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OBJECTIVE: This qualitative study aimed to examine how states implemented COVID-19 public health emergency-related federal policy flexibilities for opioid use disorder treatment from the perspective of state-level behavioral health policy makers. Recommendations are given for applying lessons learned to improve the long-term impact of these flexibilities on opioid use disorder treatment. METHODS: Eleven semistructured interviews were conducted with 13 stakeholders from six state governments, and transcripts were qualitatively coded. Data were analyzed by grouping findings according to state-, institution-, and provider-level barriers and facilitators and were then compared to identify overarching themes. RESULTS: Policy makers expressed positive opinions about the opioid use disorder treatment flexibilities and described benefits regarding treatment access, continuity of care, and quality of care. No interviewees reported evidence of increased adverse events associated with the relaxed medication protocols. Challenges to state-level implementation included gaps in the federal flexibilities, competing state policies, facility and provider liability concerns, and persistent systemic stigma. CONCLUSIONS: As the federal government considers permanent adoption of COVID-19-related flexibilities regarding opioid use disorder treatment policies, the lessons learned from this study are crucial to consider in order to avoid continuing challenges with policy implementation and to effectively remove opioid use disorder treatment barriers.

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Patients with cancer are known to have a poor prognosis when infected with SARS-CoV-2 infection. We aimed in this study to assess health outcomes in COVID-19 patients with different cancers in comparison to non-cancer COVID-19 patients from different centers in the United States (US). We evaluated medical records of 1,943 COVID-19 Cancer patients from 3 hospitals admitted between December 2019 to October 2021 and compared them with non-cancer COVID-19 patients. Among 1,943 hospitalized COVID-19 patients, 18.7% (n=364) have an active or previous history of cancer. Among these 364 cancer patients, 222 were African Americans (61.7%) and 121 were Caucasians (33.2%). Cancer patients had significantly longer hospitalization compared to controls (8.24 vs 6.7 days). Overall, Lung cancer is associated with high mortality. Patients with a previous history of cancer were more prone to death (p=0.04) than active cancer patients. In univariate and multivariate analyses, predictors of death among cancer patients were male sex, older age, presence of dyspnea, elevated troponin, elevated AST (0.001) and ALT (0.05), low albumin (p=0.04) and mechanical ventilation (p=0.001). Patients with a previous history of cancer were more prone to death when compared to active cancer COVID-19 patients. Early recognition of cancer COVID-19 patients' death-associated risk factors can help determine appropriate treatment and management plans for better prognosis and outcome.

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BACKGROUND: During the COVID-19 pandemic swift implementation of research cohorts was key. While many studies focused exclusively on infected individuals, population based cohorts are essential for the follow-up of SARS-CoV-2 impact on public health. Here we present the CON-VINCE cohort, estimate the point and period prevalence of the SARS-CoV-2 infection, reflect on the spread within the Luxembourgish population, examine immune responses to SARS-CoV-2 infection and vaccination, and ascertain the impact of the pandemic on population psychological wellbeing at a nationwide level. METHODS: A representative sample of the adult Luxembourgish population was enrolled. The cohort was followed-up for twelve months. SARS-CoV-2 RT-qPCR and serology were conducted at each sampling visit. The surveys included detailed epidemiological, clinical, socio-economic, and psychological data. RESULTS: One thousand eight hundred sixty-five individuals were followed over seven visits (April 2020-June 2021) with the final weighted period prevalence of SARS-CoV-2 infection of 15%. The participants had similar risks of being infected regardless of their gender, age, employment status and education level. Vaccination increased the chances of IgG-S positivity in infected individuals. Depression, anxiety, loneliness and stress levels increased at a point of study when there were strict containment measures, returning to baseline afterwards. CONCLUSION: The data collected in CON-VINCE study allowed obtaining insights into the infection spread in Luxembourg, immunity build-up and the impact of the pandemic on psychological wellbeing of the population. Moreover, the study holds great translational potential, as samples stored at the biobank, together with self-reported questionnaire information, can be exploited in further research. TRIAL REGISTRATION: Trial registration number: NCT04379297, 10 April 2020.

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OBJECTIVE: Racial and ethnic disparities in exposure to COVID-19-related stressors, pandemic-related distress, and adverse mental health outcomes were assessed among health care workers in the Bronx, New York, during the first wave of the pandemic. METHODS: The authors analyzed survey data from 992 health care workers using adjusted logistic regression models to assess differential prevalence of outcomes by race/ethnicity and their interactions. RESULTS: Compared with their White colleagues, Latinx, Black, Asian, and multiracial/other health care workers reported significantly higher exposure to multiple COVID-19-related stressors: redeployment, fear of being sick, lack of autonomy at work, and inadequate access to personal protective equipment. Endorsing a greater number of COVID-19-related stressors was associated with pandemic-related distress in all groups and with adverse mental health outcomes in some groups; it was not related to hazardous alcohol use in any of the groups. These associations were not significantly different between racial and ethnic groups. Latinx health care workers had significantly higher probabilities of pandemic-related distress and posttraumatic stress than White colleagues. Despite greater exposure to COVID-19-related stressors, Black, Asian, and multiracial/other health care workers had the same, if not lower, prevalence of adverse mental health outcomes. Conversely, White health care workers had a higher adjusted prevalence of moderate to severe anxiety compared with Asian colleagues and greater hazardous alcohol use compared with all other groups. CONCLUSIONS: Health care workers from racial and ethnic minority groups reported increased exposure to COVID-19-related stressors, suggestive of structural racism in the health care workforce. These results underscore the need for increased support for health care workers and interventions aimed at mitigating disparities in vocational exposure to risk and stress.

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The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.

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The clinical entity termed as long COVID has gained importance in the recent past. As this phenomenon is still evolving, it is important to document the magnitude of the syndrome during different time periods. This scoping review attempts to synthesize evidence generated from longitudinal studies which have follow-up periods beyond 3 months, up to 12 months. The review also documents the reported prevalence of long COVID for the different regions of the World Health Organization. Longitudinal studies published till March 2022 were systematically searched on PubMed, Google Scholar, and medRxiv. Among the identified 594 studies, 48 were included in this review. Data from selected studies were synthesized. The overall pooled prevalence of long COVID was 49% (40%-58%). The pooled estimates after 3 months, 4-6 months, 7-9 months, and 10-12 months were 44% (32%-57%), 50% (43%-57%), 49% (37%-62%), and 54% (46%-62%), respectively. Eastern Mediterranean Region (EMR) had the highest pooled prevalence of 63% (34%-92%] and the South East Asian Region (SEAR) had the least pooled estimate of 15% (10%-21%). The study brings out the high prevalence of long COVID even after 12 months of follow-up. It also shows the regional differences in the reported prevalence of the syndrome. This review highlights the need for well-planned follow-up studies, especially in developing nations to understand the magnitude and the pattern of long COVID-related symptoms as they emerge.

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Background: In the early stages of the COVID-19 pandemic, mental-health experts called attention to a possible deterioration of obsessive-compulsive symptoms (OCSs). In particular, people suffering from a fear of contamination were considered a vulnerable population. Aim: The aim of this study was to investigate the change in OCSs from before to during the pandemic within the Swiss general population, and to examine a possible relationship of OCSs to stress and anxiety. Methods: This cross-sectional study was implemented as an anonymized online survey (N = 3,486). The Obsessive-Compulsive Inventory-Revised (OCI-R) was used to assess global OCS severity (range: 0-72, clinical cut-off > 18) and specific OCS dimensions (range: 0-12) during the second wave of the pandemic and retrospectively for before the pandemic. Participants were asked to report stress and anxiety in the previous 2 weeks before the survey. Results: Participants reported significantly higher OCI-R total scores during (12.73) compared to before the pandemic (9.04, mean delta increase: 3.69). Significantly more individuals reported an OCI-R total score exceeding the clinical cut-off during (24%) than before the pandemic (13%). OCS severity increased on all symptom dimensions, but was most pronounced on the washing dimension (all with p < 0.001). Self-reported stress and anxiety were weakly associated with differences in severity in total score and symptom dimensions (with R2 < 0.1 and p < 0.001). Conclusion: Our results indicate that the full spectrum of people with OCS should be considered as risk groups for symptom deterioration during a pandemic and when assessing its possible long-term effects of such.

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OBJECTIVE: To identify potential barriers to care, this study examined the general psychiatry outpatient new appointment availability in the US, including in-person and telepsychiatry appointments, comparing results between insurance types (Medicaid vs. private insurance), states, and urbanization levels. METHOD: This mystery shopper study investigated 5 US states selected according to Mental Health America Adult Ranking and geography to represent the US mental health care system. Clinics across five selected states were stratified sampled by county urbanization levels. Calls were made during 05/2022-07/2022. Collected data included contact information accuracy, appointment availability, wait time (days), and related information. RESULTS: Altogether, 948 psychiatrists were sampled in New York, California, North Dakota, Virginia, and Wyoming. Overall contact information accuracy averaged 85.3%. Altogether, 18.5% of psychiatrists were available to see new patients with a significantly longer wait time for in-person than telepsychiatry appointments (median = 67.0 days vs median = 43.0 days, p < 0.01). The most frequent reason for unavailability was provider not taking new patients (53.9%). Mental health resources were unevenly distributed, favoring urban areas. CONCLUSION: Psychiatric care has been severely restricted in the US with low accessibility and long wait times. Transitioning to telepsychiatry represents a potential solution for rural disparities in access.

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INTRODUCTION: The COVID-19 pandemic has propelled a global paradigm shift in how psychological support is delivered. Remote delivery, through phone and video calls, is now commonplace around the world. However, most adoption of remote delivery methods is occurring without any formal training to ensure safe and effective care. OBJECTIVE: The purpose of this applied qualitative study was to determine practitioners' experiences of rapidly adapting to deliver psychological support remotely during COVID-19. DESIGN: We used a pragmatic paradigm and applied approach to gain perspectives related to the feasibility and perceived usefulness of synchronous remote psychological support, including views on how practitioners can be prepared. METHODS: Key informant interviews were conducted remotely with 27 specialist and non-specialist practitioners in Nepal, Perú and the USA. Interviewees were identified through purposeful sampling. Data were analysed using framework analysis. RESULTS: Respondents revealed three key themes: (i) Remote delivery of psychological support raises unique safety concerns and interference with care, (ii) Remote delivery enhances skills and expands opportunities for delivery of psychological support to new populations, and (iii) New training approaches are needed to prepare specialist and non-specialist practitioners to deliver psychological support remotely. CONCLUSIONS: Remote psychological support is feasible and useful for practitioners, including non-specialists, in diverse global settings. Simulated remote role plays may be a scalable method for ensuring competency in safe and effective remotely-delivered care.

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COVID-19 has caused an epidemic in the entire world and it is caused by the novel virus SARS-COV-2. In severe conditions, this virus can cause a critical lung infection or viral pneumonia. To administer the correct treatment to patients, COVID-19 testing is important for diagnosing and determining patients who are infected with COVID-19, as opposed to those infected with other bacterial or viral infections. In this paper, a CResNeXt chest radiograph COVID-19 prediction model is proposed using residual network architecture. The advantage of the proposed model is that it requires lesser free hyper-parameters as compared to other residual networks. In addition, the training time per epochs of the model is very less compared to VGG19, ResNet-50, ResNeXt. The proposed CResNeXt model's binary classification (COVID-19 versus No-Finding) accuracy is observed to be 98.63% and 99.99% and multi-class classification (COVID-19, Pneumonia, and No-Finding) accuracy is observed to be 97.42% and 99.27% on the original and augmented datasets, respectively.

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OBJECTIVES: The CytoSorb therapy in COVID-19 (CTC) registry evaluated the clinical performance and treatment parameters of extracorporeal hemoadsorption integrated with veno-venous extracorporeal membrane oxygenation (VV ECMO) in critically ill COVID-19 patients with acute respiratory distress syndrome (ARDS) and respiratory failure under US FDA Emergency Use Authorization. DESIGN: Multicenter, observational, registry (NCT04391920). SETTING: Intensive care units (ICUs) in five major US academic centers between April 2020 and January 2022. PATIENTS: A total of 100 critically ill adults with COVID-19-related ARDS requiring VV ECMO support, who were treated with extracorporeal hemoadsorption. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Baseline demographics, clinical characteristics, laboratory values and outcomes were recorded following individual ethics committee approval at each center. Detailed data on organ support utilization parameters and hemoadsorption treatments were also collected. Biomarker data were collected according to the standard practice at each participating site, and available values were compared before and after hemoadsorption. The primary outcome of mortality was evaluated using a time-to-event analysis. A total of 100 patients (63% male; age 44 ± 11 years) were included. Survival rates were 86% at 30 days and 74% at 90 days. Median time from ICU admission to the initiation of hemoadsorption was 87 h and was used to define two post hoc groups: ≤ 87 h (group-early start, GE) and > 87 h (group-late start, GL). After the start of hemoadsorption, patients in the GE versus GL had significantly shorter median duration of mechanical ventilation (7 [2-26] vs. 17 [7-37] days, p = 0.02), ECMO support (13 [8-24] vs. 29 [14-38] days, p = 0.021) and ICU stay (17 [10-40] vs 36 [19-55] days, p = 0.002). Survival at 90 days in GE was 82% compared to 66% in GL (p = 0.14). No device-related adverse events were reported. CONCLUSIONS: In critically ill patients with severe COVID-19-related ARDS treated with the combination of VV-ECMO and hemoadsorption, 90-day survival was 74% and earlier intervention was associated with shorter need for organ support and ICU stay. These results lend support to the concept of "enhanced lung rest" with the combined use of VV-ECMO plus hemoadsorption in patients with ARDS.

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COVID-19 has been a global pandemic. Flattening the curve requires intensive testing, and the world has been facing a shortage of testing equipment and medical personnel with expertise. There is a need to automate and aid the detection process. Several diagnostic tools are currently being used for COVID-19, including X-Rays and CT-scans. This study focuses on detecting COVID-19 from X-Rays. We pursue two types of problems: binary classification (COVID-19 and No COVID-19) and multi-class classification (COVID-19, No COVID-19 and Pneumonia). We examine and evaluate several classic models, namely VGG19, ResNet50, MobileNetV2, InceptionV3, Xception, DenseNet121, and specialized models such as DarkCOVIDNet and COVID-Net and prove that ResNet50 models perform best. We also propose a simple modification to the ResNet50 model, which gives a binary classification accuracy of 99.20% and a multi-class classification accuracy of 86.13%, hence cementing the ResNet50's abilities for COVID-19 detection and ability to differentiate pneumonia and COVID-19. The proposed model's explanations were interpreted via LIME which provides contours, and Grad-CAM, which provides heat-maps over the area(s) of interest of the classifier, i.e., COVID-19 concentrated regions in the lungs, and realize that LIME explains the results better. These explanations support our model's ability to generalize. The proposed model is intended to be deployed for free use.

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OBJECTIVE: This study was designed to assess the effects of the coronavirus disease pandemic on job satisfaction (JS) and burnout among surgical sub-specialty residents. DESIGN: This is a retrospective, observational, survey-based study. We administered a web-based questionnaire to surgical sub-specialty residents, and results were compared to a prior study in 2016. The questionnaire included elements on demographics, JS, burnout, and self-care habits. Basic statistical analyses were used to compare data from 2020 and 2016. SETTING: This study takes place at Robert Wood Johnson University Hospital, a single mid-sized New Jersey-based academic institution. PARTICIPANTS: This survey was sent to all obstetrics and gynecology and general surgery residents from every postgraduate year based out of our institution. The survey was sent to a total of 50 residents across the 2 programs. Forty total residents responded to the survey, with a response rate of 80%. RESULTS: JS was significantly higher in 2020 than 2016 (p < 0.001). There were no differences between postgraduate years for 2020 or 2016 in emotional exhaustion (p = 0.29, p = 0.75), personal accomplishment (p = 0.88, p = 0.26), or depersonalization (p = 0.14, p = 0.59) burnout scores. A total of 0% of residents in 2020 worked fewer than 61 hours per week. Residents in 2020 exercised more (40.0% vs 21.6%), had similar alcohol usage (60%), and had similar diets to residents in 2016. Residents in 2020 were less likely to regret their specialty (7.5% vs 21.6%), consider changing residencies (30.0% vs 37.8%), or consider a career change (15.0% vs 45.9%). CONCLUSIONS: JS scores were significantly higher during the coronavirus disease pandemic. The cancellation of elective surgeries led to a lighter workload for surgical residents. Residents were uncertain of their role during the pandemic, however, new stressors encouraged residents to seek alternative methods for personal wellness.

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Introduction: In the first wave of the COVID-19 pandemic, the unknown etiology and treatment of the highly transmissible coronavirus posed considerable threats to public mental health. Many people around the globe turned to religion as an attempt to mitigate their heightened psychological distress, but mixed findings have been obtained regarding the association between the use of religious coping and two psychological symptoms-anxiety and depressive symptoms-widely reported in the initial wave. Objective: The present meta-analysis was conducted to resolve the empirical inconsistency by synthesizing this body of studies and identifying both individual and national-level factors that accounted for the inconsistent findings. Methods: Following PRISMA guidelines, the literature search and data screening procedures yielded 42 eligible studies, with 25,438 participants (58% females, average age = 36.50 years) from 24 countries spanning seven world regions. Results: Overall, the results showed that only negative religious coping was positively associated with psychological symptoms (r = 0.2886, p < 0.0001). Although the associations of both general and positive religious coping with psychological symptoms were non-significant (rs = 0.0425 and -0.0240, ps > 0.39), the moderation analysis revealed significant positive associations between positive religious coping and psychological symptoms in two demographic groups who experienced greater pandemic distress than their counterparts: younger participants and female participants. Discussion: This meta-analysis provides a nuanced understanding of the complex nature of religious coping in the initial wave of the COVID-19 pandemic when the levels of public anxiety and stress were heightened. The exclusive use of religious coping may not be associated with low levels of psychological symptoms, implying the importance of supplementing the deployment of this strategy with an array of other strategies. Therapists of mental health interventions should show their clients how to make good use of positive religious coping together with other strategies, and how to avoid the use of negative religious coping, to handle their psychological problems. Systematic review registration: https://osf.io/shb32/.

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COVID-19 is a severe respiratory contagious disease that has now spread all over the world. COVID-19 has terribly impacted public health, daily lives and the global economy. Although some developed countries have advanced well in detecting and bearing this coronavirus, most developing countries are having difficulty in detecting COVID-19 cases for the mass population. In many countries, there is a scarcity of COVID-19 testing kits and other resources due to the increasing rate of COVID-19 infections. Therefore, this deficit of testing resources and the increasing figure of daily cases encouraged us to improve a deep learning model to aid clinicians, radiologists and provide timely assistance to patients. In this article, an efficient deep learning-based model to detect COVID-19 cases that utilizes a chest X-ray images dataset has been proposed and investigated. The proposed model is developed based on ResNet50V2 architecture. The base architecture of ResNet50V2 is concatenated with six extra layers to make the model more robust and efficient. Finally, a Grad-CAM-based discriminative localization is used to readily interpret the detection of radiological images. Two datasets were gathered from different sources that are publicly available with class labels: normal, confirmed COVID-19, bacterial pneumonia and viral pneumonia cases. Our proposed model obtained a comprehensive accuracy of 99.51% for four-class cases (COVID-19/normal/bacterial pneumonia/viral pneumonia) on Dataset-2, 96.52% for the cases with three classes (normal/ COVID-19/bacterial pneumonia) and 99.13% for the cases with two classes (COVID-19/normal) on Dataset-1. The accuracy level of the proposed model might motivate radiologists to rapidly detect and diagnose COVID-19 cases.

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This paper reports on a study conducted by college students at a private university in Saudi Arabia. The research examines the online learning experiences of their peers during the first wave of the coronavirus covid-19 pandemic. Many assumptions exist about online learning and its impact in higher education, but these are mainly based on the views of instructors and leaders of institutions. Hitherto, the perspectives of those meant to be beneficiaries of digital technologies have been given little consideration even though students use cyberspace for academic work and beyond. To address this silence, a group of student-researchers conducted a case study to examine students' views of cyberlearning. The research used a qualitative analysis approach to address the following questions: (1) What were the cyberlearning experiences of students at our university during the first two semesters of lockdown? (2) What are students' understandings of cyberlearning? (3) What are their aspirations for cyberlearning? Data were collected through an online survey administered to the entire student body at the university. Responses were received from 3574 students. The data were analysed using thematic analysis. The research participants perceive cyberlearning to be the same as online learning and see it as a viable educational option. They reported that the dominant mode of instruction in online classrooms is instructors delivering information. Respondents also highlighted the need for improved online teaching pedagogies and curbing academic dishonesty in online classrooms. Students' aspirations for cyberlearning were clearly articulated. Respondents suggested that increasing online learning opportunities would have a positive impact on their academic progress. Through this research students demonstrate a sense of agency and provide opportunities for equity strategies at their university. The results show that serious attempts should be made to include cyberlearning as part of everyday educational activity in an attempt to increase student engagement.

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This article describes racial and ethnic differences in mortgage payment difficulties during the COVID-19 pandemic and examines whether disparities exist in the benefits of the unemployment insurance (UI) program. The sample consisted of 80,797 jobless mortgage borrowers who received or waited for UI benefits between August 2020 and May 2022. Considering individual- and state-level variables in multilevel logistic regressions, we examined rates of mortgage delay in the last month and payment concerns about the next month by racial and ethnic group. Minority borrowers were more likely to have a difficulty in paying mortgage than White borrowers. UI recipients-regardless of race and ethnicity-were less likely to experience mortgage difficulties, but the positive unemployment benefit was reduced disproportionately among Blacks. Blacks were also at a higher risk of mortgage difficulties compounded by other pandemic-induced hardships-loss of household, lack of food, and mental illness-even after the receipt of UI. Findings on the intersection between race and ethnicity and UI suggest that pandemic policy interventions should be race conscious and consider the longstanding and systematic barriers experienced by minority mortgage borrowers. Supplementary Information: The online version contains supplementary material available at 10.1007/s10901-022-10006-w.

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In the past two years, coronavirus pandemic has severely impacted global industries and altered market dynamics. The present study compares the challenges facing Indian textile and apparel industry before and after the coronavirus pandemic. The context of our study focuses on handloom industry, as the primary financial risk for handloom micro entrepreneurs lies in capital requirements for raw materials, equipment and their lack of formal management structures to tackle the pressure of uncertainty. Thus, studying and mitigating internal and external barriers of the traditional manufacturing micro entrepreneurs during and post pandemic remains crucial to frame policy decisions for sustainability of this vulnerable sector. We have employed a two-phase (before and after the onset of pandemic) successive exploratory mixed method, starting with the Delphi technique (qualitative phase) and concluding with multi-criteria decision-making. In Phase 2 analysis, seventeen key critical barriers identified in Phase 1reduced to twelve. Phase 1 modelling suggests that lack of effective government policies, demonetization, and tax policy implementation are the most significant barriers. Further, Phase 2 identifies the absence of effective government policies as the most significant obstacle to the performance of Indian handloom industry, especially after the pandemic. Additionally, lack of branding was found to be most critically linked between independent and dependent barriers.