COVID-19 unemployment and access to statin medications in the United States.

Objective: To quantify the effect of the unemployment created by COVID-19 on access to (sales of) statin drugs in the United States population. Methods: Approximately half a billion transactions for statin drugs in the United States between January 2018 and September 2020 are analyzed. We studied the potential causal relation between abnormal levels of unemployment during the first wave of COVID-19 in the U.S. and abnormal levels of sales of statin products (both variables defined at the state/week level). Variables are analyzed using the Two-Stage Least Squares (2SLS) method, which exploits comparisons of statin sales between states where, given the occupational distribution of their workforce, unemployment was more structurally vulnerable to mobility restrictions derived from COVID-19 against states where it was less structurally vulnerable. Results: While we do not find unemployment effects on statin sales on most of the population, our estimates link COVID-fueled unemployment with a sharp sales reduction among Medicaid-insured populations, particularly those in working age. For the period between March and August of 2020, these estimates imply a 31% drop of statin sales among this population. Discussion: COVID-fueled unemployment may have had a negative and significant effect on access to statin populations among Medicaid-insured populations.

Parent Acceptance toward Inactivated COVID-19 Vaccination in Children with Acute Lymphoblastic Leukemia: The Power of Oncologist and Alliance.

Objectives: The current study aims to survey the willingness of parents to vaccinate their children, who are childhood acute lymphoblastic leukemia survivors (CALLS), and identify factors associated with vaccine acceptance. Methods: Parents of CALLS on/off treatment, with the general condition of being amendable to vaccination, were recruited for interviews with attending oncologists about COVID-19 vaccination acceptance from July to November 2021 in China. After controlling for socioeconomic factors, the Association of Oncologists' recommendations and parent−oncologist alliance with acceptance status were investigated. For validation, propensity score-matched (PSM) analysis was used. Results: A total of 424 families were included in the study, with CALLS mean remission age of 5.99 ± 3.40 years. Among them, 91 (21.4%) agreed, 168 (39.6%) hesitated, and 165 (38.9%) parents disagreed with the vaccination. The most common reason that kept parents from vaccinating their children was lack of recommendations from professional personnel (84/165, 50.9%), and massive amounts of internet information (78/175, 44.6%) was the main nonhealthcare resource against vaccination. Logistic regression analysis showed that only the recommendation from the oncologist was associated with parents' vaccine acceptance (OR = 3.17, 95% CI = 1.93−5.20), as demonstrated by PSM comparison (42 in recommendation group vs. 18 in nonrecommendation group among 114 pairs, p < 0.001). An exploratory analysis revealed that parents with a better patient−oncologist alliance had a significantly higher level of acceptance (65.6% in alliance group vs. 15.6% in nonalliance group among 32 pairs, p < 0.001). Conclusions: Due to a lack of professional recommendation resources and the potential for serious consequences, parents were generally reluctant to vaccinate their CALLS. The recommendation of oncologists, which was influenced by the parent−oncologist alliance, significantly increased acceptance. This study emphasizes the critical role of oncologists in vaccinating cancer survivors and can be used to promote COVID-19 vaccines among vulnerable populations.

Investigation on the effectiveness of ventilation dilution on mitigating COVID-19 patients' secondary airway damage due to exposure to disinfectants.

Chlorine-containing disinfectants are widely used in hospitals to prevent hospital-acquired severe acute respiratory syndrome coronavirus 2 infection. Meanwhile, ventilation is a simple but effective means to maintain clean air. It is essential to explore the exposure level and health effects of coronavirus disease 2019 patients' inhalation exposure to by-products of chloride-containing disinfectants under frequent surface disinfection and understand the role of ventilation in mitigating subsequent airway damage. We determined ventilation dilution performance and indoor air quality of two intensive care unit wards of the largest temporary hospital constructed in China, Leishenshan Hospital. The chloride inhalation exposure levels, and health risks indicated by interleukin-6 and D-dimer test results of 32 patients were analysed. The mean ± standard deviation values of the outdoor air change rate in the two intensive care unit wards were 8.8 ± 1.5 h-1 (Intensive care unit 1) and 4.1 ± 1.4 h-1 (Intensive care unit 2). The median carbon dioxide and fine particulate matter concentrations were 480 ppm and 19 µg/m3 for intensive care unit 1, and 567 ppm and 21 µg/m3 for intensive care unit 2, all of which were around the average levels of those in permanent hospitals (579 ppm and 21 µg/m3). Of these patients, the median (lower quartile, upper quartile) chloride exposure time and calculated dose were 26.66 (2.89, 57.21) h and 0.357 (0.008, 1.317) mg, respectively. A statistically significant positive correlation was observed between interleukin-6 and D-dimer concentrations. To conclude, ventilation helped maintain ward air cleanliness and health risks were not observed.

INVESTIGATING THE INFLUENCE OF FINANCIAL INDICATORS ON STOCK RETURNS IN THE PRESENCE OF THE COVID-19 PANDEMIC

In this paper, we investigate the influence of financial proxies on companies in the real estate sector listed on the Amman stock exchange during the Covid-19 pandemic. A panel data method is employed for the sample, which includes 29 listed real estate companies, for the period from 2010 to 2020. The financial proxies are considered as independent variables, which consist of earnings per share, book value per share, price-to-earnings (P/E) ratio, price-to-book value, debt ratio, and current ratio, while the market return is the dependent variable. The results revealed that all financial proxies have a significant impact on market returns. Furthermore, the financial proxies are positively and significantly correlated with market returns. The results also showed that the Covid-19 pandemic negatively affected the real estate sector returns. Decision makers in real estate companies are required to manage their working capital in an effective and efficient manner in order to deal with unforeseen short-term events as investors might use historical financial data to estimate companies’ returns. © 2022 AESS Publications. All Rights Reserved.

A Comprehensive Review of Deep Learning-Based Methods for COVID-19 Detection Using Chest X-Ray Images

The novel coronavirus disease 2019 (COVID-19) added tremendous pressure on healthcare services worldwide. COVID-19 early detection is of the utmost importance to control the spread of the coronavirus pandemic and to reduce pressure on health services. There have been many approaches to detect COVID-19;the most commonly used one is the nasal swab technique. Before that was available chest X-ray radiographs were used. X-ray radiographs are a primary care method to reveal lung infections, which allows physicians to assess and plan a course of treatment. X-ray machines are prevalent, which makes this method a preferable first approach for the detection of new diseases. However, this method requires a radiologist to assess each chest X-ray image. Therefore, different automated methods using machine learning techniques have been proposed to assist in speeding up diagnoses and improving the decision-making process. In this paper, we review deep learning approaches for COVID-19 detection using chest X-ray images. We found that the majority of deep learning approaches for COVID-19 detection use transfer learning. A discussion of the limitations and challenges of deep learning in radiography images is presented. Finally, we provide potential improvements for higher accuracy and generalisability when using deep learning models for COVID-19 detection.

Assessing the Spreading Behavior of the Covid-19 Epidemic: A Case Study of Turkey

Coronavirus (Covid-19) disease is a rapidly spreading type of virus that was discovered in Wuhan, China, and emerged towards the end of 2019. During this period, various studies were conducted, and intensive studies are continued in different fields regarding coronavirus, especially in the field of medicine. The virus continues to spread and is yet to be controlled fully. Machine learning is a well-explored field in the domain of computer science that can learn patterns based on existing data and make predictions on new data. This study focused on using various machine learning approaches for predicting the spreading behavior of the COVID-19 virus. The models that were considered include SARIMAX, Extreme Gradient Boosting (XGBoost), Linear Regression (LR), Decision Tree (DT), Gradient Boosting (GB), and Artificial Neural Network (ANN). The models were trained and then predictions were made by applying these models to the daily updated data provided by the Turkish Ministry of Health. Experiments on the test data showed that both XGBoost and Decision Tree models outperformed other models. © 2022 IEEE.

Cervico-Thoracic Air Collections in COVID-19 Pneumonia Patients - Our Experience and Brief Review.

Introduction: Abstract COVID-19 (Coronavirus-19 disease), a new clinical entity caused by SARS-COV-2 infection, could explain the physiopathology of cervicothoracic air collections (pneumothorax, pneumomediastinum, and subcutaneous emphysema). Material and Methods: We conducted an 8-months retrospective analysis of a single-center SARS-CoV-2 cases associating pneumothorax, pneumomediastinum, and subcutaneous emphysema, either alone or combined. Results: All non-intubated patients with the complications cited above had a favorable outcome after pleural drainage, percutaneous drainage, and/or conservative treatment, while the intubated patients, with multiple comorbidities, have had an unfavorable outcome, regardless the chosen treatment. Pleural drainage was used for pneumothorax cases; pneumomediastinum with subcutaneous emphysema required insertion of subcutaneous needles or angio-catheters with manual decompressive massage. Conservative methods of treatment were used for patients with pneumomediastinum and medium or severe respiratory disfunction. Conclusions: Etiopathogenic classification of pneumothorax should include SARS-CoV-2 infection as a possible cause of secondary spontaneous pneumothorax due to COVID-19 pneumonia. Survival rate after the occurrence of these complications was small (18,75%), 4 of the patients were cured, 2 had a favorable outcome and 26 have died. Pleural drainage which is mandatory to do for patients with pneumothorax complication in COVID -19 pneumonia, doesn't change the prognosis for those with severe affecting lungs, because the prolonged ventilation and the other comorbidities have led to death in most of these cases.

COVID-19 and liver diseases, what we know so far.

Coronavirus disease 2019 (COVID-19) pneumonia outbreak started in December 2019. On March 12, 2020, the World Health Organization (WHO) declared that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitutes a pandemic, and as of May 2021, SARS-CoV-2 has infected over 167.3 million patients, including 3.4 million deaths, reported to WHO. In this review, we will focus on the relationship between SARS-CoV-2 infection and the liver. We will discuss how chronic liver diseases affect the COVID-19 disease course and outcomes. We will also discuss the SARS-CoV-2 effects on the liver, mechanisms of acute liver injury, and potential management plans.

An automated real-time face mask detection system using transfer learning with faster-rcnn in the era of the covid-19 pandemic

Today, due to the pandemic of COVID-19 the entire world is facing a serious health crisis. According to the World Health Organization (WHO), people in public places should wear a face mask to control the rapid transmission of COVID-19. The governmental bodies of different countries imposed that wearing a face mask is compulsory in public places. Therefore, it is very difficult to manually monitor people in overcrowded areas. This research focuses on providing a solution to enforce one of the important preventativemeasures of COVID-19 in public places, by presenting an automated system that automatically localizes masked and unmasked human faces within an image or video of an area which assist in this outbreak of COVID-19. This paper demonstrates a transfer learning approach with the Faster-RCNN model to detect faces that are masked or unmasked. The proposed framework is built by fine-tuning the state-of-the-art deep learning model, Faster-RCNN, and has been validated on a publicly available dataset named Face Mask Dataset (FMD) and achieving the highest average precision (AP) of 81% and highest average Recall (AR) of 84%. This shows the strong robustness and capabilities of the Faster-RCNN model to detect individuals with masked and un-masked faces. Moreover, this work applies to real-time and can be implemented in any public service area. © 2022 Tech Science Press. All rights reserved.

The journey of antimalarial drugs against SARS-CoV-2: Review article.

The recent outbreak of coronavirus pandemic (COVID-19) introduced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has greatly affected the global public health. This pandemic disease became particularly threatening after the start of a new wave. Vaccines of tested efficacy to stop COVID-19 infection are being investigated vigorously worldwide. Currently, some specific drugs have been authorized for COVID-19, but the improvement of antivirals requires time. Hence, a faster way of treatment is done by drug repurposing. Repurposing of drugs is promising for treating and reducing the symptoms of the disease, and it a fast, easy, and safe method to address the crisis, because of their previously known applications. Some antimalarial drugs, especially chloroquine and hydroxychloroquine, have been repurposed, as they exhibited promising results in vitro and in vivo. This article investigates repurposed antimalarial drugs, focusing on their antiviral mechanisms of action, effects in combinations, trial results, and their side effects.

Professional identity of Wuhan and Hong Kong social workers: COVID-19 challenges and implications.

This reflexive essay focus on how COVID-19 has impacted the professional identity of social workers in Wuhan and Hong Kong. Exploratory and reflexive in nature, eight Wuhan social workers who comprised three males and five females, and seven Hong Kong social workers who comprised one male and six females were recruited for semi-structured interviews. Their experience in Wuhan and Hong Kong during COVID-19 were highlighted. The challenges to professional identity were analyzed and the reflection is categorized into four levels, namely, individual, community, educational and conceptual level. In sum, Wuhan interviewees were more struggled with educating the public on the difference between community work, volunteering and social work, especially at the hospitals, to protect the integrity of the social work profession which shows their commitment to their professional identity. Moreover, they found it difficult to position themselves in proactive online services, where hundreds of workers from different parts of the Mainland China would be involved. On the other hand, Hong Kong interviewees were more inclined to prioritize professional principles at levels that are even higher than those in standardized guidelines. Their goal is to take the best interests of their clients into consideration, and their self-reflections tend to focus more on professional judgement and development of the social work field, to pave the way for future enhancements. Finally yet importantly, the deficiencies of their education as evidenced by the pandemic have been made alarmingly explicit.

What's new in trauma 2020.

Throughout the past 2020, the pandemic COVID-19 has caused a big global shock, meanwhile it brought a great impact on the public health network. Trauma emergency system faced a giant challenge and how to manage trauma under the pandemic of COVID-19 was widely discussed. However, the trauma treatment of special population (geriatric patients and patients taking anticoagulant drugs) has received inadequate attention. Due to the high mortality following severe traumatic hemorrhage, hemostasis and trauma-induced coagulopathy are the important concerns in trauma treatment. Sepsis is another topic should not be ignored when we talking about trauma. COVID-19 itself is a special kind of sepsis, and it may even be called as serious systemic infection syndrome. Sepsis has been become a serious problem waiting to be solved urgently no matter in the fields of trauma, or in intensive care and infection, etc. This article reviewed the research progress in areas including trauma emergency care, trauma bleeding and coagulation, geriatric trauma and basic research of trauma within 2020.