Vaccination after recovery from COVID-19 affects nasal antibody levels

Introduction: Vaccines prevent severe disease, but to prevent viral transmission and lessen the risk of new variants emerging they need to also enhance mucosal protection. Intramuscular (IM) vaccines induce systemic antibody and appear to transiently reduce transmission, but their effect on nasal antibody in previously infected subjects has not been studied. Aim(s): To study durability of local and systemic antibody responses after COVID-19 in those subsequently vaccinated. Method(s): Nasal fluid and plasma were collected from 448 hospitalised COVID-19 cases during admission and convalescence via the ISARIC4C/PHOSP-COVID studies. IgA/G to wildtype SARS-CoV-2 S, NP and to receptor binding domain (RBD) of Delta and Omicron variants were measured by ELISA. Result(s): Nasal IgA/G anti-S/RBD responses appeared within 28 days and remained high for 1 year(figure 1). Plasma IgA/G responses to S also remained elevated at 1 year(P<0.001). 87% of those with complete data were vaccinated between 6-12 months after infection;when nasal and plasma anti-NP IgA/G waned, whilst anti-S/RBD responses to Delta and Omicron were maintained or increased. Conclusion(s): This is the first study to demonstrate that IM vaccination may boost nasal antibody 1 year after COVID19. This may explain why IM vaccination reduces transmission, adding to the evidence for booster vaccines in COVID-19 recoverees. (Figure Presented).

Predicting hospital emergency department visits with deep learning approaches

Overcrowding in emergency department (ED) causes lengthy waiting times, reduces ade-quate emergency care and increases rate of mortality. Accurate prediction of daily ED visits and allocating resources in advance is one of the solutions to ED overcrowding problem. In this paper, a deep stacked architecture is being proposed and applied to the daily ED visits prediction problem with deep components such as Long Short Term Memory (LSTM), Gated Recurrent Units (GRU) and simple Recurrent Neural Network (RNN). The proposed architec-ture achieves very high mean accuracy level (94.28-94.59%) in daily ED visits predictions. We have also compared the performance of this architecture with non-stacked deep mod-els and traditional prediction models. The results indicate that deep stacked models out-perform (4-7%) the traditional prediction models and other non-stacked deep learning models (1-2%) in our prediction tasks. The application of deep neural network in ED visits prediction is novel as this is one of the first studies to apply a deep stacked architecture in this field. Importantly, our models have achieved better prediction accuracy (in one case comparable) than the state-of-the-art in the literature.(c) 2022 Published by Elsevier B.V. on behalf of Nalecz Institute of Biocybernetics and Bio-medical Engineering of the Polish Academy of Sciences.

LIGHTSITE III (Interim Analysis): Evaluation of Multiwavelength Photobiomodulation in Dry Age-Related Macular Degeneration Using the LumiThera Valeda Light Delivery System

Purpose : Dry age-related macular degeneration (AMD) is a leading contributor to visual impairment across the globe. No current treatment exists to improve visual function or reduce disease progression outside of vitamin supplementation and lifestyle changes. LIGHTSITE III is evaluating multiwavelength photobiomodulation (PBM) therapy using the LumiThera Valeda® Light Delivery System in dry AMD Methods : LIGHTSITE III (NCT04065490) is a prospective, double-masked, randomized, sham-controlled, parallel group, multi-center study to assess the safety and efficacy of PBM in dry AMD. Target enrollment was approximately 96 subjects (144 eyes). Subjects are treated with six series of PBM/Sham treatments (3x per week for 3 weeks) delivered over a 24-month period with a 13-month efficacy analysis of data. PBM therapy consists of low-level light exposure to selected tissues resulting in positive effects on mitochondrial output and improvement in cellular activity. Valeda is used to deliver multiwavelength PBM treatment using 590, 660 and 850 nm of light. Subjects are assessed for clinical and safety outcomes (i.e., best-corrected visual acuity (BCVA), low- luminance BCVA, contrast sensitivity, reading speed, color vision, VFQ-25 and perimetry). Independent OCT, FAF and color fundus imaging outcomes at selected timepoints are analyzed by a masked imaging reading center Results : A total of 148 eyes from 100 subjects with dry AMD have been enrolled and randomized in a 2:1 design (PBM:Sham). The majority of subjects are female (68%) and Caucasian (99%). The average age at enrollment was 75 years and mean time since dry AMD diagnosis is 4.9 years. COVID-19 interference has been minimal and not significantly impacted subject enrollment or retention. Clinical and anatomical outcome data from the interim analysis conducted at Month 13 is presented. Results from the 21-month time point are expected at end of 2022 Conclusions : LIGHTSITE III provides the largest, randomized controlled trial evaluating the effects of PBM in dry AMD subjects. PBM therapy may offer a new treatment strategy with a unique mechanism and modality for patients with dry AMD.

Implementation of corticosteroids in treatment of COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK: prospective, cohort study

Background Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. Methods We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. Findings Between June 17, 2020, and April 14, 2021, 47 795 (75.2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86.6%] of 12 909 vs 36 415 [72.4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0.79 [95% CI 0.70-0.89], p=0.0001, for 70-79 years;0.52 [0.46-0.58], p<0.0001, for >80 years), independent of patient demographics and illness severity. 84 (54.2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27.5% in the week before June 16, 2020, to 75-80% in January, 2021. Interpretation Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.

Early Outcomes of Elderly Hip Fracture Management during the COVID-19 Pandemic: A Report from the Philippines

Introduction: The multidisciplinary model of management for fragility hip fractures has only been recently introduced in the Philippines. Its development at the national and local level is made more difficult by the COVID-19 pandemic. To our knowledge, this is the first study to provide a comprehensive report on the clinical characteristics, current management and early outcomes of fragility hip fracture patients admitted during the COVID-19 pandemic in the setting of a country with an emerging economy. Methods: A multicenter prospective cohort study was conducted in the Philippines involving 12 hospitals from June 16, 2020 to February 28, 2021 during the Extended Community Quarantine Period during the COVID-19 pandemic. The clinico-demographic characteristics, treatments, and follow-up data at 30 days post-injury were gathered using the Research Electronic Data Capture (REDCAP) database system, using a minimum common data (MCD) which was adopted from the FFN MCD. Results: A total of 158 elderly patients (>60 years old) with fragility hip fractures were eligible for the study. 9 patients (5.7%) were confirmed or suspected to have COVID-19 infection. The median time of injury-to-admission was at least 3 (IQR: 1.0-13.7) days. 80% of the patients underwent surgical intervention with a median time from admission-to-surgery of at least 5 (IQR: 2.5-13.6) days. Notably, all non-COVID admitted patients had not been reported to have contracted the virus during their hospital stay. The 30-day mortality and morbidity rate for acute fragility fractures were 3.7%. Only the presence of a COVID-19 infection was found to be an independent and poor predictor for early mortality (P = 0.010). Conservatively managed patients had a significantly higher morbidity rate than surgically treated patients (13.6% vs 1.8%;P = 0.031). All five deaths occurred in non-surgical patients with an ASA grade of at least III. Conclusion: We recommend prompt admission and multidisciplinary care for elderly hip fracture patients even during the COVID-19 pandemic. Short-term outcomes remain favorable for non-COVID patients with acute fragility fractures treated with surgery. While a suspected or confirmed COVID-19 infection was the only significant and independent pre-operative risk factor for early mortality, there is evidence in the literature as well as in this study that the benefit of surgery may well outweigh the risk of conservatively treating COVID-19 patients provided that they can be optimized appropriately for surgery.

Disrupted Data: Using Longitudinal Assessment Systems to Monitor Test Score Quality

Technical documentation for educational tests focuses primarily on properties of individual scores at single points in time. Reliability, standard errors of measurement, item parameter estimates, fit statistics, and linking constants are standard technical features that external stakeholders use to evaluate items and individual scale scores. However, these cross-sectional, "point-in-time" features can mask threats to the validity of score interpretations, including those for aggregate scores and trends over time. We use test score data collected before and during the COVID-19 pandemic to show that longitudinal analyses, not just point-in-time analyses, are necessary to detect threats to desired inferences. We propose that educational agencies require and vendors include longitudinal data features, including "match rates" and correlations, as standard exhibits in technical documentation.

Impact of the covid-19 pandemic on the epidemiology of out-of-hospital cardiac arrest: A systematic review and meta-analysis

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has influenced epidemiology through direct and indirect effects, yet the impact on out-of-hospital cardiac arrest (OHCA) is unclear. We aimed to evaluate the impact of the pandemic on the incidence, characteristics, and clinical outcomes of OHCA. Hypothesis: We hypothesized that compared to the pre-pandemic period, the COVID-19 pandemic period was associated with increased incidence and case fatality rate (CFR) of OHCA, as well as decreased rates of intermediate clinical outcomes (termination of resuscitation [TOR], return of spontaneous circulation [ROSC], survival to hospital admission, and survival to hospital discharge). We further postulated that there was a change in the etiologies of OHCA during the pandemic as well as a decline in the rate of shockable rhythm as the initial presenting rhythm. Methods: In this systematic review and meta-analysis, five scientific databases were searched from inception to May 3, 2021. Meta-analyses were performed for the primary outcomes, secondary outcomes, and clinical characteristics. This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42021253879). Results: The search yielded 966 articles. 20 articles were included for analysis. The COVID-19 pandemic was associated with a 39.5% increase in pooled annual OHCA incidence (p<0.001). Pooled CFR was increased by 2.65% (p<0.001), with an odds ratio (OR) of 1.95 for mortality (95% confidence interval [95%CI] 1.51-2.51). There was increased field TOR (OR=2.46, 95%CI 1.62- 3.74). There were decreased ROSC (OR=0.65, 95%CI 0.55-0.77), survival to hospital admission (OR=0.65, 95%CI 0.48-0.89), and survival to discharge (OR=0.52, 95%CI 0.40-0.69). There was decreased shockable rhythm (OR=0.73, 95%CI 0.60-0.88) and increased asphyxial etiology of OHCA (OR=1.17, 95%CI 1.02-1.33). There was moderate-to-high statistical heterogeneity. Findings were robust to sensitivity analyses, with no publication bias detected. Conclusions: The COVID-19 pandemic was associated with significant changes in OHCA epidemiology. Compared to the pre-pandemic period, the pandemic period was associated with increased OHCA incidence and worse outcomes.

COVID-19-related motivation to lose weight on a digital weight loss program

Background: Obesity is considered a risk factor for severe COVID-19 illness. Thus, individuals with obesity may be especially motivated to lose weight because of COVID-19. To our knowledge, this is the first study to assess COVID-related motivators to lose weight and whether they predict weight loss. Methods: In this prospective study, 530 new users of a digital commercial weight loss program completed a baseline survey in January 2021 assessing overall motivation to lose weight due to COVID (one item: 'how much of your interest in losing weight is because of COVID-19 or its impact, however minor, on your life?'), and three specific COVID motivators. These specific motivators were measured by the validated Fear of COVID-19 scale (F-C), one item assessing motivation to improve eating habits which got worse during COVID-19 (EH-C), and one item assessing motivation to prevent diseases that could increase COVID-19 risk (D-C). The main outcome was weight loss at 2 months, extracted from self-reported weight on the program. Results: Participants were 84% female, had a median age of 46, mean baseline BMI of 32.12 (SD = 6.96), and lost 3.13kg (3.49%) at 2 months (SD = 2.72kg). Overall COVID motivation was high;66% reported that their interest in losing weight was due to COVID. There was high F-C (M = 25.2 out of 35) and EH-C (M = 7.7 out of 10), and moderate D-C (M = 5.4 out of 10). Despite high COVID-related motivation, overall motivation, F-C, and EH-C did not predict weight loss at 2 months. D-C marginally significantly predicted weight loss at 2 months (B = -. 09, p = .06). Conclusions: Results suggest that even though individuals showed initial high motivation due to COVID, it did not manifest in actual weight loss, except in the most at-risk individuals who sought to prevent diseases that put them at greater risk. Individuals may need support to translate initial COVID-related motivation to actual weight loss. Next, we will examine relationships between COVID motivators, vaccination status, and weight loss at 4 months.

Elevated Central Carbon Metabolism - a Hallmark for Senescent Cells in Aging Human Hematopoietic Stem Cell Compartment

Comprehensive proteomic studies of HSC derived from bone marrow of healthy human subjects (n = 59) in different age groups (range: 20 - 72 years) showed that aging HSCs are characterized not only by myeloid lineage skewing, senescence associated secretory phenotype (SASP), accumulation of reactive oxygen species (ROS), anti-apoptosis, but prominently by elevated glycolysis, glucose uptake, and accumulation of glycogen. This is caused by a subset of HSC that has become more glycolytic than others and not on a per cell basis. Subsequent comparative transcriptome studies of HSCs from human subjects >60 years versus those from <30 years have confirmed this association of elevated glycolysis with aging transcriptome signature. Provided with this background and based on glucose metabolism levels, we have developed a method to isolate human HSCs (CD34+ cells) from bone marrow into three distinct subsets with high, intermediate, and low glucose uptake (GU) capacity (GU high, GU inter, GU low). For human subjects >60 years old (n=9), the proportions of these subsets are: GU high= 5.4+3.5 %, GU inter= 66.4+22.5 %, GU low= 28.2+21.7 %. For subjects <30 years (n=5), the proportions are GU high= 1.7+1.5 %, GU inter= 66.5+36.9 %, GU low= 31.8+36.7. Single-cell RNA-sequencing (scRNA-seq) studies and gene ontology analysis of biological processes revealed that, compared to the GU inter and GU low subsets, the GU high cells showed a significantly higher expression of genes involved in myeloid development, inflammation response (AIF1, CASP2, ANXA1, ZFP36), anti-apoptosis (GSTP1, NME1, BCL2, DMNT1, BAX), cell cycle checkpoint (MCL1, CDK1, CDK4, EIF5A), histone regulation (BCL6, EGR1, KDM1A, MLLT3), b-galactosidase, and significantly lower expressions of genes involved in lymphoid development, and of MDM4, MDM2, FOXP1, SOX4, RB1. Functional studies indicated that the glycolytic enzymes were elevated in elderly HSCs, and the GU low subset corresponded to primitive and more pluripotent HSCs than the GU interand GU high subsets. Pathway analyses have then demonstrated that the GU high subset is associated with up-regulated p53 as well as JAK/STAT signaling pathways, characteristic of senescent HSCs observed in murine models. Applying Gene Set Enrichment Analysis (GSEA) algorithms, we have compared the scRNA-seq data of CD34+ cells derived from young (<30 years) versus older (>60 years) subjects, as well as the scRNA-seq data from GU high subset versus GU inter and GU lowsubsets from each individual subject (n = 6). The results are shown in Figure 1. In analogy to the comparison between old (>60 years) versus young (<30 years) HSCs (CD34+ cells), GSEA of the GU high versus GU inter and GU low subsets shows the same pattern of changes - significant upregulation of gene-set expressions for (a) inflammatory response (b) G2M checkpoint, (c) MTORC1, (d) ROS, (Fig. 1B), (e) allograft rejection;and down-regulation of gene-set expressions for (f) pluripotency, (g) androgen response, (h) UV response (Fig. 1C) as well as (i) interferon-a induction during SARS-CoV2-infection (data not shown in Fig. 1). Thus, our novel findings of elevated glycolysis coupled with significant activation of MTORC1 in the senescent cells of the HSC compartment have provided evidence for the important role of calorie restriction (CR) for healthy aging of HSCs. In numerous animal models, aging has been shown to be driven by the nutrient-sensing MTORC1 network. In animal models of aging, CR has been reported to deactivate the MTOR pathway, thus slowing aging and delaying diseases of aging. Conclusion: In a series of multi-omics studies, we have demonstrated that the GU high subset is identical to the senescent cells (SCs) in human HSC compartment. Studies in animal models have shown that SCs in murine bone marrow are responsible for driving the aging process, and elimination of this subset by inhibitors of anti-apoptotic factors is able to rejuvenate hematopoiesis in mice. Our present results have provided cellular and molecular evidence that SCs in human HSC compartment re also dependent on anti-apoptotic factors, elevated MTORC1 as well as increased glycolysis for survival. Inhibition of MTORC1 or glycolysis, either by specific inhibitors or by CR, may eliminate senescent HSCs and promote rejuvenation of human hematopoiesis. [Formula presented] Disclosures: No relevant conflicts of interest to declare.

The Impact of the COVID-19 Pandemic on Practice Patterns in Breast Radiation Oncology: A Case-Based Survey Study in the United States

Purpose/Objective(s): The COVID-19 pandemic posed challenges in resource allocation and breast cancer (BC) treatment decisions. Our study aims to understand changes in practice patterns of United States radiation oncologists (RO) treating BC during the COVID-19 pandemic. Materials/Methods: An IRB-approved 58-question survey with 6 clinical scenarios was distributed between July 17 and November 8, 2020 to ASTRO directory members. The cases included 1) Low-grade ductal carcinoma in situ (DCIS), 2) Low-risk BC treated with lumpectomy, 3) Low-risk BC treated with mastectomy with reconstruction 4) BC treated with neoadjuvant chemotherapy and mastectomy with reconstruction 5) BC treated with mastectomy and adjuvant chemotherapy but without reconstruction 6) Metastatic BC with enlarging breast mass. RO were surveyed about treatment recommendations if cases were seen pre-pandemic (PP) and hypothetically during the peak of pandemic (DTPP). Chi-square and McNemar-Bowker tests were used to examine the significance of changes. Results: A total of 285 respondents from 48 states completed the survey and reported treating at least one patient with BC in the past 12 months. 45% primarily practice in university affiliated hospitals and 43% in private practice. 22% reported treating ≥ 1 COVID-positive BC patients. Moderate hypofractionation (2.31 - 3 Gy per fraction) in the PMRT and immediate reconstruction setting was recommended by 0.7% PP compared to 10.5% DTPP. In the low-risk PMRT setting, recommendation of no further treatment increased from 13% PP to 20% DTPP. Further, 56% changed their DCIS recommendations if the patient was seen DTPP. For low-risk BC, whole breast RT was preferred by 83.5% PP compared to 46.7% DTPP, and 35.1% recommended delay of RT DTPP compared to 0.4% PP (P < 0.05). Increase in ultra-hypofractionation (> 5 Gy per fraction) was significant for low-risk BC after lumpectomy as 0.4% reported its use PP compared to 3.8% DTPP. In addition, utilization of brachytherapy as PBI modality decreased from 23.9% to 17% among respondents PP and DTPP respectively. The Florence fractionation schedule for PBI was recommended by 46.2% for early-stage BC and by 51.7% for DCIS DTPP compared to 20% and 34.4% PP. Finally, 68.1% reported the use of 10-25 fractions PP for the palliative scenario. However, of those who would change their recommendation (48.8%), 62.8% reported recommendation of ≤ 5 fractions DTPP. Additional subset analysis by geographic region and practice type were notable for variable changes in treatment recommendations, and will be presented. Conclusion: This large survey of Breast RO clinical decision making demonstrates significant differences in recommendations and rapid adoption of unique fractionation. While likely reflective of intent to optimize resource allocations during the pandemic, maintenance of new practice patterns remains subject to future investigation.

Encrypted network traffic analysis of secure instant messaging application: A case study of signal messenger app

Instant messaging applications (apps) have played a vital role in online interaction, es-pecially under COVID-19 lockdown protocols. Apps with security provisions are able to provide confidentiality through end-to-end encryption. Ill-intentioned individuals and groups use these security services to their advantage by using the apps for criminal, illicit, or fraudulent activities. During an investigation, the provision of end-to-end encryption in apps increases the complexity for digital forensics investigators. This study aims to provide a network forensic strategy to identify the potential artifacts from the encrypted network traffic of the prominent social messenger app Signal (on Android version 9). The analysis of the installed app was conducted over fully encrypted network traffic. By adopting the proposed strategy, the forensic investigator can easily detect encrypted traffic activities such as chatting, media messages, audio, and video calls by looking at the payload patterns. Furthermore, a detailed analysis of the trace files can help to create a list of chat servers and IP addresses of involved parties in the events. As a result, the proposed strategy significantly facilitates extraction of the app’s behavior from encrypted network traffic which can then be used as supportive evidence for forensic investigation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Supporting and coping with bereavement during and post-pandemic

The following sections are included: Introduction The Pain of Disenfranchised Grief and Social Distancing during COVID-19 The Taxonomic Perils of “Social” Distancing Evolving Funerary and Bereavement Customs Amidst a Pandemic Technology as a Recreative Medium Meaning Reconstruction for Supporting Bereavement in a Post-Pandemic World The Caveat of Collective Grieving Conclusion References. © 2021 by Editors.

An automated approach to determine antibody endpoint titers for COVID-19 by an enzyme-linked immunosorbent assay.

While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33-43.While a variety of therapeutic options continue to emerge for COVID-19 treatment, convalescent plasma (CP) has been used as a possible treatment option early in the pandemic. One of the most significant challenges with CP therapy, however, both when defining its efficacy and implementing its approach clinically, is accurately and efficiently characterizing an otherwise heterogenous therapeutic treatment. Given current limitations, our goal is to leverage a SARS antibody testing platform with a newly developed automated endpoint titer analysis program to rapidly define SARS-CoV-2 antibody levels in CP donors and hospitalized patients. A newly developed antibody detection platform was used to perform a serial dilution enzyme-linked immunosorbent assay (ELISA) for immunoglobulin (Ig)G, IgM, and IgA SARS-CoV-2 antibodies. Data were then analyzed using commercially available software, GraphPad Prism, or a newly developed program developed in Python called TiterScape, to analyze endpoint titers. Endpoint titer calculations and analysis times were then compared between the two analysis approaches. Serial dilution analysis of SARS-CoV-2 antibody levels revealed a high level of heterogeneity between individuals. Commercial platform analysis required significant time for manual data input and extrapolated endpoint titer values when the last serial dilution was above the endpoint cutoff, occasionally producing erroneously high results. By contrast, TiterScape processed 1008 samples for endpoint titer results in roughly 14 minutes compared with the 8 hours required for the commercial software program analysis. Equally important, results generated by TiterScape and Prism were highly similar, with differences averaging 1.26 ± 0.2 percent (mean ± SD). The pandemic has created unprecedented challenges when seeking to accurately test large numbers of individuals for SARS-CoV-2 antibody levels with a rapid turnaround time. ELISA platforms capable of serial dilution analysis coupled with a highly flexible software interface may provide a useful tool when seeking to define endpoint titers in a high-throughput manner. Immunohematology 2021;37:33­43.

Familial cluster of COVID-19 cases associated with high prevalence of Anosmia, Ageusia, and gastrointestinal symptoms

Background: Patients with COVID-19 most commonly report respiratory symptoms, with a minority reporting gastrointestinal (GI) symptoms in currently available reports. Additionally, little is known about the symptoms of anosmia/hyposmia, ageusia, and dysgeusia anecdotally seen in COVID-19 patients, which may be considered both GI and sensory/neurological manifestations of infection. Methods: We interviewed 7 patients via oral inquiries and a questionnaire, collecting data on subject symptoms and their durations. Reverse transcriptase-polymerase chain reaction (RT-PCR) was used to confirm 2 of these cases. Results: We report a familial cluster of 7 COVID-19 cases, 5 of whom reported sensory symptoms of anosmia/hyposmia (5/7), ageusia/hypogeusia (5/7), and/or dysgeusia (3/7). All 7 cases reported GI involvement with one or more symptom of: nausea (5/7), diarrhea (4/7), abdominal pain (3/7), anorexia (3/7), and emesis (2/7). Conclusion: This frequency of GI symptoms is high relative to currently available epidemiological reports, which also infrequently report on sensory symptoms. The mechanistic underpinnings of GI and sensory symptoms in COVID-19 warrant close consideration and analysis, especially as it relates to reducing disease transmission. COVID-19 exhibits wide variation in duration, severity, and progression of symptoms, even within a familial cluster.

Data-Forensic Determination of the Accuracy of International COVID-19 Reporting: Using Zipf's Law for Pandemic Investigation

Severe outbreaks of infectious disease occur throughout the world with some reaching the level of international pandemic: Coronavirus (COVID-19) is the most recent to do so. In this paper, a mechanism is set out using Zipf's law to establish the accuracy of international reporting of COVID-19 cases via a determination of whether an individual country's COVID-19 reporting follows a power-law for confirmed, recovered, and death cases of COVID-19. The probability of Zipf's law (P-values) for COVID-19 confirmed cases show that Uzbekistan has the highest P-value of 0.940, followed by Belize (0.929), and Qatar (0.897). For COVID-19 recovered cases, Iraq had the highest P-value of 0.901, followed by New Zealand (0.888), and Austria (0.884). Furthermore, for COVID-19 death cases, Bosnia and Herzegovina had the highest P-value of 0.874, followed by Lithuania (0.843), and Morocco (0.825). China, where the COVID-19 pandemic began, is a significant outlier in recording P-values lower than 0.1 for the confirmed, recovered, and death cases. This raises important questions, not only for China, but also any country whose data exhibits P-values below this threshold. The main application of this work is to serve as an early warning for World Health Organization (WHO) and other health regulatory bodies to perform more investigations in countries where COVID-19 datasets deviate significantly from Zipf's law. To this end, this paper provide a tool for illustrating Zipf's law P-values on a global map in order to convey the geographic distribution of reporting anomalies.

Estimating the Risk of Death from COVID-19 in Adult Cancer Patients.

AIMS: During the coronavirus disease 2019 (COVID-19) pandemic, organisations have produced management guidance for cancer patients and the delivery of cytotoxic chemotherapy, but none has offered estimates of risk or the potential impact across populations. MATERIALS AND METHODS: We combined data from four countries to produce pooled age-banded case fatality rates, calculated the sex difference in survival and used data from four recent studies to convert case fatality rates into age/sex-stratified infection fatality rates (IFRs). We estimated the additional risk of death in cancer patients and in those receiving chemotherapy. We illustrate the impact of these by considering the impact on a national incident cancer cohort and analyse the risk-benefit in some clinical scenarios. RESULTS: We obtained data based on 412 985 cases and 41 854 deaths. The pooled estimate for IFR was 0.92%. IFRs for patients with cancer ranged from 0 to 29% and were higher in patients receiving chemotherapy (0.01-46%). The risk was significantly higher with age and in men compared with women. 37.5% of patients with a new diagnosis of cancer in 2018 had an IFR ≥5%. Survival benefits from adjuvant chemotherapy ranged from 5 to 10% in some common cancers, compared with the increased risk of death from COVID-19 of 0-3%. CONCLUSIONS: Older male patients are at a higher risk of death with COVID-19. Patients with cancer are also at a higher risk, as are those who have recently received chemotherapy. We provide well-founded estimates to allow patients and clinicians to better balance these risks and illustrate the wider impact in a national incident cohort.