Bill Gates and the 'new normal' COVID-19 conspiracy theories: 'it's a new thing' or nothing new under the sun?

The outbreak of SARS-CoV-2 in late 2019 and the subsequent lockdowns led to widespread conspiracy theories often involving one particular actor: Bill Gates. Adherents of these conspiracy theories believed Gates was behind the pandemic for some nefarious purpose, including chipping and/or eugenics. This was, however, no fringe sentiment: celebrities and other prominent voices articulated some iteration of the Gates-COVID-19 conspiracy theory beginning in 2020. Though the conspiracy theory appears to have come out of nowhere, it does have a (pre-)history. Some have tried to point to a single or recent origin, but it is in fact much older, more complex, and informed by real developments over the previous two decades. This article traces the origins of the conspiracy theory going back to its prehistory in the 1990s, describes the narrative in its various iterations and (per)mutations - along with Gates's shifting role in them - and charts the dissemination of this dynamic conspiracy theory while examining some of its notable tropes.

Immediate and Contributory Causes of Death in Patients Hospitalized with Covid-19

Background: Accurate determination of the immediate and contributory causes of death in patients with COVID-19 is important for optimal care and instituting mitigation strategies. Method(s): All deaths in Qatar between March 1, 2020 and August 31, 2022 flagged for likely relationship to COVID-19 by were evaluated by two independent reviewers trained to determine and assign the most likely immediate underlying cause of death. Each decedent's electronic medical records was comprehensively reviewed, and the cause of death was assigned based on the most plausible underlying event that triggered the event(s) that led to death based on clinical documentation and a review of laboratory, microbiology, pathology, and radiology data. After cause assignment, each case was categorized into major diagnostic groups by organ system, syndrome, or disease classification. Result(s): Among 749 deaths flagged for likely association with COVID-19, the most common admitting diagnoses were respiratory tract infection (91%) and major adverse cardiac event (MACE, 2.3%). The most common immediate cause of death was COVID pneumonia (66.2%), followed by MACE (7.1%), hospital associated pneumonia (HAP, 6.8%), bacteremia (6.3%), disseminated fungal infection (DFI, 5.2%), and thromboembolism (4.5%). The median length of hospital stay was 23 days (IQR 14,38). COVID pneumonia remained the predominant cause irrespective of the time from admission, though the proportion dropped with increasing length of stay in the hospital. Other than COVID pneumonia, MACE was the predominant cause of death in first two weeks but declined thereafter. No death occurred due to bacteremia, HAP, or DFI in the first week after hospitalization, but became increasing common with increased length of stay in the hospital accounting for 9%, 12%, and 10% of all deaths after 4 weeks in the hospital respectively. The majority of deaths (86%) occurred in the intensive care unit setting. COVID pneumonia accounted for approximately two-thirds of deaths in each setting. MACE and HAP were approximately equally represented in both settings while bacteremia and disseminated fungal infection were more common in the intensive care unit setting. Conclusion(s): Nearly one-third of patients with COVID infection die of non- COVID causes, some of which are preventable. Mitigation strategies should be instituted to reduce the risk of such deaths. (Figure Presented).

Endophytes - untapped resources and pharmacological prospects against coronaviruses

Introduction and aim. Viral infections stand to be among the most devastating diseases globally. Though significant efforts have been made in research and drug development against viral infections, the search for safe, affordable and effective vaccines against the current ravaging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still on. This is because already approved vaccines still need improvement. This review draws the attention of researchers on the potentials of bioactive substances from endophytes against the novel coronaviruses. Material and methods. This assessment was made using references of articles published in English peer reviewed journals indexed in PubMed and Google Scholars databases up to June, 2022. The following key words were used;'coronaviruses', 'Endophytes', 'Endophytes and viral infections, 'Endophytes and COVID-19, 'SARS-CoV'. Analysis of the literature. In-silico, in-vitro and in-vivo studies revealed that natural compounds from endophytes showed antiviral activities against various human coronavirus, including HCoV 229E and a norovirus surrogate, the feline coronavirus FCV F9, COVID-19, Coronavirus 2 (SARS-CoV-2), SARSCoV-2 Mpro, among others. Conclusion. This finding calls for researchers to also focus on endophytes, as part of drugs development in the bid to finding possible solution in combating the devastating COVID-19, an emerging situation. © 2023 The Author(s).

A critical appraisal on the treatment of acute appendicitis in pediatric population during the COVID-19 pandemic.

Acute appendicitis is one of the most common causes of abdominal pain in children. During the coronavirus disease 2019 (COVID-19) pandemic, a delay in presentation to the emergency department and a higher rate of complicated appendicitis were observed. Traditionally, operative management (laparoscopic or open appendectomy) was thought to be the best treatment strategy for acute appendicitis. However, nonoperative management with antibiotics has gained popularity in managing pediatric appendicitis during the COVID-19 era. The pandemic has posed significant challenges in the management of acute appendicitis. Cancellation of elective appendectomies, delay in seeking care due to fear of contracting COVID-19 infection, and impact of COVID-19 infection in the pediatric population have resulted in higher rates of complications. Furthermore, multiple studies have reported multisystem inflammatory syndrome in children mimicking acute appendicitis, subjecting patients to unnecessary surgery. Therefore, it is imperative to update the treatment guidelines for the management of acute appendicitis in the pediatric population during and after COVID-19 times.

Cluster analysis of biochemical markers as predictor of COVID-19 severity

Numerous blood biomarkers are altered in COVID-19 patients;however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.

The effect of the COVID-19 pandemic on severe asthma care in Europe - will care change for good?

Background The COVID-19 pandemic has put pressure on health-care services forcing the reorganization of traditional care pathways. Aim To investigate;(1) how physicians taking care of severe asthma patients in Europe reorganized care during the COVID-19 pandemic;(2) patient satisfaction with these changes;and (3) impact on future care. Methods In this European-wide cross-sectional study, patient surveys were sent to patients with a physiciandiagnosis of severe asthma, and physician surveys to severe asthma specialists (November 2020 - May 2021). Results 1101 patients and 268 physicians from 16 European countries contributed to the study. Common physicianreported changes in severe asthma care included use of video/phone consultations (46%) and change to home administered biologics (38%), which resulted in high satisfaction levels in most patients (Figure 1). Many physicians expect continued implementation of video/phone consultations (41%) and home administration of biologics (52%). Conclusions Change to video/phone consultations and home administration of biologics was common in severe asthma care during the COVID-19 pandemic, and was associated with high satisfaction levels in most but not all cases. Many physicians expect these changes to continue in future severe asthma care, though satisfaction levels may change after the pandemic. (Figure Presented).

Effect of Fluvoxamine on Interleukin-6 Levels in COVID-19 Patients Hospitalized in ICU: A Randomized Clinical Trial

Background: Reviewing the laboratory studies, we observe some drugs with other specified applications, which cause serious inhibitory immune responses in the body. Selective Serotonin Reuptake Inhibitors (SSRIs) are among these drugs. Therefore, the current research aimed to evaluate the effectiveness of one of the SSRI drugs called fluvoxamine on the cytokine levels in COVID-19 patients. Material(s) and Method(s): The current research included 80 patients with COVID-19 hospitalized in ICU in Massih Daneshvari Hospital. They were entered into the research by an accessible method of sampling and then divided into two groups randomly. One of the groups underwent the treatment with fluvoxamine as the experimental group and the other group did not receive fluvoxamine as the control group. Interleukin-6 (IL-6) and CRP levels were measured before the onset of fluvoxamine consumption and when discharging from the hospital in all members of the sample group. Result(s): The current study showed that IL-6 levels increased, while CRP levels decreased in the experimental group significantly (P-value<= 0.01). After consuming fluvoxamine, IL-6 and CRP levels were higher and lower in the females compared to the males, respectively. Conclusion(s): Considering the effectiveness of fluvoxamine on IL-6 and CRP in COVID-19 patients, it may ultimately come true to use this drug to improve both psychological and physical conditions simultaneously and leave the COVID-19 pandemic behind with less pathology.Copyright © 2022 NRITLD, National Research Institute of Tuberculosis and Lung Disease, Iran.

COVID-19's Psychological Impact on Chronic Disease Patients Seeking Medical Care.

BACKGROUND: The outbreak has harmed patients with multiple comorbidities and chronic conditions. The pandemic's psychological impact is thought to change their routine of seeking medical care. Research Question or Hypothesis: During COVID-19, patients with chronic conditions may experience anxiety, depression, and stress, and their pattern of seeking medical care may change. MATERIALS AND METHODS: In May 2021, a cross-sectional, web-based study of patients with chronic diseases was conducted. Eligible patients (1036) were assessed for psychological disorders, primarily depression, stress, and anxiety, using the DASS-21 scale, and their pattern of receiving medical care during COVID-19. RESULTS: During the pandemic, 52.5% of the patients with chronic diseases were depressed, 57.9% were anxious, and 35.6% were stressed. Patients with chronic diseases who had moderate to severe depression (34.9% versus 45.1%, p = 0.001), moderate to severe anxiety (43.6% versus 53.8%, p = 0.001), or moderate to severe stress (14.9% versus 34.8%, p = 0.001) were significantly more likely to have no follow-up for their chronic conditions. CONCLUSIONS: Patients with chronic conditions experienced significant anxiety, depression, and stress during COVID-19, which changed their pattern of seeking medical care, and the majority of them did not receive follow-up for their chronic conditions.

Maternal transfer of IgA and IgG SARS-CoV-2 specific antibodies transplacentally and via breast milk feeding.

BACKGROUND: Although there have been many studies on antibody responses to SARS-CoV-2 in breast milk, very few have looked at the fate of these in the infant, and whether they are delivered to immunologically relevant sites in infants. METHODS: Mother/infant pairs (mothers who breast milk fed and who were SARS-CoV-2 vaccinated before or after delivery) were recruited for this cross-sectional study. Mother blood, mother breast milk, infant blood, infant nasal specimen, and infant stool was tested for IgA and IgG antibodies against SARS-CoV-2 spike trimer. RESULTS: Thirty-one mother/infant pairs were recruited. Breast milk fed infants acquired systemic anti-spike IgG antibodies only if their mothers were vaccinated antepartum (100% Antepartum; 0% Postpartum; P<0.0001). Breast milk fed infants acquired mucosal anti-spike IgG antibodies (in the nose) only if their mothers were vaccinated antepartum (89% Antepartum; 0% Postpartum; P<0.0001). None of the infants in either group had anti-spike IgA in the blood. Surprisingly, 33% of the infants whose mothers were vaccinated antepartum had high titer anti-spike IgA in the nose (33% Antepartum; 0% Postpartum; P = 0.03). Half-life of maternally transferred plasma IgG antibodies in the Antepartum infant cohort was ~70 days. CONCLUSION: Vaccination antepartum followed by breast milk feeding appears to be the best way to provide systemic and local anti-SARS-CoV-2 antibodies for infants. The presence of high titer SARS-CoV-2-specific IgA in the nose of infants points to the potential importance of breast milk feeding early in life for maternal transfer of mucosal IgA antibodies. Expectant mothers should consider becoming vaccinated antepartum and consider breast milk feeding for optimal transfer of systemic and mucosal antibodies to their infants.

Designing and developing a sensitive and specific SARS-CoV-2 RBD IgG detection kit for identifying positive human samples.

BACKGROUND: More than 3 y into the coronavirus 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to undergo mutations. In this context, the Receptor Binding Domain (RBD) is the most antigenic region among the SARS-CoV-2 Spike protein and has emerged as a promising candidate for immunological development. We designed an IgG-based indirect enzyme-linked immunoassay (ELISA) kit based on recombinant RBD, which was produced from the laboratory to 10 L industry scales in Pichia pastoris. METHODS: A recombinant-RBD comprising 283 residues (31 kDa) was constructed after epitope analyses. The target gene was initially cloned into an Escherichia coli TOP10 genotype and transformed into Pichia pastoris CBS7435 muts for protein production. Production was scaled up in a 10 L fermenter after a 1 L shake-flask cultivation. The product was ultrafiltered and purified using ion-exchange chromatography. IgG-positive human sera for SARS-CoV-2 were employed by an ELISA test to evaluate the antigenicity and specific binding of the produced protein. RESULTS: Bioreactor cultivation yielded 4 g/l of the target protein after 160 h of fermentation, and ion-exchange chromatography indicated a purity > 95%. A human serum ELISA test was performed in 4 parts, and the ROC area under the curve (AUC) was > 0.96 for each part. The mean specificity and sensitivity of each part was 100% and 91.5%, respectively. CONCLUSION: A highly specific and sensitive IgG-based serologic kit was developed for improved diagnostic purposes in patients with COVID-19 after generating an RBD antigen in Pichia pastoris at laboratory and 10 L fermentation scales.

The effectiveness of COPA-based training program on the infection-control competencies of newly hired healthcare professionals.

Competency-based education that relies on nurses' and healthcare professionals' needs assessment is crucial to tackling healthcare crises such as COVID-19. Strengthening the capacities of human resources by implementing customized infection control training programs is therefore mandatory. This study aims to measure the effectiveness and satisfaction of the Competency Outcomes and Performance Assessment (COPA)-based training program. The study implemented a single group pretest-posttest experimental design. A single-stage cluster sampling technique was used. All field hospitals in Jordan were listed, and one hospital was randomly selected. A total of 87 personnel from different disciplines agreed to participate after reading the letter of information and signing the informed consent. A panel of experts representing different disciplines and hospital units initially met and agreed upon a list of competencies required for the training program, and the program was accordingly developed. The study measured the healthcare professionals' competencies in infection control and prevention before and after the administration of the competency-based training program. The results revealed significant differences between participants' pretest and posttest scores in all infection control domains and the total scores. For example, the increase in participants' total competency scores after the training was statistically significant (P < 0.007). The mean total satisfaction score was 61.18 + 7.00 reflecting that the participants were highly satisfied with the provided training. In conclusion, it is imperative to provide healthcare professionals with adequate clinical training to ensure that healthcare services are going to be delivered in the highest possible quality and minimize the possible adverse events.

The effectiveness of COPA-based training program on the infection-control competencies of newly hired healthcare professionals

Competency-based education that relies on nurses' and healthcare professionals' needs assessment is crucial to tackling healthcare crises such as COVID-19. Strengthening the capacities of human resources by implementing customized infection control training programs is therefore mandatory. This study aims to measure the effectiveness and satisfaction of the Competency Outcomes and Performance Assessment (COPA)-based training program. The study implemented a single group pretest-posttest experimental design. A single-stage cluster sampling technique was used. All field hospitals in Jordan were listed, and one hospital was randomly selected. A total of 87 personnel from different disciplines agreed to participate after reading the letter of information and signing the informed consent. A panel of experts representing different disciplines and hospital units initially met and agreed upon a list of competencies required for the training program, and the program was accordingly developed. The study measured the healthcare professionals' competencies in infection control and prevention before and after the administration of the competency-based training program. The results revealed significant differences between participants' pretest and posttest scores in all infection control domains and the total scores. For example, the increase in participants' total competency scores after the training was statistically significant (P < 0.007). The mean total satisfaction score was 61.18 + 7.00 reflecting that the participants were highly satisfied with the provided training. In conclusion, it is imperative to provide healthcare professionals with adequate clinical training to ensure that healthcare services are going to be delivered in the highest possible quality and minimize the possible adverse events.

Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity

Numerous blood biomarkers are altered in COVID-19 patients;however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development. © 2022 University of Baghdad. All rights reserved.

Viral dynamics of Omicron and Delta SARS-CoV-2 variants with implications for timing of release from isolation: a longitudinal cohort study.

BACKGROUND: In January 2022, United States guidelines shifted to recommend isolation for 5 days from symptom onset, followed by 5 days of mask wearing. However, viral dynamics and variant and vaccination impact on culture conversion are largely unknown. METHODS: We conducted a longitudinal study on a university campus, collecting daily anterior nasal swabs for at least 10 days for RT-PCR and culture, with antigen rapid diagnostic testing (RDT) on a subset. We compared culture positivity beyond day 5, time to culture conversion, and cycle threshold trend when calculated from diagnostic test, from symptom onset, by SARS-CoV-2 variant, and by vaccination status. We evaluated sensitivity and specificity of RDT on days 4-6 compared to culture. RESULTS: Among 92 SARS-CoV-2 RT-PCR positive participants, all completed the initial vaccine series, 17 (18.5%) were infected with Delta and 75 (81.5%) with Omicron. Seventeen percent of participants had positive cultures beyond day 5 from symptom onset with the latest on day 12. There was no difference in time to culture conversion by variant or vaccination status. For 14 sub-study participants, sensitivity and specificity of day 4-6 RDT were 100% and 86% respectively. CONCLUSIONS: The majority of our Delta- and Omicron-infected cohort culture-converted by day 6, with no further impact of booster vaccination on sterilization or cycle threshold decay. We found that rapid antigen testing may provide reassurance of lack of infectiousness, though guidance to mask for days 6-10 is supported by our finding that 17% of participants remained culture positive after isolation.

Menstrual symptoms variation among Lebanese women before and after the COVID-19 pandemic.

Objectives: Pandemic diseases and the confinement measures due to COVID-19 infection have introduced acute and persistent psychosocial stressors for different individuals with a greater influence on females manifested through changes in the menstrual cycle. The objective of this study was to assess Lebanese female of reproductive age about their menstrual cycle, their mental health, and their lifestyle, throughout the COVID-19 pandemic, Beirut blast, and the economic crises. Methods: A cross-sectional online study conducted between October and December 2021, enrolled 398 Lebanese women using the snowball technique. The Menstrual Symptom Questionnaire (MSQ) was used to assess menstrual symptoms. A repeated measures ANOVA was used to assess factors associated with the variation in MSQ scores after vs before the pandemic. Results: Our results showed that a significantly higher number of days of menses, number of pads per day and total MSQ score were significantly found after the pandemic compared to before it. More distress (Beta=0.68), more post-traumatic stress disorder due to COVID-19 (Beta=0.19), a higher number of waterpipes smoked per week (Beta=1.20) and being infected by COVID-19 compared to not (Beta=3.98) were significantly associated with an increase in the MSQ score after the pandemic compared to before it. Conclusion: Our main findings indicate that females had irregular menstrual cycles, unpredictable bleeding pattern, and intense symptoms severity post COVID-19 pandemic. Furthermore, stress post COVID-19 and Beirut blast tended to be associated with increased menstrual symptoms. Thus, vulnerable women should be identified and offered appropriate care, information, and awareness regarding their menstrual period during a pandemic.

Are we ready yet for digital transformation? Virtual versus on-campus OSCE as assessment tools in pharmacy education. A randomized controlled head-to-head comparative assessment.

Background: The global COVID-19 pandemic has influenced pharmacy education including learning, assessment, and exams. In the UAE, pharmacy instructors have adapted several innovative teaching methods to strive for quality learning outcomes. The current trial presented a head-to-head comparative assessment between on-campus versus virtual Objective Structured Clinical Examination (OSCE) with examiners' and students' perspectives. Aim: The main aim was to compare fourth-year students' and examiners' perceptions of the feasibility (time and logistics), stress, performance, and satisfaction between on-campus versus virtual OSCE. Method: A randomized controlled head-to-head comparative assessment between the On-campus and virtual OSCE was conducted to explore performance and satisfaction of pharmacy students and examiners towards the two OSCE settings. The virtual OSCE was carried out directly after the on-campus -OSCE and the setting was designed in a way that aligned with the on-campus OSCE but in a virtual way. Microsoft Teams® breakout room was used as a virtual stations. Respondus-lockdown-browse and Google Meet® were used for proctoring purposes. Results: Students who sat for the on-campus assessment were more satisfied with the instructions, the orientation session, the time management, and the overall exam setting, the ability of the exam to assess their communication and clinical skills, professionalism and attitude, and the interactivity of the exam compared to the students who sat for the virtual assessment. Examiners' perceptions for both settings were the same with the exception of interaction with students (p less than 0.05) as the on-campus OSCE was more interactive. Conclusion: Students still prefer the on-campus OSCE to the virtual OSCE format in many aspects. Nevertheless, virtual OSCE is still a feasible and satisfactory method of assessment when on-campus OSCE is not possible. There is a need of a specialized platform to conduct the virtual OSCE from A to Z rather than maximizing the use of options in the current digital platforms.

Deep learning approach to security enforcement in cloud workflow orchestration.

Supporting security and data privacy in cloud workflows has attracted significant research attention. For example, private patients' data managed by a workflow deployed on the cloud need to be protected, and communication of such data across multiple stakeholders should also be secured. In general, security threats in cloud environments have been studied extensively. Such threats include data breaches, data loss, denial of service, service rejection, and malicious insiders generated from issues such as multi-tenancy, loss of control over data and trust. Supporting the security of a cloud workflow deployed and executed over a dynamic environment, across different platforms, involving different stakeholders, and dynamic data is a difficult task and is the sole responsibility of cloud providers. Therefore, in this paper, we propose an architecture and a formal model for security enforcement in cloud workflow orchestration. The proposed architecture emphasizes monitoring cloud resources, workflow tasks, and the data to detect and predict anomalies in cloud workflow orchestration using a multi-modal approach that combines deep learning, one class classification, and clustering. It also features an adaptation scheme to cope with anomalies and mitigate their effect on the workflow cloud performance. Our prediction model captures unsupervised static and dynamic features as well as reduces the data dimensionality, which leads to better characterization of various cloud workflow tasks, and thus provides better prediction of potential attacks. We conduct a set of experiments to evaluate the proposed anomaly detection, prediction, and adaptation schemes using a real COVID-19 dataset of patient health records. The results of the training and prediction experiments show high anomaly prediction accuracy in terms of precision, recall, and F1 scores. Other experimental results maintained a high execution performance of the cloud workflow after applying adaptation strategy to respond to some detected anomalies. The experiments demonstrate how the proposed architecture prevents unnecessary wastage of resources due to anomaly detection and prediction.

Identifying Challenges, Enabling Practices, and Reviewing Existing Policies Regarding Digital Equity and Digital Divide Toward Smart and Healthy Cities: Protocol for an Integrative Review.

BACKGROUND: Digital equity denotes that all individuals and communities have equitable access to the information technology required to participate in digital life and can fully capitalize on this technology for their individual and community gain and benefits. Recent research highlighted that COVID-19 heightened the existing structural inequities and further exacerbated the technology-related social divide, especially for racialized communities, including new immigrants, refugees, and ethnic minorities. The intersection of challenges associated with racial identity (eg, racial discrimination and cultural differences), socioeconomic marginalization, and age- and gender-related barriers affects their access to health and social services, education, economic activity, and social life owing to digital inequity. OBJECTIVE: Our aim is to understand the current state of knowledge on digital equity and the digital divide (which is often considered a complex social-political challenge) among racialized communities in urban cities of high-income countries and how they impact the social interactions, economic activities, and mental well-being of racialized city dwellers. METHODS: We will conduct an integrative review adapting the Whittemore and Knafl methodology to summarize past empirical or theoretical literature describing digital equity issues pertaining to urban racialized communities. The context will be limited to studies on multicultural cities in high-income countries (eg, Calgary, Alberta) in the last 10 years. We will use a comprehensive search of 8 major databases across multiple disciplines and gray literature (eg, Google Scholar), using appropriate search terms related to digital "in/equity" and "divide." A 2-stage screening will be conducted, including single citation tracking and a hand search of reference lists. Results will be synthesized using thematic analysis guidelines. RESULTS: As of August 25, 2022, we have completed a systematic search of 8 major academic databases from multiple disciplines, gray literature, and citation or hand searching. After duplicate removal, we identified 8647 articles from all sources. Two independent reviewers are expected to complete the 2-step screening (title, abstract, and full-text screening) using Covidence followed by data extraction and analysis in 4 months (by December 2022). Data will be extracted regarding digital equity-related initiatives, programs, activities, research findings, issues, barriers, policies, recommendations, etc. Thematic analysis will reveal how barriers and facilitators of digital equity affect or benefit racialized population groups and what social, material, and systemic issues need to be addressed to establish digital equity for racialized communities in the context of a multicultural city. CONCLUSIONS: This project will inform public policy about digital inequity alongside conventional systemic inequities (eg, education and income levels); promote digital equity by exploring and examining the pattern, extent, and determinants and barriers of digital inequity across sociodemographic variables and groups; and analyze its interconnectedness with spatial dimensions and variations of the urban sphere (geographic differences). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/40068.

Deep Transfer Learning approach for Classification of Chest Infections in Radiographic X-Ray Images

From past two years world is suffering with the COVID-19 pandemic which mainly infecting human lungs. Lung infection can be caused by different viruses and bacteria, diagnosis of Lung infections can be done using Radiography X-ray images. Due to similarity in infections there are high chances that other infections can be falsely considered as COVID-19. Manual chest X-ray diagnosis for COVID-19 requires a radiologist and a time taking process, hence it is not a good choice as the covid-19 can spread in no time from person to person.Hence there is need for automatic process of Covid-19 detection and classification of different chest disease. We worked on developing a deep transfer learning model which will accurately classify various chest infections such as COVID-19, Lung-Opacity, Tuberculosis, Viral Pneumonia, We used transfer learning approach which uses existing deep learning models and adding our layers for classification. This work compares various pre-trained models and also convolutional neural network by considering data set of different infections with total 4526 images belonging to 5 classes for training, 647 images belonging to 5 classes for validation, 746 images for testing. © 2022 IEEE.

Healthcare providers' intention to leave their jobs during COVID-19 pandemic: A cross-sectional study.

Background and Aims: During the coronavirus pandemic (COVID-19), healthcare providers confronted risks of disease transmission to themselves and their family members, resulting in physical and psychological burdens. This might affect their decisions to leave their jobs temporarily or permanently, fearing infection and protecting their families. This study examined the factors related to the intention to leave a job among healthcare providers during the COVID-19 pandemic in Jordan. Methods: A cross-sectional correlational design was used to collect data using a convenience sample of 557 healthcare providers working in different sectors across Jordan. Data were collected using a self-administered questionnaire about the intention to leave jobs during the pandemic. Results: The sample included 368 females (63.8%) and 209 males (36.6%) participants. The mean age of participants was 30.8 years (SD = 6.65). Differences found in intention to leave job during COVID-19 in relation to age (t = 2.60, p < 0.05), gender (X 2 = 4.25, p < 0.001), and marital status (X 2 = 18.2, p < 0.001). Participants with a high risk of exposure to COVID-19 and who experienced higher workloads had higher scores of intention to leave their job during COVID-19, while being married had lower scores. Conclusions: Policy-makers need to pay attention to young and single healthcare providers during the COVID-19 pandemic to prevent them leave their job. Crucial guidelines for managing workload during the COVID-19 pandemic are needed. Policy-makers during pandemics have to protect healthcare providers who feel they are at high risk of infection.