal transplantation, and over 5000 on kidney transplantation. The liver transplantation section specially focused on clinical trials and systematic reviews published in 2020 and featured selected articles. This review highlights noteworthy literature pertinent to anesthesiologists and critical care physicians caring for patients undergoing abdominal organ transplantation. We explore a wide range of topics, including COVID-19 and organ transplantation, risk factors and outcomes, pain management, artificial intelligence, robotic donor surgery, and machine perfusion.