Defining Radiation Treatment Interruption Rates During the COVID-19 Pandemic: Findings From an Academic Center in an Underserved Urban Setting.

PURPOSE: Our purpose was to characterize radiation treatment interruption (RTI) rates and their potential association with sociodemographic variables in an urban population before and during the COVID-19 pandemic. METHODS AND MATERIALS: Electronic health records were retrospectively reviewed for patients treated between January 1, 2015, and February 28, 2021. Major and minor RTI were defined as ≥5 and 2 to 4 unplanned cancellations, respectively. RTI was compared across demographic and clinical factors and whether treatment started before or after COVID-19 onset (March 15, 2020) using multivariate logistic regression analysis. RESULTS: Of 2240 study cohort patients, 1938 started treatment before COVID-19 and 302 started after. Patient census fell 36% over the year after COVID-19 onset. RTI rates remained stable or trended downward, although subtle shifts in association with social and treatment factors were observed on univariate and multivariate analysis. Interaction of treatment timing with risk factors was modest and limited to treatment length and minor RTI. Despite the stability of cohort-level findings showing limited associations with race, geospatial mapping demonstrated a discrete geographic shift in elevated RTI toward Black, underinsured patients living in inner urban communities. Affected neighborhoods could not be predicted quantitatively by local COVID-19 transmission activity or social vulnerability indices. CONCLUSIONS: This is the first United States institutional report to describe radiation therapy referral volume and interruption patterns during the year after pandemic onset. Patient referral volumes did not fully recover from an initial steep decline, but local RTI rates and associated risk factors remained mostly stable. Geospatial mapping suggested migration of RTI risk toward marginalized, minority-majority urban ZIP codes, which could not otherwise be predicted by neighborhood-level social vulnerability or pandemic activity. These findings signal that detailed localization of highest-risk communities could help focus radiation therapy access improvement strategies during and after public health emergencies. However, this will require replication to validate and broaden relevance to other settings.

DACov: A Deeper Analysis of Data Augmentation on the Computed Tomography Segmentation Problem (preprint)

Due to the COVID-19 global pandemic, computer-assisted diagnoses of medical images have gained much attention, and robust methods of semantic segmentation of Computed Tomography (CT) images have become highly desirable. In this work, we present a deeper analysis of how data augmentation techniques improve segmentation performance on this problem. We evaluate 20 traditional augmentation techniques on five public datasets. Six different probabilities of applying each augmentation technique on an image were evaluated. We also assess a different training methodology where the training subsets are combined into a single larger set. All networks were evaluated through a 5-fold cross-validation strategy, resulting in over 4,600 experiments. We also propose a novel data augmentation technique based on Generative Adversarial Networks (GANs) to create new healthy and unhealthy lung CT images, evaluating four variations of our approach with the same six probabilities of the traditional methods. Our findings show that GAN-based techniques and spatial-level transformations are the most promising for improving the learning of deep models on this problem, with the StarGANv2 + F with a probability of 0.3 achieving the highest F-score value on the Ricord1a dataset in the unified training strategy. Our code is publicly available at https://github.com/VRI-UFPR/DACov2022

Characteristics, Treatment Patterns, and Clinical Outcomes After Heart Failure Hospitalizations During the COVID-19 Pandemic, March to October 2020.

OBJECTIVE: To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. PATIENTS AND METHODS: The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames. RESULTS: The adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05). CONCLUSION: The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame.

Suicidal Ideation Amongst University Students During the COVID-19 Pandemic: Time Trends and Risk Factors.

OBJECTIVE: Examine time trends in suicidal ideation in post-secondary students over the first three waves of the COVID-19 pandemic in Canada and identify subpopulations of students with increased risk. METHOD: We analysed 14 months of data collected through repeated cross-sectional deployment of the World Health Organization (WHO) World Mental Health-International College Student (WMH-ICS) survey at the University of British Columbia. Estimated log odds weekly trends of 30-day suicidal ideation (yes/no) were plotted against time with adjustments for demographics using binary logistic generalized additive model (GAM). Risk factors for 30-day suicidal ideation frequency (four categories) were examined using the ordered logistic GAM, with a cubic smoothing spline for modelling time trend in obervation weeks and accounting for demographics. RESULTS: Nearly one-fifth (18.9%) of students experienced suicidal ideation in the previous 30 days. While the estimated log odds suggested that binary suicidal ideation was relatively stable across the course of the pandemic, an initial drop followed by an increasing trend was observed. Risk factors for suicidal ideation frequency during the pandemic included identifying as Chinese or as another non-Indigenous ethnic minority; experiencing current symptoms of depression or anxiety; having a history of suicidal planning or attempts; and feeling overwhelmed but unable to get help as a result of COVID-19. Older age was identified as a protective factor. CONCLUSIONS: The general university student population in our study was relatively resilient with respect to suicidal ideation during the first three waves of the pandemic, but trends indicate the possibility of delayed impact. Specific sub-populations were found to be at increased risk and should be considered for targeted support. Further analyses should be undertaken to continue monitoring suicidality trends throughout the remainder of the pandemic and beyond.

Five-Year Follow-Up of a Phase 1 Trial of Donor-Derived Modified Immune Cell Infusion in Kidney Transplantation

Background: The administration of modified immune cells (MIC) prior to kidney transplantation led to specific immunosuppression against the allogeneic donor and a significant increase in regulatory B lymphocytes (Breg) (Morath et al., J Clin Invest 2020). We now wanted to investigate how this approach affects the clinical course of treated patients. Method(s): Clinical results of ten patients from a phase I clinical trial who had received MIC infusions before kidney transplantation were compared to results of 15 matched standard-risk recipients. Follow-up was until year five after surgery. Result(s): The 10 MIC patients had an excellent clinical course with stable kidney graft function and showed no donor-specific human leukocyte antigen antibodies (DSA) or acute rejections during follow-up. In contrast, 1 of 15 controls died and 5 of 15 controls developed DSA (log rank P = 0.046) (Figure 1 A, B). While the number of patients with a non-opportunistic infection did not differ significantly between groups (P = 0.36), opportunistic infections were reported more frequently in controls (log rank P = 0.033) (Figure 1 C). Compared to controls, MIC patients were found to have a trend towards a higher COVID-19 anti-S1 IgG index after vaccination with a median of 53 vs. 2 (P = 0.16). Importantly, the four MIC patients who had received the highest MIC cell dose 7 days before surgery and were on low immunosuppression during follow-up, continued to show absent anti-donor T lymphocyte reactivity in vitro and high CD19+CD24hiCD38hi transitional Breg as well as CD19+CD24hiCD27+ memory Breg. Conclusion(s): MIC infusions together with reduced conventional immunosuppression were associated with lower de novo DSA development and lower rates of opportunistic infections. In the future, MIC infusions could contribute to graft protection while reducing the side effects of immunosuppressive therapy. (Figure Presented).

Online counterconditioning with COVID-19-relevant stimuli in lockdown: Impact on threat expectancy, fear, and persistent avoidance.

BACKGROUND AND OBJECTIVES: In counterconditioning, a conditioned aversive stimulus (CS) is paired with an appetitive stimulus to reduce fear and avoidance. Findings are, however, mixed on the relative impact of counterconditioning versus standard extinction, where the CS is presented in the absence of the aversive event. This analogue treatment study investigated the impact of counterconditioning relative to standard extinction on threat expectancy, fear, and persistent avoidance with an online fear-conditioning task conducted with COVID-19-relevant appetitive stimuli during the pandemic. METHODS: Following habituation, in which two CSs (male faces wearing face-coverings) were presented in the absence of the unconditioned stimulus (US; a loud female scream), participants (n = 123) underwent threat-conditioning where one stimulus (CS+) was followed by the US and another (CS-) was not. In avoidance learning, the US could be prevented by making a simple response in the presence of the CS+. Next, participants received either counterconditioning in which trial-unique positively rated images of scenes from before the COVID-19 pandemic and its associated restrictions (e.g., hugging others and holding hands) were presented with the CS + or no-counterconditioning (i.e., extinction). In the final test phase, avoidance was available, and all US deliveries were withheld. RESULTS: Counterconditioning led to diminished threat expectancy and reduced avoidance relative to no-counterconditioning. Fear ratings did not differ between groups. LIMITATIONS: No physiological measures were obtained. CONCLUSIONS: Implemented online during the pandemic with COVID-19-relevant appetitive stimuli, counterconditioning was effective at reducing persistent avoidance and threat expectancy.

Longitudinal assessment of COVID-19 fear and psychological wellbeing in the United Kingdom.

The COVID-19 pandemic continues to impact global psychological wellbeing. To investigate the sustained impact of COVID-19 on wellbeing, the current study longitudinally assessed fear of COVID-19, anxiety, depression, intolerance of uncertainty, worry, sleep quality, loneliness and alcohol use during the pandemic in the United Kingdom. Timepoint 1 (T1; N = 445) took place in February 2021 following the highest number of pandemic-related deaths in the UK. Timepoint 2 (T2, N = 198) took place in June 2021 when pandemic-related deaths had declined considerably, and many had been vaccinated. At T1, COVID-19 fear predicted elevated levels of anxiety, depression, intolerance of uncertainty, worry, sleep quality and loneliness. At T2, we observed that levels of COVID-19 fear, depression, loneliness and sleep quality decreased. However, COVID-19 fear continued to predict elevated intolerance of uncertainty, worry and impaired sleep quality. These findings demonstrate the longitudinal impact of COVID-19 fear on psychological wellbeing.

The World Mental Health International College Student Survey in Canada: Protocol for a Mental Health and Substance Use Trend Study.

BACKGROUND: The World Health Organization World Mental Health International College Student (WMH-ICS) initiative aims to screen for mental health and substance use problems among postsecondary students on a global scale as well as to develop and evaluate evidence-based preventive and ameliorative interventions for this population. This protocol paper presents the Canadian version of the WMH-ICS survey, detailing the adapted survey instrument, the unique weekly cross-sectional administration, the multitiered recruitment strategy, and the associated risk mitigation protocols. OBJECTIVE: This paper aims to provide a methodological resource for researchers conducting cross-national comparisons of WMH-ICS data, as well as to serve as a useful guide for those interested in replicating the outlined cross-sectional methodology to better understand how mental health and substance use vary over time among university students. METHODS: The online survey is based on the WMH-ICS survey instrument, modified to the Canadian context by the addition of questions pertaining to Canadian-based guidelines and the translation of the survey to Canadian French. The survey is administered through the Qualtrics survey platform and is sent to an independent stratified random sample of 350 students per site weekly, followed by two reminder emails. Upon survey closure every week, a random subsample of 70 nonresponders are followed up with via phone or through a personal email in an effort to decrease nonresponder bias. The survey is accompanied by an extensive risk mitigation protocol that stratifies respondents by the level of need and provides tailored service recommendations, including a facilitated expedited appointment to student counseling services for those at increased risk of suicide. The anticipated sample size is approximately 5500 students per site per year. RESULTS: In February 2020, the Canadian survey was deployed at the University of British Columbia. This was followed by deployment at Simon Fraser University (November 2020), McMaster University (January 2021), and the University of Toronto (January 2022). Data collection at all 4 sites is ongoing. As of May 6, 2022, 29,503 responses have been collected. CONCLUSIONS: Based on international collaboration, the Canadian version of the WMH-ICS survey incorporates a novel methodological approach centered on the weekly administration of a comprehensive cross-sectional survey to independent stratified random samples of university students. After 27 months of consecutive survey administration, we have developed and refined a survey protocol that has proven effective in engaging students at four Canadian institutions, allowing us to track how mental health and substance use vary over time using an internationally developed university student survey based on the criteria from the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/35168.

Impact of the COVID-19 Pandemic on Canadian Radiation Oncology Practices.

PURPOSE: To survey Canadian radiation oncology (RO) practice leaders to determine the effect of the COVID-19 pandemic on radiation services and patient and staff issues in the early phase of the pandemic and 1 year later. METHODS AND MATERIALS: The RO leader (department or division head) from every Canadian cancer center with radiation services was identified. Two surveys were circulated to the identified leader via email from the Canadian Association of Radiation Oncology central office, using the SurveyMonkey survey tool: the first closed in June 2020 and the second (expanded) survey in June 2021, representing 2 points in time of the COVID-19 pandemic. Questions included patient volume, service interruptions and delays, and changes in scheduling and telemedicine use. Additional questions were included in the follow-up survey to determine further effects on disease presentation, volume, vaccination and access, and personnel issues. RESULTS: Telemedicine was widely adopted early in the pandemic and continued to be a common technique to communicate and connect with patients. Although many centers were deferring or delaying certain disease sites early in the pandemic, this was not as prevalent 1 year later. Reduced cancer screening and patients presenting with more advanced disease were concerns documented in the 2021 survey. A high level of concern regarding stress among health care professionals was identified. CONCLUSIONS: Canadian RO centers have faced numerous challenges during the COVID-19 pandemic but continued to provide timely and essential cancer care for patients with cancer. Future evaluation of RO center practices will be important to continue to document and address the effect of the COVID-19 pandemic on issues relevant to RO leaders, patients, and staff.

Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic Segmentation (preprint)

With the COVID-19 global pandemic, computer-assisted diagnoses of medical images have gained much attention, and robust methods of Semantic Segmentation of Computed Tomography (CT) became highly desirable. Semantic Segmentation of CT is one of many research fields of automatic detection of COVID-19 and has been widely explored since the COVID-19 outbreak. In this work, we propose an extensive analysis of how different data augmentation techniques improve the training of encoder-decoder neural networks on this problem. Twenty different data augmentation techniques were evaluated on five different datasets. Each dataset was validated through a five-fold cross-validation strategy, thus resulting in over 3,000 experiments. Our findings show that spatial level transformations are the most promising to improve the learning of neural networks on this problem.

Remote, online assessment of avoidance learning

Avoidance is an adaptive response to actual or perceived threat. However, persistent avoidance despite low likelihood of threat can become maladaptive and prevent effective psychological treatment. To examine behavioural avoidance, in-person, lab-based threat learning paradigms are typically used with relatively small sample sizes. However, such methods pose issues when in-person testing is difficult. The aim of the current study was therefore to adapt a validated lab-based threat and avoidance conditioning paradigm into an online avoidance learning task to investigate threat expectancy and avoidance remotely during the COVID-19 pandemic. An online fear and avoidance learning task was developed and administered to 119 participants who differed in the opportunity to avoid a safe stimulus. Fear and avoidance conditioning were successful and the opportunity to avoid a known safe stimulus increased threat expectancy and fear for the experimental group, relative to the control group. Such remote delivery paradigms may therefore be useful when evaluating changes in fear and avoidance

Hydroxychloroquine versus placebo in the treatment of non-hospitalised patients with COVID-19 (COPE - Coalition V): A double-blind, multicentre, randomised, controlled trial.

Background: Previous Randomised controlled trials (RCT) evaluating chloroquine and hydroxychloroquine in non-hospitalised COVID-19 patients have found no significant difference in hospitalisation rates. However, low statistical power precluded definitive answers. Methods: We conducted a multicenter, double-blind, RCT in 56 Brazilian sites. Adults with suspected or confirmed COVID-19 presenting with mild or moderate symptoms with ≤ 07 days prior to enrollment and at least one risk factor for clinical deterioration were randomised (1:1) to receive hydroxychloroquine 400 mg twice a day (BID) in the first day, 400 mg once daily (OD) thereafter for a total of seven days, or matching placebo. The primary outcome was hospitalisation due to COVID-19 at 30 days, which was assessed by an adjudication committee masked to treatment allocation and following the intention-to-treat (ITT) principle. An additional analysis was performed only in participants with SARS-CoV-2 infection confirmed by molecular or serology testing (modified ITT [mITT] analysis). This trial was registered at ClinicalTrials.gov, NCT04466540. Findings: From May 12, 2020 to July 07, 2021, 1372 patients were randomly allocated to hydroxychloroquine or placebo. There was no significant difference in the risk of hospitalisation between hydroxychloroquine and placebo groups (44/689 [6·4%] and 57/683 [8·3%], RR 0·77 [95% CI 0·52-1·12], respectively, p=0·16), and similar results were found in the mITT analysis with 43/478 [9·0%] and 55/471 [11·7%] events, RR 0·77 [95% CI 0·53-1·12)], respectively, p=0·17. To further complement our data, we conducted a meta-analysis which suggested no significant benefit of hydroxychloroquine in reducing hospitalisation among patients with positive testing (69/1222 [5·6%], and 88/1186 [7·4%]; RR 0·77 [95% CI 0·57-1·04]). Interpretation: In outpatients with mild or moderate forms of COVID-19, the use of hydroxychloroquine did not reduce the risk of hospitalisation compared to the placebo control. Our findings do not support the routine use of hydroxychloroquine for treatment of COVID-19 in the outpatient setting. Funding: COALITION COVID-19 Brazil and EMS.

Variable Effect of the COVID-19 Pandemic on Radiation Oncology Practices in the United States.

PURPOSE: Early in the pandemic, the American Society for Radiation Oncology surveyed physician leaders at radiation oncology practices in the United States to understand how the field was responding to the outbreak of COVID-19. METHODS AND MATERIALS: Surveys were repeated at multiple points during the pandemic, with a response rate of 43% in April 2020 and 23% in January 2021. To our knowledge, this is the only longitudinal COVID-19 practice survey in oncology in the United States. RESULTS: The surveys indicate that patient access to essential radiation oncology services in the United States has been preserved throughout the COVID-19 pandemic. Safety protocols were universally adopted, telehealth was widely adopted and remains in use, and most clinics no longer deferred or postponed radiation treatments as of early 2021. Late-stage disease presentation, treatment interruptions, shortages of personal protective equipment, and vaccination barriers were reported significantly more at community-based practices than at academic practices, and rural practices appear to have faced increased obstacles. CONCLUSIONS: Our findings provide unique insights into the initial longitudinal effect of the COVID-19 pandemic on the delivery of radiation therapy in the United States. Downstream lessons in service adaptation and improvement can potentially be guided by formal concepts of resilience, which have been broadly embraced across the US economy.

Extracellular Vimentin as a Target Against SARS-CoV-2 Host Cell Invasion.

Infection of human cells by pathogens, including SARS-CoV-2, typically proceeds by cell surface binding to a crucial receptor. The primary receptor for SARS-CoV-2 is the angiotensin-converting enzyme 2 (ACE2), yet new studies reveal the importance of additional extracellular co-receptors that mediate binding and host cell invasion by SARS-CoV-2. Vimentin is an intermediate filament protein that is increasingly recognized as being present on the extracellular surface of a subset of cell types, where it can bind to and facilitate pathogens' cellular uptake. Biophysical and cell infection studies are done to determine whether vimentin might bind SARS-CoV-2 and facilitate its uptake. Dynamic light scattering shows that vimentin binds to pseudovirus coated with the SARS-CoV-2 spike protein, and antibodies against vimentin block in vitro SARS-CoV-2 pseudovirus infection of ACE2-expressing cells. The results are consistent with a model in which extracellular vimentin acts as a co-receptor for SARS-CoV-2 spike protein with a binding affinity less than that of the spike protein with ACE2. Extracellular vimentin may thus serve as a critical component of the SARS-CoV-2 spike protein-ACE2 complex in mediating SARS-CoV-2 cell entry, and vimentin-targeting agents may yield new therapeutic strategies for preventing and slowing SARS-CoV-2 infection.

Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT's Semantic Segmentation (preprint)

With the COVID-19 global pandemic, computerassisted diagnoses of medical images have gained a lot of attention, and robust methods of Semantic Segmentation of Computed Tomography (CT) turned highly desirable. Semantic Segmentation of CT is one of many research fields of automatic detection of Covid-19 and was widely explored since the Covid19 outbreak. In the robotic field, Semantic Segmentation of organs and CTs are widely used in robots developed for surgery tasks. As new methods and new datasets are proposed quickly, it becomes apparent the necessity of providing an extensive evaluation of those methods. To provide a standardized comparison of different architectures across multiple recently proposed datasets, we propose in this paper an extensive benchmark of multiple encoders and decoders with a total of 120 architectures evaluated in five datasets, with each dataset being validated through a five-fold cross-validation strategy, totaling 3.000 experiments. To the best of our knowledge, this is the largest evaluation in number of encoders, decoders, and datasets proposed in the field of Covid-19 CT segmentation.

Mobile vs. Non-Mobile Live-Streaming: A Comparative Analysis of Users Engagement and Interruption Using Big Data from a Large CDN Perspective.

Video streaming on the Internet is constantly changing and growing. New devices and new video delivery mechanisms generate huge gaps in the understanding of how video application works. From exploratory research of one among the largest streaming services in Brazil, this work presents a comparison between mobile and non-mobile users, in large-scale lives. This work focuses on metrics such as engagement, interruption, churn, and payload. This work also presents a report-overview of mobile-users, considering the operating system, geolocation, network access, interruption, and engagement. These results might offer potential information for streaming improvement, in addition to serving as a historical mark.

Systematic SARS-CoV-2-testing for asymptomatic cancer patients treated at a public healthcare tertiary centre in Brazil.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has had enormous consequences in Brazil and worldwide. Patients with cancer affected by COVID-19 are at a higher risk of developing complications and worse outcomes compared to the non-cancer population, particularly the ones on active systemic treatment. Considering the COVID-19's high transmissibility in asymptomatic and pre-symptomatic patients, we sought to determine the prevalence of COVID-19 infection in patients with solid cancers receiving systemic therapy in a Brazilian public health hospital. Furthermore, we studied whether socio-economic status was associated with prevalence. METHODS: Consecutive asymptomatic patients undergoing treatment for solid tumours at the chemotherapy and infusion centre of Hospital de Base were enrolled. Patients were prospectively tested for severe acute respiratory syndrome coronavirus 2 RNA real-time polymerase chain reaction with nasal and oropharyngeal swabs immediately prior to treatment. A socio-economic survey was carried out prior to testing. Demographic and socio-economic characteristics were summarised in means, medians and proportions. RESULTS: From 6 to 13 October 2020, 148 asymptomatic patients were identified. Of those, 41 were excluded, leaving 107 eligible patients. The mean age of the population was 58 years (SD ± 12.6); 54% were female and 90% were self-identified as White. The most common cancer sites were gastrointestinal tract (36%) and breast (25%). Most patients had a metastatic disease (59%) and were on anticancer treatment involving chemotherapy (95%). Regarding socio-economic status, 46% of our population had either primary school or illiterate as their highest educational level. In terms of monthly income, 92% had a personal income inferior to U$380 and 88% a household income inferior to U$585. Of the 107 patients tested, only 1 (0.9%) was positive for COVID-19. This is a 48-year-old man living in an urban area, with primary school educational level and a monthly personal income inferior to U$390. CONCLUSION: Despite a high prevalence of COVID-19 in Brazil, our cohort demonstrated a low prevalence of COVID-19 (0.9%) amongst asymptomatic patients with cancer. We hypothesise that patients with cancer, independent of their socio-economic status, are aware of the increased risk of developing a severe disease and are adherent to physical distancing, masking and hygiene measures.

Assessing the impact of air pollution and climate seasonality on COVID-19 multiwaves in Madrid, Spain.

While the COVID-19 pandemic is still in progress, being under the fifth COVID-19 wave in Madrid, over more than one year, Spain experienced a four wave pattern. The transmission of SARS-CoV-2 pathogens in Madrid metropolitan region was investigated from an urban context associated with seasonal variability of climate and air pollution drivers. Based on descriptive statistics and regression methods of in-situ and geospatial daily time series data, this study provides a comparative analysis between COVID-19 waves incidence and mortality cases in Madrid under different air quality and climate conditions. During analyzed period 1 January 2020-1 July 2021, for each of the four COVID-19 waves in Madrid were recorded anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere and favorable stability conditions for COVID-19 disease fast spreading. As airborne microbial temporal pattern is most affected by seasonal changes, this paper found: 1) a significant negative correlation of air temperature, Planetary Boundary Layer height, and surface solar irradiance with daily new COVID-19 incidence and deaths; 2) a similar mutual seasonality with climate variables of the first and the fourth COVID-waves from spring seasons of 2020 and 2021 years. Such information may help the health decision makers and public plan for the future.

Religion in the US during the time of a Pandemic: A Medical Perspective.

Approximately 80% of Americans identify as religious. As physicians caring for patients with COVID-19, we have seen both positive and negative effects of religious activity during the pandemic. Religious worship generally supports close social interaction, which provides many benefits, especially in mental health, but it can also contradict infection control measures. These forces do not necessarily have to be in opposition to each other. Herein, we present three case vignettes of religious patients who were infected with and recovered from COVID-19. We review the potential benefits and risks of religious activity in the current pandemic, as supported by the medical literature. Finally, we offer some thoughts on how to engage with patients so that the benefits of both religious activity and public health measures are optimized.