The Impact of the Sars-Cov-2 Pandemic (COVID-19) on the Incidence of Newly Diagnosed Multiple Myeloma Patients Using a Federated Network of Real-World Evidence in US and Germany

Objectives: COVID-19 had an impact on health care, including diagnostics. Early diagnosis of MM is a critical factor for prognosis. We examined the impact of COVID-19 on incidence of NDMM patients and on characteristics in NDMM patients in US and in Germany. Method(s): 44,164 NDMM patients were identified in TriNetX federated network across 55 healthcare organizations in US between January 2018 and December 2021. A bivariate analysis examined changes in patient characteristics in two cohorts before (Cohort 1;n=25513) and after (Cohort 2;n=18.651) the start of the COVID-19 pandemic in March 2020. 4172 NDMM patients were identified in the German database in a sample of across >100 healthcare organizations in the same time period. Similarly, bivariate analysis examined changes in patient characteristics before (Cohort 1;n=2252) and after (Cohort 2;n=1920) the start of pandemic. Result(s): Analysis of US data showed a significant decrease in incidence of NDMM. Bivariate analysis revealed that NDMM patients in Cohort 2 have a significantly higher risk profile compared with patients in Cohort 1, higher incidence of renal failure (13.5% v. 15.43%), heart failure (10.3% v 11.26%), bone lesions (12.6% v. 13.05%) and anemia (26.8% v. 29.75%). The German data indicated an increased risk profile in Cohort 2, with higher reporting of renal impairment (12.3% v. 15.5%) and cardiac impairment (8.3% v. 10.9%). The higher risk profile was reflected in a significant increase of all SLiM-CRAB criteria, notably hypercalcemia (24.1 % v. 36.9%), bone marrow plasma cell infiltration (28.1% v. 36.8%) and free light chain involvement (27.3% v. 41.3%). Conclusion(s): The results provide real-world evidence of a change in risk profile for patients with NDMM during COVID-19. This higher risk profile is observed in both the US and Germany, and may negatively impact outcomes such as progression-free and five-year overall survival.Copyright © 2023

PanDa Game: Optimized Privacy-Preserving Publishing of Individual-Level Pandemic Data Based on a Game Theoretic Model.

Sharing individual-level pandemic data is essential for accelerating the understanding of a disease. For example, COVID-19 data have been widely collected to support public health surveillance and research. In the United States, these data are typically de-identified before publication to protect the privacy of the corresponding individuals. However, current data publishing approaches for this type of data, such as those adopted by the U.S. Centers for Disease Control and Prevention (CDC), have not flexed over time to account for the dynamic nature of infection rates. Thus, the policies generated by these strategies have the potential to both raise privacy risks or overprotect the data and impair the data utility (or usability). To optimize the tradeoff between privacy risk and data utility, we introduce a game theoretic model that adaptively generates policies for the publication of individual-level COVID-19 data according to infection dynamics. We model the data publishing process as a two-player Stackelberg game between a data publisher and a data recipient and then search for the best strategy for the publisher. In this game, we consider 1) the average performance of predicting future case counts, and 2) the mutual information between the original data and the released data. We use COVID-19 case data from Vanderbilt University Medical Center from March 2020 to December 2021 to demonstrate the effectiveness of the new model. The results indicate that the game theoretic model outperforms all state-of-the-art baseline approaches, including those adopted by CDC, while maintaining low privacy risk. We further perform an extensive sensitivity analyses to show that our findings are robust to order-of-magnitude parameter fluctuations.

Supporting COVID-19 Disparity Investigations with Dynamically Adjusting Case Reporting Policies

Data access limitations have stifled COVID-19 disparity investigations in the United States. Though federal and state legislation permits publicly disseminating de-identified data, methods for de-identification, including a recently proposed dynamic policy approach to pandemic data sharing, remain unproved in their ability to support pandemic disparity studies. Thus, in this paper, we evaluate how such an approach enables timely, accurate, and fair disparity detection, with respect to potential adversaries with varying prior knowledge about the population. We show that, when considering reasonably enabled adversaries, dynamic policies support up to three times earlier disparity detection in partially synthetic data than data sharing policies derived from two current, public datasets. Using real-world COVID-19 data, we also show how granular date information, which dynamic policies were designed to share, improves disparity characterization. Our results highlight the potential of the dynamic policy approach to publish data that supports disparity investigations in current and future pandemics.

Neuropsychiatric Side Effects of Steroids during Treatment for Pediatric Acute Lymphoblastic Leukemia: A Comprehensive Narrative Review

Background/Purpose: Pediatric Acute Lymphoblastic Leukemia (ALL) affects ~4000 young Americans each year. Steroids are essential to curative ALL treatment yet have significant neuropsychiatric side effects that decrease quality of life for patients and families. However, incidence and predisposing risk factors are not well understood. This review aims to describe the current literature on neuropsychiatric side effects of steroids in Pediatric ALL. Method(s): A precise search in PubMed and Embase was cultivated using controlled vocabulary terms (MeSH, Emtree) and keywords for the following concepts: pediatrics, steroids, side effects, cancer, and neurobehavioral manifestations. Keywords and controlled vocabulary for each subject were arranged logically and combined with other concepts by Boolean Logic, using the Boolean operator AND, resulting in 642 precise results exploring neurobehavioral side effects of steroids in children with cancer. Results (2010 to date of search) were imported into Covidence systematic review software, and reviewed by SB and AM. Result(s): Twenty-three articles met inclusion criteria. There is marked variability in research methodology and no standard measurement of neuropsychiatric symptoms. Commonly reported symptoms include mood swings, irritability, depression, anxiety, aggression, insomnia, mania, and psychosis with prevalence between 5% and 75%. Heterogeneous research methodology and descriptions of psychiatric symptoms make it difficult to determine risk factors, though dexamethasone, family psychiatric history, and younger age are consistently associated with greater risk of behavioral dysregulation. Genetic predisposition (Bcl1 polymorphism, SNPs in GR gene) may increase susceptibility to developing depression during treatment. Data suggest variable efficacy of antipsychotics, benzodiazepines, hydrocortisone, and potassium-chloride. Conclusions and Implications: Existing data about neuropsychiatric side effects of steroids in pediatric ALL is extremely heterogeneous, creating challenges for standardized assessment and treatment. The burden of these symptoms necessitates further research to identify and treat vulnerable patients. Standard measurement of these symptoms could be a first step in eventually alleviating this source of distress.

Characteristics and risk factors for persistent breathlessness after hospitalisation for COVID-19

Background: Persisting breathlessness after COVID-19 infection is common and debilitating. We aimed to characterise and identify risk factors for patients with persistent breathlessness following COVID-19 hospitalisation. Method(s): PHOSP-COVID is a multi-centre prospective cohort study of UK adults hospitalised for COVID-19. Clinical data were collected during hospitalisation and at a research visit. Breathlessness was measured by a numeric rating scale of 0-10. We defined post-COVID breathlessness as an increase in score of 1 or more compared to the preCOVID-19 level. Multivariable logistic regression was used to identify risk factors. Result(s): We included 1,226 participants (37% female, median age 59 years, 22% mechanically ventilated). At a median five months after discharge, 50% reported post-COVID breathlessness. Risk factors for post-COVID breathlessness were socio-economic deprivation (adjusted odds ratio, 1.67;95% confidence interval, 1.14-2.44), pre-existing depression/anxiety (1.58;1.06-2.35), female sex (1.56;1.21-2.00) and admission duration (1.01;1.00- 1.02). Black ethnicity (0.56;0.35-0.89) and older age groups (0.31;0.14-0.66) were less likely to report post-COVID breathlessness. Post-COVID breathlessness was associated with worse performance on the shuttle walk test and forced vital capacity, but not with obstructive airflow limitation. Conclusion(s): Half of this national cohort of patients hospitalised for COVID-19 experienced persistent breathlessness at follow up. The risk factors identified for post-COVID breathlessness should inform mechanistic work to understand causal processes and develop future interventions to improve outcomes in this growing population.

In God We Trust: Community and Immunity in American Religions during COVID-19

From the systemic issues of race and class division to political partisanship and religious identity, the pandemic has affected many aspects of American social and political life. I interrogate the role that religions have played in communal identity-making during the pandemic, and how such identities shaped ideological responses, particularly in the US, stymying public health efforts to stop, or at least significantly slow, the spread of COVID-19. Drawing from Gabriel Garcia Marquez's Love in the Time of Cholera as a historical case study, I use Garcia Marquez's depiction of religion's identity-making power during the cholera pandemic depicted in the novel as a comparison by which to understand current experiences of white Evangelical Christians in America during the current COVID-19 pandemic, particularly those who reject risk-minimizing practices such as mask wearing, quarantining, and vaccination. Drawing both from representations of Roberto Esposito's theory of immunity and community, and from Lauren Berlant's concept of "cruel optimism”, as well as sociological understandings of religion and identity, I argue that the boundary-making practices of religion and of communal and national identity are related to the complex and often contradictory set of moral practices that led many white Evangelicals to disregard public health policies surrounding COVID-19. A concurrent analysis of Garcia Marquez's novel and of current events will allow me to explore this phenomenon, as Lauren Berlant would put it, both through the historically affective aesthetic and through the affective present. © 2023 by the author.

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.

Emergence in emergency: How actors adapt to service ecosystem disruption

Marketing scholars are applying the concept of emergence to understand an increasingly unstable world. While what emerges is of interest, the present study enriches conceptualisations of how emergence unfolds through a netnographic study of an online network formed to address the deficiencies of service ecosystems disrupted by Covid-19. We identify how a new network between actors with no prior ties to each other is formed at speed by individuals to integrate unregulated resources, and observe the early emergence of a proto-institution in the form of new practices as actors move quickly to stabilise this network. Initial interactions are prompted by individual vulnerability but sustained by the emergence of a shared conception of vulnerability among surprisingly agentic actors. While these findings stem from a single case of disruption, they suggest that further research which deepens understanding of emergent phenomena in conditions of volatility and uncertainty would be of great value. © 2023

Polymer formulated self-amplifying RNA vaccine is partially protective against influenza virus infection in ferrets.

COVID-19 has demonstrated the power of RNA vaccines as part of a pandemic response toolkit. Another virus with pandemic potential is influenza. Further development of RNA vaccines in advance of a future influenza pandemic will save time and lives. As RNA vaccines require formulation to enter cells and induce antigen expression, the aim of this study was to investigate the impact of a recently developed bioreducible cationic polymer, pABOL for the delivery of a self-amplifying RNA (saRNA) vaccine for seasonal influenza virus in mice and ferrets. Mice and ferrets were immunized with pABOL formulated saRNA vaccines expressing either haemagglutinin (HA) from H1N1 or H3N2 influenza virus in a prime boost regime. Antibody responses, both binding and functional were measured in serum after immunization. Animals were then challenged with a matched influenza virus either directly by intranasal inoculation or in a contact transmission model. While highly immunogenic in mice, pABOL-formulated saRNA led to variable responses in ferrets. Animals that responded to the vaccine with higher levels of influenza virus-specific neutralizing antibodies were more protected against influenza virus infection. pABOL-formulated saRNA is immunogenic in ferrets, but further optimization of RNA vaccine formulation and constructs is required to increase the quality and quantity of the antibody response to the vaccine.

Global value chains for medical gloves during the COVID-19 pandemic: Confronting forced labour through public procurement and crisis

This paper evaluates ways in which labour issues in global value chains for medical gloves have been affected by, and addressed through, the COVID-19 pandemic. It focuses on production in Malaysia and supply to the United Kingdom's National Health Service and draws on a large-scale survey with workers and interviews with UK government officials, suppliers and buyers. Adopting a Global Value Chain (GVC) framework, the paper shows how forced labour endemic in the sector was exacerbated during the pandemic in the context of increased demand for gloves. Attempts at remediation are shown to operate through both a reconfigured value chain in which power shifted dramatically to the manufacturers and a context where public procurement became higher in profile than ever before. It is argued that the purchasing power of governments must be leveraged in ways that more meaningfully address labour issues, and that this must be part of value chain resilience. © 2022 The Authors. Global Networks published by John Wiley & Sons Ltd.

Privacy-Preserving Publishing of Individual-Level Pandemic Data Based on a Game Theoretic Model

Sharing individual-level pandemic data is essential for accelerating the understanding of a disease. For example, COVID-19 data have been widely collected to support public health surveillance and research. In the United States, these data need to be de-identified before being released to the public due to privacy concerns. However, current data publishing approaches for individual-level pandemic data, such as those adopted by the U.S. Centers for Disease Control and Prevention (CDC), have not flexed over time to account for the dynamic nature of infection rates. Thus, the policies generated by these strategies may either raise privacy risks or impair the data utility (or usability). To optimize the tradeoff between privacy risk and data utility, we introduce a game theoretic model that adaptively generates policies to publish individual-level COVID-19 data according to infection dynamics. We model the data publishing process as a two-player Stackelberg game between a data publisher and a data recipient and then search for the best strategy for the publisher. In this game, we consider 1) the average accuracy of predicting future case counts for all demographic groups, and 2) the mutual information between the original data and the released data. We use COVID-19 case data from Vanderbilt University Medical Center from March 2020 to December 2021 to demonstrate our model and evaluate its effectiveness. The experimental results show that our game theoretic model outperforms all baseline approaches, including those adopted by CDC, while maintaining low privacy risk. © 2022 IEEE.

Uptake of Covid-19 Vaccination among Respiratory Therapists in Canada

The COVID-19 pandemic continues throughout the world causing morbidity and mortality. With communities in and out of lockdown, there is an economic and mental health crisis on top of the general COVID-19 health crisis. The development of COVID-19 vaccines is often touted as the solution to this crisis but vaccine effectiveness is dependent on the uptake by the world's population. Canada has currently approved five vaccines and began vaccination in mid December 2020. Healthcare workers were amongst the initial groups for vaccination;however, uptake rates were not initially as high as expected. The Respiratory Therapy profession was on the frontline in the fight against COVID-19, dealing with the most critically ill patients and seeing regularly the most deadly effects of this virus. The rate of vaccination for the Respiratory Therapists in Canada is evolving constantly but it is not clear where it stands in comparison to other Canadian health care workers. In addition, the drivers or factors that play into the decision to get vaccinated are also not clear. Canadian Respiratory Therapist COVID-19 vaccination uptake rates and responses are being investigated with a look at the reasons behind any delays or non-vaccinations as well as other demographics, attitudes or factors that may be shown to play a role. An anonymous survey using SurveyMonkey on vaccination uptake rates, responses and attitudes is available to Student, Graduate and Registered Respiratory Therapists in Canada from July to November 2021. Vaccination uptake rates will be compared to those of healthcare workers in general as per the Government of Canada stats looking at numerous factors including demographics;work and personal experiences with COVID-19 patients;and COVID-19 vaccination attitudes/ concerns. The study will look for any trends in vaccination rates by demographic data, COVID-19 exposure, work experience as well as attitudes for those who are not vaccinated. This data can help by providing information on vaccination uptake rates amongst Respiratory Therapists compared to the healthcare workers and the general populations' rates in Canada. Future studies may look closer at developing specific vaccination campaigns by targeting the reasons for non-vaccination amongst RTs in Canada. Study data will be presented and to date there are over 1000 surveys completed.

A Systematic Review of Sex Differences of Incidence and Overall Survival in 15 Non-Reproductive Cancers

Sex is an important factor that influences disease development, progression, and treatment. In multiple non-reproductive cancers, sex differences in incidence, progression, treatment response, survival, and other clinical outcomes are observed. Overall, males have a 20% higher chance of developing cancer over their lifetime, and experience worse clinical outcomes when compared with females. The NIH recognizes the importance of sex as a biologic variable and addressing sex as a biological variable is now required for all researchers submitting NIH grants. While more researchers are investigating the role of sex differences in cancer, a systematic review that examines the patterns of sex differences in incidence and survival across 15 non-reproductive cancers has not yet been published. We performed a systematic review by searching five databases using keywords and controlled vocabulary terms for each concept of interest and limited to English language. Records were included if it reported sex differences in human adults (18+), addressed incidence, mortality, or survival, at least one of the 15 cancers of interest, and were a cohort, cross-sectional, RCT, or case control study. Covidence was used for screening and two reviewers independently screened each record at title/ and then full text. Two reviewers independently completed data extraction using Microsoft Excel and the Cochrane RoB 2.0, and JBI tools were used for risk of bias assessment. The searches and pilot of the methods are underway. Understanding the role sex-differences play on incidence and survival are important for adding to our understanding of advances in diagnosis and treatment of individuals with cancer.

Impact of Online Learning in the Context of COVID-19 on Undergraduates with Disabilities and Mental Health Concerns

The COVID-19 pandemic upended college education and the experiences of students due to the rapid and uneven shift to online learning. This study examined the experiences of students with disabilities with online learning, with a consideration of surrounding stressors such as financial pressures. In a mixed method approach, we compared 28 undergraduate students with disabilities (including mental health concerns) to their peers during 2020, to assess differences and similarities in their educational concerns, stress levels, and COVID-19-related adversities. We found that students with disabilities entered the Spring quarter of 2020 with significantly higher concerns about classes going online, and reported more recent negative life events than other students. These differences between the two groups diminished 3 months later with the exception of recent negative life events. For a fuller understanding of students' experiences, we conducted qualitative analysis of open-ended interviews. We examined both positive and negative experiences with online learning among students with disabilities and mental health concerns. We describe how online learning enabled greater access-e.g., reducing the need for travel to campus-alongsideways inwhich online learning impeded academic engagement-e.g., reducing interpersonal interaction. We highlight a need for learning systems to meet the diverse and dynamic needs of students with disabilities.

Students' intention on post COVID19 continuance of e-learning

Traditional teaching methods have changed as a result of COVID-19's prominence. For many teachers, the lack of traditional face-to-face training was effectively made up for by online learning. Under emergency management, online learning may support students and schools while also generating special opportunities. In reaction to the epidemic, educational institutions from many nations have introduced extensive online course options. Online education during a pandemic is distinct from regular online education. An investigation on emergency management-related educational reform can be done by surveying students in higher education institutions University students were polled to discover more about their intentions to keep learning online despite the outbreak. Using the task-technology fit model, expectation confirmation theory was broadened to examine if the technical support for promoting online learning assisted students in completing course learning assignments while pandemic was going on and led to a persistent intention to take use of E-learning in the nearby future. When creating eLearning platforms, governments must exercise caution because students' intentions to continue their e-learning may change as a result of unanticipated crises like COVID-19. Through the use of online surveys, data were gathered. The research hypotheses were validated with partial least squares method and structural equation modelling on a total of 513 valid replies. The findings showed that continuing intention was substantially explained by the entire research design. After the COVID-19 pandemic, specific recommendations are made regarding how higher education institutions may support online learning strategies. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.