ABSTRACT
As a result of COVID-19, journalists have had to disseminate information on health issues, being in charge of translating complex terms into a language understandable to the general population. Objective: To assess the reading comprehension of communication degree students on news published in the press related to COVID-19;specifically 1) Identify your frequency of exposure to news;2) Determine their perception of risk and 3) assess their understanding of specific terminology. Methodology: Online questionnaire for students of degrees in Journalism, Advertising and Public Relations and Audiovisual Communication, from the UA and the UMH. Results: 79.6% (n=225) frequently read news related to COVID-19 to stay informed about health problems. Less than half of them declared knowing terms such as "prevalence" or "screening"', and less than 20% correctly identified the definition of the concept. Conclusions: Low understanding of specific terminology, which may imply an incorrect perception of risk. © 2023 Universidad Complutense de Madrid. All rights reserved.
ABSTRACT
Background: Multisystem inflammatory syndrome in children (MIS-C) is a post-infectious sequelae of acute COVID-19 infection affecting children. This study was done over a period of 12 months from December 2020 to November 2021 to describe the clinical presentation, laboratory abnormalities, and outcome of children with MIS-C. Method(s): Seventy-eight children below 12 years of age who satisfied the WHO diagnostic criteria for MIS-C were included in the study. Clinical parameters were recorded at admission. Relevant laboratory investigations, radiological studies, and outcome were documented. Result(s): The most commonly affected age group was 6-12 years with a female predominance. COVID RTPCR was negative in all patients. Most cases presented 2-6 weeks after the onset of acute COVID-19 infection. Lethargy, poor feeding, vomiting, abdominal pain, loose stools, cough, and cold are common symptoms of MIS-C syndrome in children and the common signs were rash, conjunctival congestion, hypotension, tachycardia, tachypnea, and hypoxemia. Gastrointestinal system was the commonly affected followed by the hepatic, renal, and cardiovascular systems. Coronary artery abnormalities were seen in 20% of cases. IVIg was the mainstay of therapy used in 95% of patients. Mortality was 1.3%. Cases responded well to IVIg and steroids. Conclusion(s): Overall, the short-term outcome was favorable with low mortality in our study cohort. One-fifth of children had coronary artery abnormalities during acute phase underscoring the need for long-term follow-up. Copyright © 2022, The Author(s).
ABSTRACT
Background and objective The coronavirus disease 2019 (COVID-19) pandemic has highlighted the shortcomings worldwide in terms of preparedness protocols related to epidemics. A key area of research that is evidently overlooked across the globe is the mental health of family caregivers taking care of patients with COVID-19. In light of this, this study aimed to engage in a comparative analysis between the two worst affected countries, India and the United States of America (USA), which differ considerably in their demography, socio-epidemiological factors, and health system efficiency. Methods A cross-sectional study was conducted among 1,250 family caregivers of patients with COVID-19 in India and the USA to assess their stress, anxiety, and sleep disturbance levels using the 10-item Perceived Stress Scale (PSS-10), the 7-item Generalized Anxiety Disorder (GAD-7) scale, and the Pittsburgh Sleep Quality Index (PSQI), respectively. Psychological assessment questionnaires were administered through online mode, which gathered demographic information and responses on several self-reporting scales. The main outcome measures were self-reported ratings on PSS, GAD-7 scale, and PSQI. Results We found that 75.4% of the family members of COVID-19 patients suffered from mental health issues. The scores of all three scales were higher in caregivers from the USA than in India, more evident and pronounced in caregivers of hospitalized patients. The test scores were statistically significant (p<0.05) indicating a negative impact of having a dependent member in the family, being married, being of younger age, and having a longer duration of COVID-19 infection. Vaccines were found to have a life-enhancing effect. Conclusion Our findings highlight that the mental health of family caregivers is an ignored aspect and must be addressed. We recommend the implementation of well-researched and appropriate legislation, treatment programs, and health policies that involve not only the patients but also their families.
ABSTRACT
COVID-19 pandemic is triggering a massive epidemic in more than 180 countries worldwide, causing chaos in many people's health and lives. Identifying infected patients early enough and placing them under special treatment is one of the most critical steps in combating COVID-19. RT-PCR is a standard test process. The test procedure is typically conducted by air samples collected using a nasopharyngeal swab. However, using a nasal swab or sputum extract is not always possible. Due to the shortage of testing kits, virus mutations, and a longer time to detect. In addition to laboratory tests, chest scans can help diagnose COVID-19 in people who have severe clinical concerns. So, classification through X-ray images could be beneficial. This experiment aims to analyze the X-Ray images as abnormal or not. The intention is to train a convolution neural network(CNN) to classify the image using different architectures such as Xception, Resnet-50, DenseNet-121, VGG-16. Test the Performance metrics for each model and train further based on the insight gained. The following is an experimental study where we repeatedly train better models based on the insights gained from the previous model. The models tested on test data, and most of the results achieved a sensitivity rate of 98 percent (± 2 %), With a specificity rate of around 98 percent. While the achieved results are auspicious, additional research in a broader collection of COVID-19 chest X-ray pictures is needed to estimate accuracy rates accurately. © 2021 IEEE.
ABSTRACT
Technology advancements have a rapid effect on every field of life, be it medical field or any other field. Artificial intelligence has shown the promising results in health care through its decision making by analysing the data. COVID-19 has affected more than 100 countries in a matter of no time. People all over the world are vulnerable to its consequences in future. It is imperative to develop a control system that will detect the coronavirus. One of the solutions to control the current havoc can be the diagnosis of disease with the help of various AI tools. The proposed system contains textual data analysis as well as real time physiological data analysis concept. The embedded platform reads the body temperature and heart rate of the patients. The patient is automatically induced to attend the pre-screening survey designed using the software GUI that collects most of the information on symptoms persists. A COVID-19 dataset is collected from publicly available websites. The read survey values and sensor values are pre-processed and extracted the unique features present in it. Those unique parameters are compared with the database to produce the output showing COVID positive status or Negative status and immediate medicine suggestions for them using the global collective medicine suggestions box. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
Background: India currently has the second largest burden of infections due to COVID-19. Health Care Worker (HCW) shortages are endemic to Indian healthcare. It should therefore be a huge priority to protect this precious resource as a critical component of the systemic response to this pandemic. Advisories from the Indian Council of Medical Research (ICMR) have focused on using hydroxychloroquine prophylaxis against COVID-19 in at risk HCW. This prophylaxis strategy has no evidence. In further jeopardy there appear to insubstantial attempts to build this evidence as well. In this connection, we commissioned a survey within our Institution to estimate the penetration of hydroxychloroquine (HCQ) use and use this to statistically model the impact of current ongoing studies in India. We also briefly review the literature on HCQ prophylaxis for COVID-19. Design and methods: A structured survey designed using RedCAP application was disseminated among healthcare professionals employed at an academic referral tertiary care centre via online social media platforms. The survey was kept open for the entire month of June 2020. The survey was additionally used to statistically model the size of studies required to comprehensively address the efficacy of HCQ in this setting. Results: 522 responses were received, of which 4 were incomplete. The ICMR strategy of 4 or more doses of HCQ was complete only in 15% of HCW in our survey. The majority of respondents were doctors (238, 46%). Amongst all category of responders, only 12% (n=63) received the full course. A majority of those who initiated the chemoprophylaxis with HCQ turned out to be medical professionals (59/63) with neither nurse nor other categories of healthcare workers accessing the medication. The respondents of our institutional survey did not report any life-threatening side effects. Presuming efficacy as per ICMR modelling for new registry trial on the lines of the published case control study, equal allocation between cases and controls and assuming a RR of 1.3.6, the power of such a study would be very low for n=2000 for event rates from 2.5-12.5%. Conclusion: We report the low penetration of HCQ chemoprophylaxis among the healthcare workers of our institution. We highlight the inherent drawbacks in the study design of current national COVID related trial based on the statistical modelling of our survey results and published literature, and thereby emphasis the need of evidence-based strategies contributing to research policy at national level.
ABSTRACT
Close contacts with high-risk exposure to COVID-19 cases are more robust in statistics for inferring future development of COVID-19 epidemic. In Beijing, the proportion of close contact cases in newly confirmed cases had increased from about 50% at the end of January to nearly 100% in mid-February, indicating that contact tracing and quarantine measures are effective non-pharmaceutical interventions for containing the epidemic. In addition, we show at the national level that the cumulative number of close contacts was stabilized at about eight times as much as infected individuals, and the growth rate of daily close contacts was consistent with that of daily confirmed cases 5~6 days later. Consequently, tracking the daily change of close contacts is beneficial to predict the trend of the epidemic, based on which advanced medical supplies scheduling and effective epidemic prevention can be achieved. © 2020, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved.