Search results for: covid posters

Authors: Elisavet Arsenaki

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Paracetamol overdose is associated with significant and possibly permanent consequences including hepatotoxicity, acute and chronic liver failure, and death. This quality improvement project explores the prevalence of accidental iatrogenic paracetamol overdose in hospital patients with a low body weight, defined as <50kg and assesses the impact of educational posters in trying to reduce it. The study included all adult inpatients on the admissions ward, a short stay ward for patients requiring 12-72 hour treatment, and consisted of three cycles. Each cycle consisted of 3 days of data collection in a given month (data collection for cycle 1 occurred in January 2022, February 2022 for cycle 2 and March 2022 for cycle 3). All patients given paracetamol had their prescribed dose checked against their charted weight to identify the percentage of adult inpatients <50kg who were prescribed 1g of paracetamol instead of 500mg. In the first cycle of the audit, data were collected from 83 patients who were prescribed paracetamol on the admissions ward. Subsequently, four A4 educational posters were displayed across the ward, on two separate occasions and with a one-month interval in between each poster display. The aim of this was to remind prescribing doctors of their responsibility to check patient body weight prior to prescribing paracetamol. Data were collected again one week after each round of poster display, from 72 and 70 patients respectively. Over the 3 cycles with a cumulative 225 patients, 15 weighed <50kg (6.67%) and of those, 5 were incorrectly prescribed 1g of paracetamol, yielding a 33.3% prevalence of accidental iatrogenic paracetamol overdose in adult inpatients. In cycle 1 of the project, 3 out of 6 adult patients weighing <50kg were overdosed on paracetamol, meaning that 50% of low weight patients were prescribed the wrong dose of paracetamol for their weight. In the second data collection cycle, 1 out of 5 <50kg patients were overdosed (20%) and in the third cycle, 1 out of 4 (25%). The use of educational posters resulted in a lower prevalence of accidental iatrogenic paracetamol overdose in low body weight adult inpatients. However, the differences observed were statistically insignificant (p value 0.993 and 0.995 respectively). Educational posters did not induce a significant decrease in the prevalence of accidental iatrogenic paracetamol overdose. More robust strategies need to be employed to further decrease paracetamol overdose in patients weighing <50kg.

Keywords: iatrogenic, overdose, paracetamol, patient, safety

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Authors: Nesengani Elelwani Clinton

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This paper presents reflective learning as an opportunity commonly available and used for food waste learning in a food processing company in the transition to sustainable and just food systems. In addressing how employees learn about food waste during food processing, the opportunities available for food waste learning were investigated. Reflective learning appeared to be the most used approach to learning about food waste. In the case of food waste learning, reflective learning was a response after employees wasted a substantial amount of food, where process controllers and team leaders would highlight the issue to employees who wasted food and explain how food waste could be reduced. This showed that learning about food waste is not proactive, and there continues to be a lack of structured learning around food waste. Several challenges were highlighted around reflective learning about food waste. Some of the challenges included understanding the language, lack of interest from employees, set times to reach production targets, and working pressures. These challenges were reported to be hindering factors in understanding food waste learning, which is not structured. A need was identified for proactive learning through structured methods. This is because it was discovered that in the plant, where food processing activities happen, the signage and posters that are there are directly related to other sustainability issues such as food safety and health. This indicated that there are low levels of awareness about food waste. Therefore, this paper argues that food waste learning should be proactive. The proactive learning approach should include structured learning materials around food waste during food processing. In the structuring of the learning materials, individual trainers should be multilingual. This will make it possible for those who do not understand English to understand in their own language. And lastly, there should be signage and posters in the food processing plant around food waste. This will bring more awareness around food waste, and employees' behaviour can be influenced by the posters and signage in the food processing plant. Thus, will enable a transition to a just and sustainable food system.

Keywords: sustainable and just food systems, food waste, food waste learning, reflective learning approach

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Authors: Zoirov Amirdin Olimovich, Akbarov Elbek Elmurodovich

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Introduction: Pneumonia that occurs during COVID-19 infection is common among patients. This research was conducted to determine the frequency of symptoms occurring during pneumonia according to the purpose. Objective and Task: The goal of our research is to develop clinical concepts of pneumonia that occur during COVID-19 infection. Our main task is to analyze the results of blood tests and understand the progression of the disease. Research Materials and Methods: The research was conducted among patients admitted to the Tashkent Medical Academy multi-profile clinic in the department of infectious diseases undergoing stationary treatment with a diagnosis of COVID-19. The analyzed patients had an average age of 46, with a total of 48 patients, 23 of whom were female and 25 were male. Research Results: The research results showed the development of pneumonia within three days in 27 patients after COVID-19 infection. During the observation period, 24 patients (88.8%) recovered completely. The X-ray revealed no signs of pneumonia in those who fully recovered. The remaining three patients showed a persistent form of pneumonia. Conclusion: The conclusion of the research indicates that pneumonia during COVID-19 infection develops in many patients, and 88.8% of patients recover completely without any lingering symptoms.

Keywords: COVID-19, pneumonia, the X-ray, blood, TTA

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Authors: Dzatur Rizqi Fathienah Syarifuddin, Isharyah Sunarno, Eddy Hartono, Siti Maisuri T. Chalid

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Introduction: The potential impact of coronavirus disease 2019 (COVID-19) on the health of expectant mothers and fetuses has strained attention. Pregnant women are considered a vulnerable category to respiratory infections. Moreover, several inflammatory cytokines are 2-100 times more abundant in COVID-19 with cytokine storms than in normal individuals; interleukin 6 (IL-6) exhibits much higher elevations. Investigating potential relationships between IL-6 serum levels and the severity of COVID-19 symptoms in pregnant women is the aim of this study. Material and Methods: Sixty-two eligible pregnant women were divided into a positive COVID-19 group (n=31) and a negative COVID-19 group (n=31) in this cross-sectional study. The research subjects were selected using consecutive sampling. The IL-6 was measured from a vein blood specimen using ELISA methods. Results: The COVID-19 positive group had a higher median IL-6 serum level (45.35 (35.15- 153.99) vs. 38.86 ± 11.43 (15.02-59.52), p=0.03) than the negative group. On the other hand, the IL-6 serum level had comparable value according to the COVID-19 symptoms severity (88.35 ± 36.14 ng/mL vs. 51.09 ± 25.48 ng/mL vs. 56.02 ± 33.20 ng/mL in moderate symptoms, mild symptoms, and asymptomatic, respectively; p=0.152). Conclusion: Although the IL-6 serum levels are not related to COVID-19 symptoms severity, an elevated of this biomarker was found in pregnant women with affected diagnoses.

Keywords: interleukin-6, pregnancy, COVID-19, several inflammatory

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Mohammed Al-Shalabi

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In recent years, the Internet of Things (IoT) has become an important technology for connecting various smart objects in many applications, especially in health monitoring applications. The IoT technology develops healthcare applications from traditional to personalized ones by making the treatment and monitoring of patients easier. Nowadays, especially during the COVID-19 pandemic, the necessity of enhancing healthcare monitoring applications to avoid the spreading of this pandemic is increased. In this paper, a mechanism is proposed to minimize direct contact with COVID-19 patients who need ventilators by using IoT technology. The proposed mechanism saves medical providers from COVID-19 infection and then minimizes the spreading of this disease.

Keywords: internet of things, healthcare monitoring, COVID-19, ventilators, thingspeak, clouds

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Authors: Melissa Vang, Raheyma Khan, Haihua Chen

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The coronavirus disease 2019 (COVID‐19) pandemic has changed people's lives from all over the world. More people have turned to Twitter to engage online and discuss the COVID-19 vaccine. This study aims to present a text mining approach to identify people's attitudes towards the COVID-19 vaccine on Twitter. To achieve this purpose, we collected 54,268 COVID-19 vaccine tweets from September 01, 2020, to November 01, 2020, then the BERT model is used for the sentiment and topic analysis. The results show that people had more negative than positive attitudes about the vaccine, and countries with an increasing number of confirmed cases had a higher percentage of negative attitudes. Additionally, the topics discussed in positive and negative tweets are different. The tweet datasets can be helpful to information professionals to inform the public about vaccine-related informational resources. Our findings may have implications for understanding people's cognitions and feelings about the vaccine.

Keywords: BERT, COVID-19 vaccine, sentiment analysis, topic modeling

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Authors: Chijindu Okpalaoka, Charles Chinedu Onuselogu

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COVID-19, humanity's coronavirus disease caused by SARS-CoV-2, was first detected in late 2019 in Wuhan, China. COVID-19 lacked an established conventional pharmaceutical therapy, and as a result, the outbreak quickly became an epidemic affecting the entire World. Only a qPCR assay is reliable for diagnosing COVID-19. Clustered, regularly interspaced short palindromic repeats (CRISPR) technology is being researched for speedy and specific identification of COVID-19, among other therapeutic techniques. Apart from its therapeutic capabilities, the CRISPR technique is being evaluated to develop antiviral therapies; nevertheless, no CRISPR-based medication has been approved for human use to date. Prophylactic antiviral CRISPR in living being cells, a Cas 13-based approach against coronavirus, has been developed. While this method can be evolved into a treatment approach, it may face substantial obstacles in human clinical trials for licensure. This study discussed the potential applications of CRISPR-based techniques for developing a speedy and accurate feasible treatment alternative for the COVID-19 virus.

Keywords: COVID-19, CRISPR technique, Cas13, SARS-CoV-2, prophylactic antiviral

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Authors: Dhurgham Al-Karawi, Nisreen Polus, Shakir Al-Zaidi, Sabah Jassim

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The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.

Keywords: COVID-19, chest x-ray scan, artificial intelligence, texture analysis, local binary pattern transform, Gabor filter

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Authors: Sireethorn Nimitvilai, Ussanee Poolvivatchaikarn, Nuchanart Tomeun

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Objective: To determine the simple laboratory parameters to predict disease severity among COVID-19 patients in resource-limited settings. Material and methods: A retrospective cohort study was conducted at Nakhonpathom Hospital, a 722-bed tertiary care hospital, with an average of 50,000 admissions per year, during April 15 and May 15, 2021. Eligible patients were adults aged ≥ 15 years who were hospitalized with COVID-19. Baseline characteristics, comorbid conditions ad laboratory findings at admission were collected. Predictive factors for severe COVID-19 infection were analyzed. Result: There were 207 patients (79 male and 128 female) and the mean age was 46.7 (16.8) years. Of these, 39 cases (18.8%) were severe and 168 (81.2%) cases were non-severe. Factors associated with severe COVID-19 were neutrophil to lymphocyte ratio ≥ 4 (OR 8.1, 95%CI 2.3-20.3, P < 0.001) and C-reactive protein to albumin ratio ≥ 10 (OR 3.49, 95%CI 1.3-9.1, p 0.01). Conclusions: Complete blood counts, C-reactive protein and albumin are simple, inexpensive, widely available tests and can be used to predict severe COVID-19 in resource-limited settings.

Keywords: COVID-19, predictor of severity, resource-limiting settings, simple laboratory parameters

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Authors: Hilary P. Stevenson, Alexander J. Hayek, Amie Dereczyk

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In this case report, we provide an example of an asymptomatic COVID-19 positive patient who presented with new-onset psychosis with severe paranoid delusions. He was seen in our ED after ingesting isopropyl alcohol which he reported was an attempt to escape presumed attackers, which at the time was logical to the patient. The patient’s family had COVID-19 symptoms that corresponded to those typically observed from the Omicron variant. The patient was treated successfully, within ten days, with Risperdal twice-daily dosing resulting in the resolution of the patient’s delusions and improved insight regarding the events that led to his hospitalization. In this work, we examine possible contributing factors to new-onset psychosis in the context of COVID-19, a phenomenon that is becoming increasingly notable in the literature. One area of importance is the already established inflammatory hypothesis of psychosis in which defects in the innate immune system, which result in its overactivation, may play a role in a typical first-episode psychosis, in addition to subsequent episodes. Given that COVID-19 is known to cause derangements in the innate immune system, such as cytokine storm reactions, this link may be critical in further understanding the etiologies of new-onset COVID-19 psychosis and its risk factors. Also included in this work is a brief review of antipsychotic interventions that have been described in the literature to date for the first episode of COVID-19-related psychosis. This will explore the potential of some antipsychotics to innately diminish the production of pro-inflammatory cytokines, further enhancing their usefulness in COVID-19 first-episode psychosis patients.

Keywords: COVID-19, first break psychosis, inflammatory hypothesis of psychosis, Risperdal

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Authors: Le-Quyen Nguyen, Hoang Van Bui, Ngoc Thi Tran, Binh Thanh Le, Linus Olson, Thanh Quang Le

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Objective: We compared of outcomes between infected and non-infected COVID-19 pregnant at the largest obstetrics and gynecology hospital in southern Vietnam. Materials and Methods: A retrospective study was conducted at gestational age (GA) 28-42 weeks, who terminated pregnancy and had a real-time PCR test for SARS-CoV-2 at Tu Du Hospital. Demographic, clinical, laboratory, and epidemiological data were collected from hospital electronic-medical-records. Diagnosis and screening of SARS-CoV-2 used Real-time-PCR. Results: From July to October 2021, 9,246 pregnant with GA of 28-42 weeks were delivered, including 664 infected with COVID-19 and 8,582 non-infected. The cesarean section (CS) rates of pregnant with and without COVID-19 were 47.3% and 46.0%. At GA 32-34 weeks, the rate of CS with COVID-19 was 5.07 times higher than without. The rate of postpartum hemorrhage (PPH) and the Apgar score between these two groups were similar. The mortality rate of infected pregnants was 2.26%. Conclusions: COVID-19 infection increased the CS rate in the group of preterm pregnancies from 32 to less than 34 weeks. COVID-19 did not increase the risk of complications related to adverse pregnancy outcomes such as PPH, Apgar scores, the ratio of stillbirths, deaths due to malformation, and fetal deaths in labor.

Keywords: COVID-19, SARS-CoV-2, pregnancy, outcome, vietnam

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Authors: Mubarak Jan Beebee Zeba Mahetaab, Sumera Bibi Keenoo

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Background: Covid-19 was first reported in Wuhan. On 13th March 2020, WHO declared Covid-19 as a pandemic disease with 140,936 cases globally. The outbreak of covid-19 occurred in over 184 countries, and it created a lot of medical and mental burdens. Aside from the physical problems, the mental health of the medical staff has been of critical concern. Aims and Objectives: To determine the prevalence of burnout among HCW dealing with COVID-19, identify the risk factors and find measures to support their mental health while dealing with the current and future pandemic. Methodology: A cross-sectional study was conducted among the HCW who fought against COVID-19 in SSRN Hospital in Mauritius. The HCWs were recruited using the snowballing sampling technique. Age, gender, job category, income, duration of vacation, working environment and importance of mental health were measured. Results: The prevalence of burnout was highest among HCA. Age had no significant association with pandemic-related burnout. In Mauritius, burnout during the pandemic is linked with lower income and having less vacation days. Conclusion: Burnout is prevalent among healthcare workers working during the Covid-19 Pandemic. Interventions such as psychological counselling, yoga and financial increments need to be implemented to help the healthcare workers.

Keywords: burnout, Covid-19, health care professionals, pandemic

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Süleyman Günes

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The crucial effects of the COVID-19 pandemic have on social and economic systems in Turkey as well as all over the world. It has impacted logistic providers and worldwide supply chains. Unexpected risks played a central role in creating vulnerabilities for logistics service operations during the pandemic terms. This study aims to research and design qualitative and quantitive contributions to logistic services. The COVID-19 pandemic brought unavoidable risks to the logistics industry in Turkey. The Logistic Service Providers (LSPs) have learned how to ensure uncertainties and risks triggered by main and adverse effects. The risks that LSPs encounter during the COVID-19 pandemic have been investigated and unveiled, and identified uncertainties and risks. The cause-effect structures were displayed by the qualitative and quantitive studies. The results suggest that supply chains and demand changes triggered by the COVID-19 pandemic while it influenced financial failure and forecast horizon with operational performances.

Keywords: logistic service providers, COVID-19, development, financial failure

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Authors: Gabriel Hunduma

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Asymptomatic intra-thoracic neurogenic tumours are rare. Tumours arising from the intercostal nerves of the chest wall are exceedingly rare. This paper reports an incidental discovery of a neurogenic intercostal tumour while being investigated for Coronavirus Disease 2019 (COVID-19). A 54-year-old female underwent a thoracotomy and resection for an intercostal tumour. Pre-operative images showed an intrathoracic mass, and the biopsy revealed a schwannoma. The most common presenting symptom recorded in literature is chest pain; however, our case remained asymptomatic despite the size of the mass and thoracic area it occupied. After an extensive search of the literature, COVID-19 was found to have an influence on the development of certain cells in breast cancer. Hence there is a possibility that COVID-19 played a role in progressing the development of the schwannoma cells.

Keywords: thoracic surgery, intercostal schwannoma, chest wall oncology, COVID-19

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Authors: Pugazhenthan Thangaraju

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Background: Since the pandemic began, more than millions of people have become infected with COVID-19. Globally, researchers are working for safe and effective treatments for this disease. Remdesivir is a drug that has been approved for the treatment of COVID-19. Many aspects are still being considered that may influence the future use of remdesivir. Aim: To assess the safety and efficacy of Remdesivir in hospitalized adult patients diagnosed with moderate and severe COVID-19. Methods: It was a record-based retrospective cohort study conducted between April 1st, 2020 and June 30th, 2021 at the tertiary care teaching hospital All India Institutes of Medical Sciences (AIIMS), Raipur Results: There were a total of 10,559 medical records of COVID-19 patients of which 1034 records were included in this study. Overall, irrespective of the survival status, there was statistical significant difference observed between the WHO score at the time of admission and discharge. Clinical improvement among the survivors was found to be statistically significant. Conclusion: Remdesivir's potential efficacy against coronaviruses has so far been limited to in vitro studies and animal models. However, information about COVID-19 is rapidly expanding. Several clinical trials for the treatment of COVID-19 with remdesivir are now underway. However, the findings of this study support remdesivir as a promising agent in the fight against SARS-CoV-2.

Keywords: Remdesivir, COVID-19, SARS-CoV-2, antiviral, RNA-dependent RNA polymerase, viral pneumonia

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Authors: Teklay Gebrecherkos, Dawit Wolday, Muhamud Abdulkader

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Background: COVID-19 symptomatology in Africa appears significantly less serious than in the industrialized world. Our hypothesis for this phenomenon, being a different, more activated immune system due to parasite infections contributes to reduced COVID-19 outcome. We investigated this hypothesis in an endemic area in sub sub-saharan Africa. Methods: Ethiopian COVID-19 patients were enrolled and screened for intestinal parasites, between July 2020 and March 2021. The primary outcome was the proportion of patients with severe COVID-19. SARS-CoV-2 infection was confirmed by RT-PCR on samples obtained from nasopharyngeal swabs, while direct microscopic examination, modified Ritchie concentration, and Kato-Katz methods were used to identify parasites and ova from a fresh stool sample. Ordinal logistic regression models were used to estimate the association between parasite infection and COVID-19 severity. Models were adjusted for sex, age, residence, education level, occupation, body mass index, and comorbidities. Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant. Results: A total of 751 SARS-CoV-2 infected patients were enrolled, of whom 284 (37•8%) had an intestinal parasitic infection. Only 27/255 (10•6%) severe COVID-19 patients were co-infected with intestinal parasites, while 257/496 (51•8%) non-severe COVID-19 patients appeared parasite positive (p<0.0001). Patients co-infected with parasites had lower odds of developing severe COVID-19, with an adjusted odds ratio (AOR) of 0•14 (95% CI 0•09–0•24; p<0•0001) for all parasites, AOR 0•20 ([95% CI 0•11–0•38]; p<0•0001) for protozoa, and AOR 0•13 ([95% CI 0•07–0•26]; p<0•0001) for helminths. When stratified by species, co-infection with Entamoeba spp., Hymenolopis nana, and Schistosoma mansoni implied a lower probability of developing severe COVID-19. There were 11 deaths (1•5%), and all were among patients without parasites (p=0•009). Conclusions: Parasite co-infection is associated with a reduced risk of severe COVID-19 in African patients. Parasite-driven immunomodulatory responses may mute hyper-inflammation associated with severe COVID-19.

Keywords: COVID-19, SARS-COV-2, intestinal parasite, RT-PCR, co-infection

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Authors: Omar Sorour, Michael Leahy, Thomas Irvine, Vladimir Koren

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Introduction: Covid encephalitis is a rare yet dangerous complication, particularly affecting the older and immunocompromised. Symptoms range from confusion to delirium, coma, and seizures. Although neurological manifestations have become more well-characterized in COVID patients, little is known about whether priorneurological abnormalities may predispose patients to COVID encephalopathy. Case Description: A 73 y.o. male with a CT and MRI-confirmed stable, prior 9 mm cavernoma in the right frontal lobe and no past history of seizures was hospitalized with generalized weakness, abdominal pain, nausea, and shortness of breath with subsequent COVID pneumonia. Three days after the initial presentation, the patient developed a spontaneous generalized tonic-clonic seizure consistent with presumed COVID encephalitis, along with somnolence and confusion. A day later, the patient had two other seizure episodes. Follow-up EEG suggested an inter-ictal epileptic focus with sharp waves corresponding to roughly the same location as the patient’s pre-existing cavernoma. The patient’s seizures stopped shortly thereafter, while his encephalopathy continued for days. Conclusion: We illustrate that a pre-existing anatomic cortical abnormality may act as a potential nidus for new-onset seizure activity in the context of suggested COVID encephalopathy. Future studies may further demonstrate that manifestations of COVIDencephalopathy in certain patients may be more predictable than initially assumed.

Keywords: cavernoma, covid, encephalopathy, seizures

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Authors: Samuel Fernandes, Dylan Kato, Emin Burak Onat, Patrick Keyantuo, Raja Sengupta, Amine Bouzaghrane

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The COVID-19 pandemic has spread across the United States, forcing cities to impose stay-at-home and shelter-in-place orders. Building operations had to adjust as non-essential personnel worked from home. But as buildings prepare for personnel to return, they need to plan for safe operations amid new COVID-19 guidelines. In this paper we propose a methodology for capacity and flow modeling of personnel within buildings to safely operate under COVID-19 guidelines. We model personnel flow within buildings by network flows with queuing constraints. We study maximum flow, minimum cost, and minimax objectives. We compare our network flow approach with a simulation model through a case study and present the results. Our results showcase various scenarios of how buildings could be operated under new COVID-19 guidelines and provide a framework for building operators to plan and operate buildings in this new paradigm.

Keywords: network analysis, building simulation, COVID-19

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Authors: Mark Linden, Michael Brown, Lynne Marsh, Maria Truesdale, Stuart Todd, Nathan Hughes, Trisha Forbes, Rachel Leonard

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Background: The COVID-19 pandemic exacerbated the already significant strain placed on family carers of people with profound and multiple intellectual disabilities (PMID), given the withdrawal of many services during lockdown. The aim of this study was to explore the experiences of family carers of people with PMID during the COVID-19 pandemic. Methods: Online focus groups were conducted with family carers (n=126) from across the UK and the Republic of Ireland. Participants were asked about their experiences of the COVID-19 pandemic, coping strategies, and challenges faced. Focus groups were audio recorded, transcribed verbatim and analyzed through thematic analysis. Findings: Three themes emerged from our analysis of the data: (i) COVID-19 as a double-edged sword, (ii) The struggle for support (iii) the Constant nature of caring. These included 11 subthemes: (i) ‘COVID-19 as a catalyst for change’, ‘Challenges during COVID-19: dealing with change’, ‘Challenges during COVID-19: fear of COVID-19’, ‘The online environment: the new normal’ (ii) ‘Invisibility of male carers’, ‘Carers supporting carers’, ‘The only service you get is lip service: non-existent services’, ‘Knowing your rights’ (iii) ‘Emotional response to the caring role: Feeling devalued’, ‘Emotional response to the caring role: Desperation of caring’, ‘Multiple demands of the caring role.’ Conclusions: Poor or inconsistent access to services and support has been an ongoing difficulty for many family carers. The COVID-19 pandemic has only further intensified these difficulties, increasing family carers' stress. There is an urgent need to design services, such as online support programs, in partnership with family carers that adequately address their needs.

Keywords: intellectual disabilities, family carer, COVID-19, disability

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Authors: Victoria Wolf, Renata Dobrucka, Robert Prezkop, Stephan Haubold

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The COVID-19 causes a worldwide crisis and has an impact in every dimension of the economy. Organizations with the ability to adapt to new developments and which innovate solutions for the disrupted world during and after the Corona crises have the opportunity to not only survive the crisis but rather to use new trends to implement new business models and gain advantage. In this context, startups seem to have better opportunities to manage the Corona crisis through their innovation-based nature. The main result of this paper is the understanding that by applying a startup orientated innovation (SOCI) strategy, established companies can be motivated to meet the challenge of COVID-19 in a similar way like startups. This result can be achieved by describing the role of innovation and a SOCI strategy as helpful methods for organizations to meet the coming challenges during and after the COVID-19 epidemics. In addition to this, this paper presents a practical application of SOCI through the PANDA approach of the Fresenius University of Applied Sciences in Germany and discuss it in the context of COVID-19 as an exemplary successful real-world implementation of SOCI strategy.

Keywords: Covid-19, innovation, open innovation, startup, soci framework

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Authors: Dennis Schmickle

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Introductory statement: Augmented reality (AR) can be used to breathe life into traditional graphic design media, such as posters, book covers, and album art. AR superimposes a unique image/video on a user’s view of the real world, which makes it more immersive and realistic than traditional 2D media. This study developed a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. The results of this study suggest that AR can be an effective tool for teaching graphic design. Abstract: Traditional graphic design media, such as posters, book covers, and album art, could be considered to be “old media.” However, augmented reality (AR) can breathe life into these formats by making them more interactive and engaging for students and audiences alike. AR is a technology that superimposes a computer-generated image on a user’s view of the real world. This allows users to interact with digital content in a way that is more immersive and interactive than traditional 2D media. AR is becoming increasingly popular, as more and more people have access to smartphones and other devices that can support AR experiences. This study is comprised of a series of projects that utilize both traditional and AR media to teach the fundamental principles of graphic design. In these projects, students learn to create traditional design objects, such as posters, book covers, and album art. However, they are also required to create an animated version of their design and to use AR software to create an AR experience with which viewers can interact. The results of this study suggest that AR can be an effective and exciting tool for teaching graphic design. The students who participated in the study were able to learn the fundamental principles of graphic design, and they also developed the skills they need to create effective AR content. This study has implications for the future of graphic design education. As AR becomes more popular, it is likely that it will become an increasingly important tool for teaching graphic design.

Keywords: graphic design, augmented reality, print media, new media, AR, old media

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Authors: Ida Shafinaz Mohamed Kamil, Mohd Dahlan Abdul Malek

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Today, the whole world is facing a catastrophe called the novel coronavirus disease known as COVID-19. As of October 2021, it has been reported that more than 248 million cases and 5 million deaths have been recorded worldwide. In Malaysia, 2,466,663 cases were reported, with 28,876 deaths recorded on 30 October 2021. Unfortunately, the world is not only facing the COVID-19 pandemic but the COVID-19 infodemic as well, where fake news about COVID-19 disease is spreading faster and more widely than from the virus itself. The spread of fake news is amplified through various social media platforms, which is causing concern among the community. The uncertainty in understanding what fake news really is has caused difficulties and challenges in providing a solution to the hazards that it creates. This article discusses what constitutes fake news and examines the current legal framework put in place to combat fake news in Malaysia. Employing a doctrinal research methodology, this article thoroughly analyzes the relevant legal provisions under the Communications and Multimedia Act 1998, the Penal Code and the Emergency (Essential Powers) Ordinance (No.2) 2021, which came into force on 12 March 2021 as well as related case laws, for offenses and punishments with regards to fake news. The findings from the analysis indicate that there is still room for improvement in regulating fake news, in particular concerning COVID-19.

Keywords: fake news, legal pespective, covid 19, pendemic

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Authors: Siriniya Siribrahmanakul

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Introduction:SARsCOVID-19 is rapidly spreading, and some people may exhibit severe symptoms. Mortality rate of 2.0–3.0% with COVID-19 infection atworldwide. Human leukocyte antigen (HLA), located on chromosome 6, consist of HLA class I and class II. HLA are used by the immune system to attach self-antigens. Previous studies, HLA-DRB1*01:01,HLA-DRB1*12:01and HLA-DRB1*14:04 were, showed significant difference with severe COVID-19 in the Chinese population by p-value < 0.05. Objective: We investigated the prevalence of HLA-DRB1 alleles associated with severe COVID-19 in Thai population. Materials and Methods:200 DNA samples were isolated from EDTA blood using the MagNAprue Compact Nucleic Acid Isolation kits.HLA-DRB1alleles were genotyped using sequence-specific oligonucleotides (PCR-SSOs). Results:The frequency of HLA-DRB1 alleles in Thai population wereHLA-DRB1*12:02 (15.75%), HLA-DRB1*15:02 (14.50%), HLA-DRB1*09:01 (11.50%), HLA-DRB1*07:01 (9.50%), HLA-DRB1*03:01,HLA-DRB1*05:01 (5.75%), HLA-DRB1*14:01 (5.50%), HLA-DRB1*16:02 (4.50%), HLA-DRB1*04:05 (4.00%), HLA-DRB1*14:03 (3.25%), HLA-DRB1*10:01 (2.25%) and HLA-DRB1*13:02 (2.00%). Particularly, HLA-DRB1*12:02 allele was the highest allele frequency presented in the four regions groups of Thai population. Furthermore, the HLA-DRB1* alleles associated with severe COVID-19, which consists ofHLA-DRB1*14:04(2.00 %) and HLA-DRB1*12:01(0.50%) in Thai population, whereas HLA-DRB1*01:01 allele was not found in this population. HLA-DRB1*14:04 and HLA-DRB1*12:01alleles were similarly distributed in four regions populations in Thailand (p-value > 0.05). The alleles frequencies of HLA-DRB1*14:04 and HLA-DRB1*12:01, which associated with severe COVID-19, had no significant differences between Thai population, South China population, South Africa population, and South Koreapopulation (p-value > 0.05). Conclusions: Particularly, this study has focused on allele frequency of HLA-DRB1*14:04in a healthy Thai population to evaluating their impact on the severe COVID-19. Furthermore, our research needs to be done in larger numbers of Thai patients.

Keywords: HLA-DRB1, allele frequency, Thai population, COVID-19 marker

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Authors: Aleena Rena Onozuka, Patompong Satapornpong

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Introduction: In a Human Leukocyte Antigen (HLA)’s immune response, HLA alleles (HLA class I and class II) play a crucial role in fighting against pathogens. HLA-B*15:01 allele had a significant association with asymptomatic COVID-19 infection (p-value = 5.67 x 10-5 ; OR = 2.40 and 95% CI = 1.54 - 3.64). There was also a notable linkage between HLA-B*51:01 allele and critically ill patients with COVID-19 (p-value = 0.007 and OR = 3.38). This study has described the distribution of HLA marker alleles in Thais and sub-groups. Objective: We want to investigate the prevalence of HLA-B*15:01 and HLA-B*51:01 alleles in the Thai population. Materials and Methods: 200 healthy Thai population were included in this study from the College of Pharmacy, Rangsit University. HLA-B alleles were genotyped using the sequence-specific oligonucleotides process (PCR-SSOs). Results: We found out that HLA-B*46:01 (12.00%), HLA-B*15:02 (9.25%), HLA-B*40:01 (6.50%), HLA-B*13:01 (6.25%), and HLA-B* 38:02 (5.50%) alleles were more common than other alleles in Thai population. HLA-B*46:01 and HLA-B*15:02 were the most common allele found across four regions. Moreover, the frequency of HLA-B*15:01 and HLA-B*51:01 alleles were similarly distributed in Thai population (0.50, 5.25 %) and (p-value > 0.05), respectively. The frequencies of HLA-B*15:01 and HLA-B*51:01 alleles were not significantly different from other populations compared to the Thai population. Conclusions: We can screen for HLA-B*15:01 and HLA-B*51:01 alleles to determine the symptoms of COVID-19 since they are universal HLA-B markers. Importantly, the database of HLA markers indicates the association between HLA frequency and populations. However, we need further research on larger numbers of COVID-19 patients and in different populations.

Keywords: HLA-B*15:01, HLA-B*51:01, COVID-19, HLA-B alleles

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Authors: Sean Sloan

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Probability Risk Assessments (PRA) can be a difficult concept for students to grasp. So in searching for different ways to describe PRA to relate it to their lives; COVID-19 came up. The parallels are amazing. Soon students began analyzing acceptable risk with the virus. This helped them to quantify just how dangerous is dangerous. The original lesson was dismissed and for the remainder of the period, the probability of risk, and the lethality of risk became the topic. Spreading events such as a COVID carrier on an airline became analogous to single fault casualties such as a Tsunami. Odds of spreading became odds of backup-diesel-generator failure – like with Fukashima Daiichi. Fatalities of the disease became expected fatalities due to radiation spread. Quantification from this discussion took it from hyperbole and emotion into one where we could rationally base guidelines. It has been one of the most effective educational devices observed.

Keywords: COVID, education, probability, risk

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Authors: Viknesh Kasthuri, Victoria Angenent-Mari, Jade Wexler

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The COVID-19 pandemic dramatically altered the landscape of asylum medicine. Brown Human Rights Asylum Clinic (BHRAC) is a medical-student-run asylum clinic that provides pro-bono medical evaluations and forensic affidavits for individuals seeking asylum in New England. After the outbreak of COVID-19 in March 2020, BHRAC experienced numerous changes both in the number of clients requesting services as well as in the resource needs of these clients. Uniquely, BHRAC assesses the needs of clients during their affidavit interview and seeks to address these needs by connecting clients to local community organizations and resources. Data regarding the specific needs of clients range from 2019-present day. Analysis of internal BHRAC’s internal data suggested a small increase in requests for assistance with light and gas (from 5% of total resource requests pre-COVID to 11%), as well as a decrease in requests for mental health services (from 20% of resources pre-COVID to 13% post-COVID). Furthermore, BHRAC witnessed a decline in clinic volume during the second half of 2020. In short, our data suggest that the pandemic affected asylum seekers' access to medico-legal services and the resources they need. Future research with larger sample sizes and in other geographic locations is required to determine the holistic impact of the COVID-19 pandemic on asylum seekers.

Keywords: asylum clinic, asylum medicine, COVID, social determinants of health

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Vittoria Franchina, Laura Salerno, Rubinia Celeste Bonfanti, Gianluca Lo Coco

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This study examines the relationships between existential concerns (ECs), basic psychological needs (BPNs), vaccine hesitancy (VH), and the mediating role of negative attitudes toward COVID-19 vaccines. A cross-sectional survey was carried out on a sample of two-hundred eighty-seven adults (Mage = 36.04 (12.07); 59.9% females). Participants were recruited online through clickworker and filled in measures on existential concerns, basic psychological needs, attitudes toward COVID-19 vaccines, and vaccine hesitancy for Pfizer-BioNTech and Astrazeneca vaccines separately. Structural equation modelling showed that existential concerns were related to Pfizer-BioNTech and Astrazeneca vaccine hesitancy both directly and indirectly through negative attitudes toward possible side effects of COVID-19 vaccines. The present study has identified several predictive factors relating to the intention to uptake vaccination to protect against COVID-19 in Italy. Specifically, these findings suggest a causal link between existential concerns, attitudes, and vaccine hesitancy.

Keywords: COVID-19, existential concerns, Pfizer-BioNTech and Astrazeneca vaccines, vaccine hesitancy

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