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1.
New Physics: Sae Mulli ; JOUR(7):525-536, 72.
Article in Korean | Scopus | ID: covidwho-2090457

ABSTRACT

This study was conducted to alleviate the difficulty of teaching online physics experiments. To this end, five methods for teaching online physics experiments based on a literature review are summarized: experiments using simulations, experimental videos, remote experiments, experiments focusing on data analysis, and hands-on experiments at home. In this study, the advantages and disadvantages of these five online experimental methods and the conditions for effectively using online physical experiments are summarized. Therefore, the results of this study should be useful for teaching actual online physical experiments. Although this study was initiated because of complete online education caused by COVID-19, online physics learning should continue to expand in ordinary learning situations. Therefore, the results of this study can be meaningfully used even after the COVID-19 pandemic. © 2022 The Korean Physical Society. All rights reserved.

2.
R Soc Open Sci ; 9(10): 220716, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2087953

ABSTRACT

Online platforms play a relevant role in the creation and diffusion of false or misleading news. Concerningly, the COVID-19 pandemic is shaping a communication network which reflects the emergence of collective attention towards a topic that rapidly gained universal interest. Here, we characterize the dynamics of this network on Twitter, analysing how unreliable content distributes among its users. We find that a minority of accounts is responsible for the majority of the misinformation circulating online, and identify two categories of users: a few active ones, playing the role of 'creators', and a majority playing the role of 'consumers'. The relative proportion of these groups (approx. 14% creators-86% consumers) appears stable over time: consumers are mostly exposed to the opinions of a vocal minority of creators (which are the origin of 82% of fake content in our data), that could be mistakenly understood as representative of the majority of users. The corresponding pressure from a perceived majority is identified as a potential driver of the ongoing COVID-19 infodemic.

3.
Clin Exp Med ; 2022 Oct 26.
Article in English | MEDLINE | ID: covidwho-2085405

ABSTRACT

BACKGROUND: Reinfection by SARS-CoV-2 is a rare but possible event. We evaluated the prevalence of reinfections in the Province of Modena and performed an overview of systematic reviews to summarize the current knowledge. METHODS: We applied big data analysis and retrospectively analysed the results of oro- or naso-pharyngeal swab results tested for molecular research of viral RNA of SARS-CoV-2 between 1 January 2021 and 30 June 2021 at a single center. We selected individuals with samples sequence of positive, negative and then positive results. Between first and second positive result we considered a time interval of 90 days to be sure of a reinfection. We also performed a search for and evaluation of systematic reviews reporting SARS-CoV-2 reinfection rates. Main information was collected and the methodological quality of each review was assessed, according to A Measurement Tool to Assess systematic Reviews (AMSTAR). RESULTS: Initial positive results were revealed in more than 35,000 (20%) subjects; most (28%) were aged 30-49 years old. Reinfection was reported in 1,258 (3.5%); most (33%) were aged 30-49 years old. Reinfection rates according to vaccinated or non-vaccinated subjects were 0.6% vs 1.1% (p < 0.0001). Nine systematic reviews were identified and confirmed that SARS-CoV-2 reinfection rate is a rare event. AMSTAR revealed very low-moderate levels of quality among selected systematic reviews. CONCLUSIONS: There is a real, albeit rare risk of SARS-CoV-2 reinfection. Big data analysis enabled accurate estimates of the reinfection rates. Nevertheless, a standardized approach to identify and report reinfection cases should be developed.

4.
Naunyn Schmiedebergs Arch Pharmacol ; 2022 Oct 25.
Article in English | MEDLINE | ID: covidwho-2085334

ABSTRACT

Motivated by the 150-year anniversary of the Naunyn-Schmiedeberg's Archives of Pharmacology in 2023, we studied the bibliometric development of the journal. We evaluated data from Editorial Reports, Clarivate, and Springer Nature databases. Several parameters representing the journal's performance, such as the impact factor and social impact, were analyzed over the years. We analyzed the journal's meta-data and wrote an algorithm to retrieve cities and countries of origin. We could see a decrease in publications from Germany and an increase in papers from Brazil, China, Egypt, and Iran during the last years. The decrease in publications from Germany is probably a zeitgeist effect because this country places a strong emphasis on high-impact factor papers for academic promotion and winning grants. Germany was the country with the most publications throughout the 100 most-cited articles. Most of these articles were published between 1970 and 1990, when neurotransmitters were the most published topic. Klaus Starke (Freiburg) and Manfred Göthert (Bonn) were prominent drivers of this field. The most common topics nowadays are "Drugs for the Treatment of Malignant Tumor Diseases" and "Immunopharmacology." The internationality of the journal substantially increased after introduction of English as mandatory language in the 1970s. The journal also experienced substantial COVID-19 pandemic-related effects. This paper is not only of relevance for the field of pharmacology but for science in general in the sense that Naunyn-Schmiedeberg's Archives of Pharmacology is a case study for profound changes in a traditional scientific journal, requiring permanent adjustment by editors, referees, publisher, authors, and readers alike. The development of the journal has been strongly influenced by historic and political developments, cultural attitudes (zeitgeist), language changes, global changes in research topics, and eminent individuals who published many papers in Naunyn-Schmiedeberg's Archives of Pharmacology.

5.
Isr J Health Policy Res ; 11(1): 36, 2022 10 20.
Article in English | MEDLINE | ID: covidwho-2079545

ABSTRACT

Mathematical and statistical models have played an important role in the analysis of data from COVID-19. They are important for tracking the progress of the pandemic, for understanding its spread in the population, and perhaps most significantly for forecasting the future course of the pandemic and evaluating potential policy options. This article describes the types of models that were used by research teams in Israel, presents their assumptions and basic elements, and illustrates how they were used, and how they influenced decisions. The article grew out of a "modelists' dialog" organized by the Israel National Institute for Health Policy Research with participation from some of the leaders in the local modeling effort.


Subject(s)
COVID-19 , Humans , Pandemics/prevention & control , SARS-CoV-2 , Israel/epidemiology , Models, Statistical
6.
Lecture Notes on Data Engineering and Communications Technologies ; 150:75-84, 2023.
Article in English | Scopus | ID: covidwho-2075289

ABSTRACT

Based on the surging situation of COVID-19 and its rapid propagation speed and wide range, schools as a crowded place are prone to outbreak of large areas. Therefore, in order to ensure the normal progress of campus teaching order, campus should be the focus of epidemic prevention and control. By using AnyLogic simulation software, using system dynamics model and combined with the actual data operation of College D Teaching Building, this paper simulates the D Teaching Building, and intuitively shows the simulation and control effect through the Time Plot. The simulation results show that the school can reduce the number of infected people by taking effective measures to control the contact rate of students and vaccinating them in time;Finally, effective treatment can greatly increase the rehabilitation rate of infected people and reduce the number of deaths. This method has certain guiding significance in today’s severe epidemic prevention and control. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

7.
Ieee Access ; 10:103806-103818, 2022.
Article in English | Web of Science | ID: covidwho-2070268

ABSTRACT

Throughout the various containment phases of a pandemic, such as Covid-19, digital tools and services have proven to be essential measures to counteract the ensuing disrupting effects in social and working interactions. In such scenarios, Nausica@DApp, the comprehensive solution proposed in this paper, eases compatibility of the in-presence activities of a campus-based corporation with the organizational constraints posed by the virus during the pandemic, or at a later endemic stage. This is accomplished throughout several intervention areas, such as personnel contact tracing, crowd gathering surveillance, and epidemiological monitoring. These operational requirements, in particular indirect contact tracing and overcrowd monitoring, call for the adoption of an absolute device localization paradigm, which, in the proposed solution, has been devised on top of the campus WiFi infrastructure, proving to be encouragingly accurate in most cases. Absolute localization, on the other hand, entails a certain amount of server-based centralized operations, which might affect the preservation of user data privacy. The novelty of the proposed solution consists in maximizing confidentiality and integrity in the handling of sensitive personal information, in spite of the centralized aspects of the localization system. This is accomplished by decentralizing contact tracing matching operations, which are entirely carried out locally, by apps running on the users' mobile devices. Contact data are pseudonymized and their authenticity is guaranteed by a blockchain. Furthermore, the proposed novel solution improves privacy preservation by eschewing recourse to the Bluetooth app-to-app channel for user data exchange, in fact a typical choice of most current contract tracing solutions. Thanks to a sensible use of the blockchain features, integrated into Nausica@DApp's microservice-based back-end, a higher degree of operation transparency can be relied upon, thus boosting the user's level of trust and enhancing the availability and reliability of data about people gathering within the campus premises. Moreover, contact tracing only requires the mobile device WiFi interface to be on, so that users are neither forced to adopt new habits, nor to grant additional device access permissions to contact tracing apps (potentially undermining their own privacy). The overall system has been analysed in terms of performance and costs, and the experiments have shown that its adoption is viable and effective.

8.
Int J Environ Res Public Health ; 19(20)2022 Oct 14.
Article in English | MEDLINE | ID: covidwho-2071450

ABSTRACT

The COVID-19 pandemic has created unprecedented burdens on people's health and subjective well-being. While countries around the world have established models to track and predict the affective states of COVID-19, identifying the topics of public discussion and sentiment evolution of the vaccine, particularly the differences in topics of concern between vaccine-support and vaccine-hesitant groups, remains scarce. Using social media data from the two years following the outbreak of COVID-19 (23 January 2020 to 23 January 2022), coupled with state-of-the-art natural language processing (NLP) techniques, we developed a public opinion analysis framework (BertFDA). First, using dynamic topic clustering on Weibo through the latent Dirichlet allocation (LDA) model, a total of 118 topics were generated in 24 months using 2,211,806 microblog posts. Second, by building an improved Bert pre-training model for sentiment classification, we provide evidence that public negative sentiment continued to decline in the early stages of COVID-19 vaccination. Third, by modeling and analyzing the microblog posts from the vaccine-support group and the vaccine-hesitant group, we discover that the vaccine-support group was more concerned about vaccine effectiveness and the reporting of news, reflecting greater group cohesion, whereas the vaccine-hesitant group was particularly concerned about the spread of coronavirus variants and vaccine side effects. Finally, we deployed different machine learning models to predict public opinion. Moreover, functional data analysis (FDA) is developed to build the functional sentiment curve, which can effectively capture the dynamic changes with the explicit function. This study can aid governments in developing effective interventions and education campaigns to boost vaccination rates.


Subject(s)
COVID-19 , Social Media , Humans , COVID-19 Vaccines , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , Public Opinion , China/epidemiology
9.
Journal of Acute Disease ; 11(4):120-126, 2022.
Article in English | EMBASE | ID: covidwho-2066823

ABSTRACT

Unbalanced magnesium levels in the body, like other minerals, are a factor that is important in the severity and mortality of COVID-19. This study was designed to investigate the relationship between serum magnesium levels and clinical outcomes in COVID-19 patients. In this systematic review, a comprehensive search was performed in PubMed, Scopus, and Web of Science databases until September 2021 by using the keywords COVID-19, severe acute respiratory syndrome coronavirus 2, coronavirus disease, SARS- COV-infection 2, SARS-COV-2, COVID 19, and magnesium. End-Note X7 software was used to manage the studies. Articles that evaluated effect of magnesium on COVID-19 were included in the analysis. After reviewing several articles,12 studies were finally included in the ultimate analysis. The studies show that hypomagnesemia and hypermagnesemia are both factors that increase mortality in patients with COVID-19, even in one study, hypomagnesemia is the cause of doubling thedeaths in COVID-19 patients. Some studies have also found a negative correlation between magnesium deficiency and infectionseverity, while some others have reported no correlation between magnesium level and disease severity. According to the important role of magnesium in the body and its involvement in many physiological reactions, as well as differences in physical and physiological conditions of COVID-19 patients, in addition to the need for studies with larger sample sizes, monitoring and maintaining normal serum magnesium levels during the disease seems necessary as a therapeutic target, especially in patients admitted to the intensive care unit.

10.
Open Access Macedonian Journal of Medical Sciences ; 10(E):1169-1173, 2022.
Article in English | EMBASE | ID: covidwho-2066702

ABSTRACT

BACKGROUND: The implementation of the vaccine on a large scale has almost reached all provinces in Indonesia. East Kalimantan, one of the provinces affected by COVID-19, has also implemented a vaccine program. Seroprevalence surveys are essential to describe the success of vaccine program based on antibody titer test. AIM: This study aims to determine the anti-SARS-CoV-2 antibody titer value based on the type of vaccine received by the academic community in Samarinda, one of the cities most affected by COVID-19 in East Kalimantan. METHODOLOGY: The study was population-based. The study sampled 100 people from the community. Participants must be in good health, aged 16–60, with a positive COVID-19 test, no comorbid illnesses or other chronic problems, no blood transfusions, and most importantly, have received the least initial dosage of immunization. The data will be analyzed using SPSS 26 and STATA 16. A normality test and Tobit regression test to determine the antibody distribution in each vaccine type. RESULTS: The results showed that Moderna COVID-19 Vaccine provided a significant (p = 0.001) increase in antibody prediction of 1090 U/ml (95% CI: 764–1416), while Pfizer provided a significant (p = 0.000) rise of 766 U/ ml (95% CI: 307–1226). CONCLUSION: According to the results of a seroprevalence survey conducted among the academic community in East Kalimantan, receivers of inactivated vaccinations outnumbered those of mRNA and vector-based vaccines. It can be determined that booster immunizations for students and academic staff are required to guard against COVID-19 infection. As boosters, both Moderna’s COVID-19 Vaccine and Pfizer’s COVID-19 Vaccine are strongly recommended.

11.
Open Access Macedonian Journal of Medical Sciences ; 10(E):1463-1471, 2022.
Article in English | EMBASE | ID: covidwho-2066697

ABSTRACT

BACKGROUND: Clinical laboratory (CL) services are at the forefront to support health-care services, particularly during the pandemic of COVID-19. The increasing number of private clinical laboratories at present days indicates the increase in patient needs, causing the health-care service provider to face challenges as people have more options. Therefore, fostering patient loyalty (PL) is a crucial success factor for the business growth of clinical laboratories as health-care providers. AIM: The purpose of this study is to analyze antecedents of patient satisfaction (PS) in clinical laboratories towards PL with the switching cost and location as moderating factors. METHODS: This study was done as a quantitative survey, and data were obtained by a cross-sectional approach with partial least squares structural equation modeling for the data analysis method. There are 266 respondents eligible as samples, who undergo the phlebotomy process (PP) in a private laboratory located within a specific area. RESULTS: This study demonstrated that all the nine hypotheses supported with α: 0.05 and p < 0.05, include six independent variables named administrative process, information availability (IA), the environment in the phlebotomy room, PP, waiting time, and result notification that influence PS. PS has been shown to have a direct effect on PL and also mediate the antecedents. Furthermore, SC and LO have demonstrated a significant effect to moderate this relationship. CONCLUSIONS: PS has been confirmed as the main construct to predict PL whereas the AP is the most important independent variable followed by IA. CL management should pay more attention to these antecedents to ensure PS and retain the clinic’s patients. The cost from the patient’s perspective should be taken into account since this helps the CL keep the patient loyal.

12.
Open Access Macedonian Journal of Medical Sciences ; 10:644-648, 2022.
Article in English | EMBASE | ID: covidwho-2066695

ABSTRACT

BACKGROUND: In the COVID-19 pandemic situation, there are almost all routine services including maternal and newborn health services. For example, pregnant women are reluctant to go to the community health center or other facilities for fear of being infected and services delay pregnancy checks and classes for pregnant women. This causes maternal and newborn health services to be one of the services affected, both in terms of access and quality. Therefore, in improving maternal health, literacy about COVID-19 and Antenatal Care (ANC) services are needed during the adaptation period of the COVID-19 period. The general purpose of the study was to determine the effectiveness of providing literacy about COVID-19 on the compliance of pregnant women in conducting ANC in Pematangsiantar City. AIM: The specific objectives of the study were to determine the level of health literacy about COVID-19 in pregnant women, to know the coverage of ANC during the COVID-19 pandemic, and to analyze the effectiveness of providing literacy about COVID-19 on the compliance of pregnant women with ANC in Pematangsiantar City. METHODS: This research used a quasi-experimental design by providing literacy about COVID-19 and ANC to pregnant women. Literacy ability was assessed using a 16-item S-HLS-EU-Q questionnaire with a Likert scale. The number of samples in this study was 33 for the intervention group and 33 for the control group. Consecutive sampling and data analysis using the Chi-square test using the Statistical Package and Service Solutions version 25.0 application. RESULTS: The results of the study were 33 respondents in the intervention group, all of whom had high literacy about the health-care domain. While in the control group, only 75.8% had high literacy. The results of Fisher’s test showed p = 0.005. In the intervention group, 97% of the disease prevention domain had high literacy, and in the control group, there were 84.8% who had high literacy. The results of Fisher’s test showed p = 0.197. In the intervention group, the domain of health promotion overall had high literacy, and in the control group, there were 84.8% who had high literacy. Fisher’s test results show p = 0.053. CONCLUSION: The results, based on research, need to be made efforts to overcome the compliance of pregnant women in implementing an ANC.

13.
Sustainability ; 14(19):12811, 2022.
Article in English | ProQuest Central | ID: covidwho-2066465

ABSTRACT

Although the needs for sustainable urban infrastructure systems are increasingly being recognized and addressed, the same is not true for Native American communities, where existence, condition, and access to a collection of infrastructure systems is often lagging behind urban and non-native communities. To date, there has been a quite limited number of studies exploring Native American perspectives on infrastructure challenges and how to build sustainable and resilient infrastructure systems in their communities. Thus, the purpose of this study is to identify the challenges and opportunities for building sustainable infrastructure systems for Native American communities in Southern California and investigate how those communities experience, understand, and apply engineering practice in the context of their community and culture. Drawing from six group interviews, our study highlights challenges and opportunities for building sustainable and resilient infrastructure systems on tribal reservations in San Diego County, California, from the perspectives offered by Native Americans themselves. We focus on infrastructure systems fundamental to well-being: built environment, water/wastewater, telecommunications, transportation, energy, human capital, and education. Our research participants emphasized the importance of their cultures, sovereignty, and care for the welfare of their communities in innovating sustainable and resilient infrastructure. To accomplish this, a key priority should be to train native engineers, who are best positioned to understand the infrastructure needs and opportunities in their own communities.

14.
Sustainability ; 14(19):12356, 2022.
Article in English | ProQuest Central | ID: covidwho-2066403

ABSTRACT

This article investigates the connection between US logistics companies’ commitment to environmental, social and fair governance (ESG) strategy and their performance on the US stock market during the 2007–2022 period. The research considers historical data analysis, CAPM and a comparison of optimised portfolios. According to the results of the analyses, ‘green’ logistics stocks are less volatile, and hence less risky, and more profitable compared to ‘non-green’ logistics stocks. The Great Recession (2007–2009) and the COVID-19 pandemic (2020) had the greatest impact on stock volatility, in terms of the US stock market. Optimised during the time of the Ukrainian crisis, green logistics portfolios were shown to have higher returns, but also risks and Sharpe ratios, than ‘non-green’ ones. The results confirm there to be a connection between companies’ commitment to ESG strategy and enhanced stock performance, which contributes to the importance of the ESG agenda.

15.
Pakistan Journal of Medical and Health Sciences ; 16(8):88-91, 2022.
Article in English | EMBASE | ID: covidwho-2067739

ABSTRACT

Background: The COVID-19 first surfaced when cluster of pneumonia patients arose in Wuhan, Hubei Province, China. Although the current gold standard for COVID-19 diagnosis is reverse transcriptase-polymerase chain reaction (RT-PCR), chest x-ray (CXR) and computed tomography (CT) play a vital role in sickness diagnosis due to their limited sensitivity and availability. Aim: To evaluate retrospectively the role of CXR, the main radiological findings in it and its diagnostic accuracy in COVID-19 pneumonia. Methods: This is a cross sectional study involving 264 PCR positive COVID-19 patients with their clinical-epidemiological findings admitted at Ziauddin Hospital from May-July 2020. CXRs were taken as digital radiographs in our emergency department's isolation wards using the same portable X-ray device, according to local norms. CXRs were taken in two directions: antero-posterior (AP) and postero-anterior (PA). The hospitals' database had all of the images. To determine the number of radiological findings, multiple radiologists on duty completed an independent and retrospective examination of each CXR. In the event of disagreement, a mutual agreement was reached. SPSS version 20 was used for statistical analysis. Results: We were able to find 264 patients who met our criteria. With a mean age of 56.4214.89, the majority of individuals were determined to be males 189(71.6%) and females 75(28.4%). (Range of 16 to 87 years). 127 patients (48.1%) had severe illness symptoms and were admitted to the ICU, while the remaining 102(38.6%) had mild to moderate disease 35(13.3%). Diffuse (29.2%) and middle and lower co-existing distribution (25.8%) whereas just lower lobe (13.3%) were the most common predominance in severity. Peripheral involvement was also seen in (8.7%) cases. Conclusion: Both lungs are equally affected with the disease having the consolidation and opacifications while the effusion is the major complication in the severe cases. Diffuse involvement of the lung lobes is seen in the study followed by the middle and lower lobe involvement.

16.
Pakistan Journal of Medical and Health Sciences ; 16(8):24-26, 2022.
Article in English | EMBASE | ID: covidwho-2067738

ABSTRACT

Aim: To evaluate the potential use of ivermectin with standard therapy among mild to moderate covid-19 illness. Methods: This is a single-centered, prospective observational, randomized, parallel group (1:1 ratio), standard versus controlled ivermectin study recruited 210 confirmed COVID-19 positive patients who were admitted in COVID treatment center of Dr Ruth Kum Pafu Civil hospital Karachi, Pakistan from 1st November 2020 to 30th May 2021. Data were analyzed using SPSS version Results: Total of 210 patients were enrolled in the study and aged matched patients were divided in two groups 105 patients received ivermectin 6 mg twice a day for five days along with standard therapy while remaining 105 patients received standard therapy as per local and international guidelines. Male were 140(66.7%) and female 70(33.3%);age ranges between 26 to 77 years and majority 140( 66.7%) were more than 50 years of age. Fever, dry cough and dyspnea were the major symptoms seen;112(53.3%) patients had DM as a comorbid illness . Total of 21(20%) of 105 patients of ivermectin group had negative PCR for COVID 19 on day seven while the other group had positive covid test in all of 105 patients . On day 10 total of 49 more patients from ivermectin group found COVID negative along with 21 previously negative had second PCR was found negative in this way total of 70( 66.7%) of ivermectin group had negative PCR for COVID 19 while 21(20%) patients from non ivermectin got negative PCR for COVID 19 on day 10 . Conclusion: Use of ivermectin with standard therapy clear the virus earlier than standard therapy in mild to moderate COVID-19 infected patients admitted in COVID treatment center of Dr Ruth Kum Pafu Civil Hospital Karachi.

17.
Research Journal of Pharmacy and Technology ; 15(8):3717-3724, 2022.
Article in English | EMBASE | ID: covidwho-2067732

ABSTRACT

Background: Health care workers (HCWs), being in the front line dealing with COVID-19 patients, are facing various challenges. Therefore, being aware about COVID-19 is of high importance. The overall aim of this study is to evaluate the HCWs' knowledge and attitude about COVID-19. The objectives of the study are assessment of HCWs' knowledge and attitude about COVID-19 and determining the significant factors that influence their knowledge. Methods and Materials: a descriptive cross-sectional study was carried out among convenient sample (n=353) of HCWs in the UAE by using an online self-administrated questionnaire. The data was analyzed using the SPSS version 26. Mann Whitney u test and Kruskal Wallis test were used to test the differences in quantitative variables across groups. Multivariate logistic regression analysis was used to investigate the association between the knowledge about COVID-19 and significant factors. A p value <0.05 was chosen as the criteria to make decisions regarding statistical significance. Result(s): A total of (353) HCWs participated in the study and completed the whole questionnaire. The average knowledge score was 76.3% with a 95% confidence interval (CI) [75.2%, 77.5%]. Of the total participants, 122 (34.6%) have poor knowledge, 81 (22.9%) have acceptable knowledge and 150(42.5%) have good knowledge. In the present study, significantly higher knowledge scores were observed in Western participants (OR 2.83;95% CI 1.51 - 5.29), General practitioners (OR 1.319;95% CI 1.03 - 1.69), participants working in Dubai (OR 1.47;95 % CI 1.28- 1.69) and participants who had been in contact with suspected or confirmed COVID-19 cases (OR 1.235;95% CI 1.11- 1.37). On the other hand, significantly lower knowledge scores were observed in participants aged 30-39 years (OR 0.760;95% CI 0.647- 0.893), Arabian participants (OR 0.76;95 % CI 0.58- 0.98) and participants with less than 1year experience (OR 0.729;95% CI 0.601- 0.883). Conclusion(s): This study revealed that HCWs working in the UAE have a good level of general knowledge about COVID-19 symptoms, transmission, progression, and prevention. Questions about deeper knowledge revealed a lower level of knowledge. Therefore, tailored awareness campaigns may be required in order to meet HCWs' needs and enhance their levels of deep knowledge. Copyright © RJPT All right reserved.

18.
Indian Journal of Forensic Medicine and Toxicology ; 16(3):63-68, 2022.
Article in English | EMBASE | ID: covidwho-2067687

ABSTRACT

Background: COVID-19 is a pandemic disease caused by droplet infection from SARS-CoV-2. Due to its rapid transmission and high case fatality rate, the identification of risk factors and prognostic factors is important. Obesity is a risk factor for poor outcomes in COVID-19. It is associated with chronic inflammation, disorders of the immune system. Obesity can be determined based on BMI. Chest X-Ray is supported in establishing the diagnosis and prognosis of COVID-19 patients. Assessment of the severity index of Chest X-Ray radiographs can use the Modified Chest X-Ray Scoring System of RSUP Dr. Soetomo. This study was conducted to analyze the relationship between BMI and chest radiography severity index in hospitalized COVID-19 patients at dr. Mohammad Hoesin Palembang in 2021. Methods: This research used a cross-sectional analytic observational design. Sampling was done using a consecutive sampling technique with 70 samples and obtained from the patient's medical record. The data were analyzed by univariate and bivariate (Chi-Square) using IBM SPSS Statistics 26 software. Results: Patients with BMI Overweight-Obesity had more in Moderate-Severe (18.6%) radiographic severity index scores (18.6%) than Normal-Mild (15.7%). Chi-Square bivariate analysis, BMI (p=0.033;p-value <0.05) had a significant relationship with the chest radiographic severity index with Odds Ratio 3,00, 95% CI (1,073–8,386). Conclusion: There is a significant relationship between body mass index and chest radiography severity index in COVID-19 patients. Overweight-Obesity BMI patients have a 3-fold chance of having a Moderate-Severe category of radiographic severity index compared to Underweight-Normal BMI patients.

19.
Aging Medicine and Healthcare ; 13(3):132-138, 2022.
Article in English | EMBASE | ID: covidwho-2067646

ABSTRACT

Background/Purpose: Due to the pandemic of COVID-19 and the need to pay attention to the older adults as one of the most vulnerable groups, this study aimed to determine the effects of educational programs based on the Protection Motivation Theory (PMT) as non-pharmaceutical intervention in promoting protective behaviors against COVID-19 among the older adults in Hamadan. Method(s): The present study was a randomized controlled trial performed in 2021 on 80 older adults visiting retirement centers in Hamadan. Participants were randomly assigned to experimental (n=40) and control groups (n=40). The data collection tool was a researcher-made questionnaire including demographic variables and constructs of PMT which were completed before and two months after the intervention. The intervention consisted of four sessions implemented for the experimental group. The collected data was analyzed in SPSS-16 using Chi-square, Mann-Whitney, and Wilcoxon tests. Result(s): There was no significant difference between the two groups in terms of all demographic variables and theoretical constructs before the educational intervention. After the educational intervention, there was a significant difference in the constructs of perceived severity (P=0.012), perceived response efficiency (P=0.009), perceived self-efficacy (P=0.021), and perceived response cost (P <0.001) after the intervention. No significant changes were reported in the control group (P >0.05). Also, results showed that there was no significant difference in the mean of COVID-19 preventive behaviors between the two groups after the educational intervention (P >0.05). Conclusion(s): The results showed that the use of educational intervention as non-pharmaceutical intervention based on the PMT was an effective approach to perform preventive behaviors against infectious diseases such as COVID-19. Copyright © 2022, Full Universe Integrated Marketing Limited. All rights reserved.

20.
NeuroQuantology ; 20(12):91-103, 2022.
Article in English | EMBASE | ID: covidwho-2067346

ABSTRACT

Machine learning has been successfully used in the medical field for the last few years. The emergence of covid-19 pandemic has seen researchers using machine learning approaches to detect and predict whether a patient has been infected by covid-19 or not. Cough and fevers are the two most likely symptoms of the covid-19. In this paper, the journals regarding the prediction of covid-19 severity based on symptoms have been discussed. Several researchers have established deep learning-based models for the prediction. They have used the test data from the hospitals for their research process. The KNN models, ANN models, and SVM models have been discussed. The limitations of the past research process have been evaluated to be the biased test data set and missing values. The methodology that was used for the research process has been described. Mixed method of data collection was used for the research processes. The secondary data was collected from reliable sources for this research process. Kaggle website was used to collect the test data regarding the covid-19 patients. The data analysis was done on the weka tool using various machine learning models. Copyright © 2022, Anka Publishers. All rights reserved.

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