ABSTRACT
Background. Surveys on Public Knowledge, Attitude, and Practice (PKAP) have been conducted in various countries with respondents from the public as well as health workers. Measuring the knowledge of the public about COVID-19 is very important to determine the knowledge gap among the public and also as an evaluation of the preventive efforts for COVID-19. Objective. The purpose of this research was to determine whether education level is a factor that affects one's literacy about COVID-19. Materials and Methods. This is cross-sectional research with online-based data collection using the Kobo toolbox application. The data collection was carried out from the 19th of April until the 2nd of May 2020. The number of people under study is 792. The level of knowledge was measured using 12 research questions with true or false question types. the multivariable logistic regression was carried out. Results. Most of the respondents (52.5%) were in the young age group (15-35 years old), were male (57.3%), and had a bache-lor or diploma education level (62.1%). Furthermore, most of the respondents had good knowledge (65.4%). The higher the respon-dents' educational level means, the better knowledge they had concerning COVID-19 (P=0.013). Conclusions. Public knowledge about COVID-19 is affected by their level of education. A good level of knowledge about COVID-19 was found among respondents with master's and doctoral degrees. This finding can contribute to the prevention of COVID-19, in which the priority of educating communities about COVID-19 should be given to those having an educational level below a master's degree.Copyright © the Author(s), 2023.
ABSTRACT
This paper describes the continuation of a project that aims at establishing an interoperable annotation scheme for quantification phenomena as part of the ISO suite of standards for semantic annotation, known as the Semantic Annotation Framework. After a break, caused by the Covid-19 pandemic, the project was relaunched in early 2022 with a second working draft, which deals with certain issues in the annotation of quantification in a more satisfactory way than the original first working draft.
ABSTRACT
Deaths from COVID-19 are increasing in patients with comorbidities. One of the most common comorbidities is diabetes mellitus. The researchers wanted to see how having diabetes affected the mortality rate of COVID-19 participants. This investigation is a case control observational analytical study. Different types of people, called "cases," and "controls," complete the research sample. Each group had 68 responders, for a grand total of 136. Medical records from COVID-19 patients treated at Airlangga University Hospital, Surabaya, between March 2020 and September 2021 serve as the study's secondary data source. The purpose of this study's data analysis is to calculate an odds ratio. Patients with COVID-19 with concomitant diabetes mellitus had an increased risk of death, and this risk increased with age, gender, and COVID-19 symptoms. In contrast, education, occupation, and laboratory results were not significantly related to mortality among COVID-19 individuals with concomitant diabetes mellitus (GDA status). The results of this study show that COVID-19 patients with concomitant diabetes mellitus are at a higher risk of death if they are over the age of 65, if they are male, and if they have severe symptoms. Copyright © the Author(s),2022.
ABSTRACT
While the world has been combating COVID, there has also been an ongoing “Infodemic,” caused by the spread of fake news about the pandemic. Due to the rapid data sharing on social media, the impact of fake news can be quite damaging. Citizens might mistake fakes news for real news. Human lives have been lost due to fake information about COVID. Our goal is to identify fake news on social media and help stem the spread by deep learning approaches. To understand the different characteristics in fake and real news, we conducted behavioral and sentiment analyses between fake and real news regarding the COVID pandemic. We then further built detection models based on feature elimination, and we identified differences of model robustness based on selected features. © 2022, by the authors. All rights reserved.
ABSTRACT
The COVID-19 (2019 Novel Coronavirus Pneumonia) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the most severe challenge facing mankind in a century. After Wuhan, a city in China became the epicenter of the outbreak of COVID-19 in December 2019, multiple countries have experienced multiple waves of the disease. Scientific experts have been working on the characteristics of COVID-19 with the aim of finding the most appropriate way to control the virus. This phenomenon has reinforced the strong need to develop a vaccine to control the rate and spread of infection. In view of the global importance attached to COVID-19, this article mainly reviews the basic biological characteristics, sources and transmission routes of SARS-CoV-2, and provides an overview of the current clinical trials of representative new coronavirus vaccines (including inactivated vaccines, live attenuated vaccines, recombinant vector vaccines, subunit vaccines and nucleic acid vaccines) to summarize and analyze the advantages and disadvantages of various COVID-19 vaccines on the market today, and provide reference suggestions for the design and optimization of COVID-19 vaccines. © 2021, Editorial Board of Pharmaceutical Biotechnology. All right reserved.
ABSTRACT
During the COVID-19 pandemic, there has been an emerging need for rapid, dedicated, and point-of-care COVID19 patient disposition techniques to optimize resource utilization and clinical workflow. In view of this need, we present COVIDMobileXpert: a lightweight deep neural network (DNN) based mobile app that can use chest X-ray (CXR) for COVID-19 case screening and radiological trajectory prediction. We design and implement a novel three-player knowledge transfer and distillation (KTD) framework including a pre-trained attending physician (AP) network that extracts CXR imaging features from a large scale of lung disease CXR images, a fine-tuned resident fellow (RF) network that learns the essential CXR imaging features to discriminate COVID-19 from pneumonia and/or normal cases with a small amount of COVID-19 cases, and a trained lightweight medical student (MS) network to perform on-device COVID-19 patient triage and follow-up. To tackle the challenge of vastly similar and dominant fore-and background in medical images, we employ novel loss functions and training schemes for the MS network to learn the robust features. We demonstrate the significant potential of COVID-MobileXpert for rapid deployment via extensive experiments with diverse MS architecture and tuning parameter settings.
ABSTRACT
While largely agreeing with Ruiping Fan, Chenyang Li makes three points regarding the handling of COVID-19. First, in addition to state capacity, social trust, and leadership, as identified by Francis Fukuyama, factors responsible for successful pandemic responses include the value of individual freedom upheld by citizens. A high level of individual freedom can make it difficult to implement strict measures even when they are objectively necessary. Second, a strong state can be effective in handling a pandemic, but without checks and balances it also runs the risk of leading a country into a major catastrophe. Third, Confucian ethics and other ethics can aid in coping with the pandemic. However, their efficacy is not unlimited, and ultimately, human survival overrides other concerns.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is still a global epidemic. Several studies of individuals with severe COVID-19 regard convalescent plasma (CP) transfusion as an effective therapy. However, no significant improvements are found in randomized clinical trials of CP treatment. Until now, data for individuals with mild COVID-19 transfused CP were lacking. This study recruited eight individuals with mild COVID-19 who received at least one dose of CP transfusion. After CP therapy, the clinical symptoms of all individuals improved. Lymphocyte counts tended to increase, and lactate dehydrogenase, creatine kinase and aspartate aminotransferase tended to decrease. However, C-reactive protein increased transiently in three individuals. The median time for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid test to become negative was 2.5 days after CP transfusion. The study shows the potential benefits of CP. Meanwhile, CP probably enhances the inflammatory response to SARS-CoV-2 temporarily in people with insufficient antiviral immunity. However, the effects of CP are not permanent.
ABSTRACT
The pandemic of coronavirus disease 2019 (COVID-19) has posed serious challenges. It is vitally important to further clarify the epidemiological characteristics of the COVID-19 outbreak for future study and prevention and control measures. Epidemiological characteristics and spatial-temporal analysis were performed based on COVID-19 cases from 21 January 2020 to 1 March 2020 in Shandong Province, and close contacts were traced to construct transmission chains. A total of 758 laboratory-confirmed cases were reported in Shandong. The sex ratio was 1.27: 1 (M: F) and the median age was 42 (interquartile range: 32-55). The high-risk clusters were identified in the central, eastern and southern regions of Shandong from 25 January 2020 to 10 February 2020. We rebuilt 54 transmission chains involving 209 cases, of which 52.2% were family clusters, and three widespread infection chains were elaborated, occurring in Jining, Zaozhuang and Liaocheng, respectively. The geographical and temporal disparity may alert public health agencies to implement specific measures in regions with different risk, and should attach importance on how to avoid household and community transmission.