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At the beginning of 2020, the COVID-19 contagious virus swept, which caused a lot of disturbances in all countries worldwide. The Egyptian government declared an emergency and placed the country under lockdown. Preventive measures such as social distancing, sterilization, mask wear, frequent temperature checks, offering COVID-19-related training, and encouraging work-from-home initiatives, among other precautions, have been implemented. Such precautionary measures affected the construction production rate. This research used a questionnaire and face-to-face interviews to solicit the opinion of construction industry professionals and experts on tier-one construction companies on the impact of this pandemic on construction production rate. A quantitative analysis has been done in this study using IBM SPSS Statistics 26© to determine the most important effective factors of the production rate of the construction industry, mainly in Egypt. Also, this study illustrates an Artificial Neural Networks (ANNs) model to predict the project's cost and production rate at construction for the actual status in Egypt at the peak of COVID-19. The model does not only present the actual case but can also predict the most important and influential factors of the construction industry mainly in Egypt, at the peak of the virus, and can be used in other similar crises as a lesson learned which no study covered this area at the previous works. Finally, the results and the validation study of the proposed ANN model in the research show and present the actual status of production rate in the construction sector, mainly in Egypt (case study), and also predict the production rates of the construction sector at the future crisis. © 2023 by the authors.
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In order to study the overall situation of college English online teaching and students' online learning satisfaction during the COVID-19 epidemic, this paper made a questionnaire from four aspects: learning environment, teachers' teaching activities, students' learning activities, and online learning effect. Through SPSS23.0 software, the questionnaire data were analyzed by reliability analysis, validity analysis, principal component analysis, regression analysis and other methods, and the impacts of learning environment, teaching activities, learning activities, learning evaluation on students' learning satisfaction were studied. © 2022 IEEE.
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Background: This study aims to assess factors associated with food security and dietary diversity among poor urban households of western Oromia, Ethiopia, after the outbreak of the Covid-19 pandemic. Method: A cross-sectional, community-based study was conducted in May to June 2021 with 361 poor urban households in the Horo Guduru Wollega zone, western Oromia, Ethiopia. A pre-tested structured questionnaire was used to collect primary data. Twenty-four hour reminder points were used to assess household dietary diversity, and household food security was assessed using the Household Food Insecurity Access Scale tool. Data were evaluated using the statistical software SPSS version 25.0. Results: This study showed a prevalence of food insecurity in households of 59.6%. The mean and standard deviation of household dietary diversity values were 4.19 ± 1.844. Family size (AOR = 8.5; 95% CI:3.295-21.92), monthly income (AOR = 3.52; 95% CI; 1.771-6.986), dietary diversity (AOR = 8.5; 95% CI; 3.92-18.59), knowledge (AOR = 3.0, 95% CI = 1.08-)8.347), attitude (AOR = 8.35, 95% CI:3.112-22.39) and practices against Covid-19 (AOR = 2.12; 95% CI:1.299-11.4) were factors significantly associated with food insecurity. Variables like educational status (AOR = 3.46; 95% CI:1.44-8.312), increased family size after the Covid-19 pandemic (AOR = 2.26; 95% CI:1.02-5.04), food security (AOR = 6.7; 95% CI:4.01-19.01), knowledge (AOR = 3.96; 95% CI:1.57-10.0), attitude (AOR = 3.9; 95% CI:1.75-8.82) and practices toward coronavirus (AOR = 2.23; 95% CI:2.18-23.95) were predictors significantly associated with dietary diversity. Conclusion: This study concluded that family size, monthly income, and dietary diversity were factors contributed to household food security. On the other hand, variables such as educational status, family size, and food security were highly relevant factors for dietary diversity after the outbreak of the Covid-19 pandemic. Knowledge, attitudes, and practices were also variables related to both household food security and dietary diversity. Therefore, immediate interventions such as nutrition-specific interventions can be suggested to address food insecurity and problems of inadequate food intake in poor urban households. In addition, governmental and non-governmental organizations should raise awareness and policies to support those at higher risk by developing affordable, sustainable and targeted social protection systems that ensure food security and adequate dietary intake at the household level.
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The aim of this analysis is to measure and analyse the shape changes in Lung CT scans using orthogonal Zernike moments in comparison with traditional shape measures. Materials and Methods: A total sample size of 176 scans are acquired for this analysis, by assigning parameters such as the effect size = 0.3, standard error rate = 0.05 and algorithm power = 0.80 are predefined in Gpower software. In this analysis, the comparison between traditional shape measures and Hough Transform algorithms in classifying normal and COVID-19 is performed. Results: It is observed that there is no shape change in the lungs of the normal subjects and in COVID subjects the shape of the lungs reduces due to tissue loss. The feature values obtained from Hough Transform are found to be statistically important (p<0.05). The statistical values (Mean ± standard deviation) of normal and COVID subjects are 0.18 ± 0.13 and 0.10 ± 0.13. The significant features for the Zernike moment were M13,9, M10,8. The extracted values from the Computed Tomography images are consistent in displaying a considerable difference between healthy subject and COVID CT- scan images. The proposed Hough Transform based Zernike Moments algorithm has significantly better accuracy (97%) than the Traditional shape measures with accuracy (78%). Conclusion: The Hough transform based Zernike moments algorithm gives a significantly better result oriented to extraction of shape changes and manifestation of a significant difference in the healthy subject and COVID subject CT scan images than Traditional shape measures algorithm. © 2022 IEEE.
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Albanian SMEs faced unforeseen difficulties during the period of the COVID-19 pandemic. This type of situation, unprecedented before, caused many problems in areas such as the management of activities, liquidity, human capital, sales, marketing, etc. This paper highlights the fact that during this pandemic period, Albanian SMEs felt the need to understand the most important risks that their activities face under these circumstances. The empirical study of this paper was based on the data collected to a structured questionnaire, to identify the perception of the type of risks Albanian SMEs face. Qualitative data collected by SMEs in the southern region of Albania were used for the successful realization of this study. These data were processed with the help of the statistical software SPSS v.21, using logistic regression. As a result, it was concluded that Albanian SMEs have preferences in the perception of some special types of risk that their activities face. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.
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Objectives: To evaluate the impact of COVID-19 pandemic on orthodontic treatment and mental health of patients undergoing orthodontic treatment and to compare their mental health with the age-matched control group. Materials and methods: 484 orthodontic patients (245 males and 239 females) and 200 age-matched control subjects were divided into two age groups. Group 1 had 14-18 years of adolescents (N = 274) and 100 control participants (Group 2) and Group 3 comprised of 19 years above adults (N = 210) and 100 control participants (Group 4). Group 1 and 3 patients filled the 4 sections of the questionnaire related to orthodontic emergencies (Sections 1-3) and mental distress (Kessler Psychological Distress Scale-Section 4), while groups 2 and 4 were asked to fill only Section-4. The comparison of mental distress on high/low Kessler scores was made using the Chi-Square test/Fisher's exact test. The factors which came out to be significant were put to bivariate logistic regression analysis. Results: The percentage of patients with high Kessler scores among Group 1 and Group 3 were 9.9% and 17.2% respectively, and their differences with age-matched control groups were non-significant. The mean differences of Kessler score were significantly higher for Group 3 compared to group 1. The higher Kessler score was associated with age, higher education, a feeling of concern for non-availability of appointments, increased treatment duration, its effect on the quality of treatment, and sabotaging of definitive future plans. Conclusions: The orthodontic treatment and emergencies may not be a significant factor contributing to increased stress among patients during the lockdown.
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Construction delay in projects is a common manifestation in the construction industry. Delay in construction will lead to a bad relationship between the parties involved and will also lead to an increase in the allocated completion time. Delay in the ongoing project might result in the loss of the money, time and other facilities by the client and cause a lot of financial damage to the contractor due to its investment in the purchase of equipment, construction materials and the hire of skilled workers. Delay in construction is a common problem that occurs mostly due to the unforeseen problems during the design & construction stages which often lead to delays in the completion of the project. Oman’s construction industry is one of the most important industries for the country’s economic development and growth. In this study, analysis of some available literature was conducted, and a questionnaire survey was floated among contractors, consultants, clients, project managers, and engineers involved in construction projects. All the collected responses were evaluated by using SPSS. The results of the study identified a total of 60 causes of delay out of which three factors have a “High” significance level for construction delays. These factors of “High” significance were associated with “Client related issues only” in which the initial design was altered by the client, delaying in deciding by the client and, scope change by the client. Majority of the delay (84 %) was observed to be lying in the range of 1‑2 years. This study also recognized the effect and minimization of regular delay and delay resulted due to Covid-19. Minimizing construction delay criteria can be managed by having a proper control system in the project time and funds
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Introduction: The perceived COVID-19 risk may lead to the use of various complementary and alternative medicine (CAM) modalities to reduce the potential risks of this disease. This study was conducted to investigate the relationship between individuals' use of complementary and alternative medicine during the pandemic in Turkey and their attitudes towards perceived COVID-19 risk. Methods: The study was conducted in Turkey between November 2021 and March 2022 and 1003 individuals voluntarily participated. The Personal Information Form, Attitude Towards Holistic Complementary and Alternative Medicine Scale (HCAMS), and Perceived COVID-19 Risk Scale (PCRS) were used for data collection. To evaluate the data descriptive statistics, Pearson's correlation, and Cronbach's alpha reliability analysis were used. Results: In the study, 54.2% of the individuals were found to use CAM during the pandemic, and 56.2% believed that CAM practices were useful in preventing or recovering from COVID-19. It was revealed that 53.8% of the individuals drank herbal tea, 55.2% used religious and spiritual healing to manage, 6.6% used massage, and 10.1% applied aromatherapy. The mean total score of the HCAMS was 28.29 ± 4.99, and the mean total score of the perceived COVID-19 risk scale was 27.78 ± 6.35. A statistically significant positive correlation was identified between the CAM subscale and the emotional risk subscale (p < 0.05). Conclusion: Individuals had a positive attitude towards using CAM during the pandemic period, the risk perception of COVID-19 was high and CAM methods were widely used.The literature should be supported by increasing the current and scientific studies in which CAM methods are questioned and their benefits are investigated during epidemic periods.
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Electronic health records (EHRs) have proven their effectiveness during the coronavirus disease (COVID-19) pandemic. However, successful implementation of EHRs requires assessing nurses' attitudes as they are considered the first line in providing direct care for patients. This study assessed Jordanian nurses' attitudes and examined factors that affect nurses' attitudes toward using EHRs. A cross-sectional, correlational design was used. A convenient sample of 130 nurses was recruited from three major public hospitals in Jordan. All Participants completed the Nurses' attitudes Towards Computerization (NATC) Questionnaire. The overall nurses' attitude was positive; the mean was 61.85 (SD = 10.97). Findings revealed no significant relationship between nurses' attitudes toward using EHRs and nurses' age, gender, education level, previous computer skills experience, years of work experience, and years of dealing with EHRs. However, the work unit was found to have a significant correlation with nurses' attitudes toward using EHRs. Therefore, nurse administrators should arrange for the conduct of educational workshops and continuous training programs considering the needs of the nurses.
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The horrifying and fast spreading COVID-19 pandemic has shocked India and in fact the entire world to its core. Indian Government has taken all the possible preventive steps to contain the wider spread of this highly contagious disease but the second wave in the month of April, 2021 has turned this strong country in a helpless position. In this paper, the effect of environmental factors like temperature and air quality index on the new confirmed cases along with recovered cases has been seen in Bengaluru Urban district of Karnataka State of India. Regression analysis has been carried out with the help of SPSS software. The outcomes from the paper will definitely give some valuable insights for the researchers around the world in their future combat measures.
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At the beginning of the SARS-CoV-2 pandemic, developing of new treatments to control the spread of infection and decrease morbidity and mortality are necessary. This prospective, open-label, case-control intervention study evaluates the impact of the oral intake of the probiotic yeast Kluyveromyces marxianus B0399 together with Lactobacillus rhamnosus CECT 30579, administered for 30 days, on the evolution of COVID-19 patients. Analysis of the digestive symptoms at the end of the follow up shows a benefit of the probiotic in the number of patients without pyrosis (100% vs 33.3%; p 0.05) and without abdominal pain (100% vs 62.5%; p 0.04). Results also show a better evolution when evaluating the difference in the overall number of patients without non-digestive symptoms at the end of the follow-up (41.7%, vs 13%; p 0.06). The percentage of improvement in the digestive symptoms (65% vs 88%; p value 0.06) and the global symptoms (digestive and non-digestive) (88.6% vs 70.8%; p value 0.03) is higher in the probiotic group. The probiotic was well tolerated with no relevant side effects and high adherence among patients. In conclusion, this coadjutant treatment seems to be promising, although results should be confirmed in new studies with higher number of patients.
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Introduction: Increasing manpower capacity to meet the demands in the healthcare system is important during health emergencies. Medical students have roles to play during a pandemic but their involvement in these duties should be voluntary. The objective of this study was to assess the willingness and motivations of final year medical students in Lagos, Nigeria towards volunteering during the COVID-19 pandemic. Methods: A descriptive cross-sectional study was conducted among medical students in their sixth (final) year of study at the two public Universities in Lagos, Nigeria using total population sampling technique. A web-based questionnaire was used for data collection and data were analysed using SPSS. Logistic regression analysis was used to predict the willingness to volunteer. Results: The mean age of the respondents was 23.4â¯years⯱â¯2.6SD and 62.6% were female. About 65.9% of the medical students were willing to volunteer. Motivational factors which include self-rated good health status [OR: 2.1(95%CI: 1.16-3.6)], self-rated competence to work as a COVID-19 volunteer [OR: 6.5(95%CI: 3.61-11.54)] and availability of adequate protection and personal protective equipment [OR: 3.3(95%CI: 1.74-6.33)] significantly increased the odds of willingness to volunteer after controlling for other variables. Respondents' opinions on settings where medical students can serve as volunteers during the COVID-19 pandemic include case management (21.7%) and telemedicine (85.8%). Conclusion: Medical students are willing to volunteer during the COVID-19 pandemic. There is a need to prepare and motivate the final year medical students by developing their skills to improve their competence and by providing adequate protection for the willing students to function as volunteers.
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Knowledge discovery in databases (KDD) is another name of Data mining. It is an interdisciplinary area which focuses on extraction of useful knowledge from data in every sector like health, education, business etc. There are many fields to explore like business, health care, e-commerce etc but nowadays, as covid pandemic is affecting everyone and due to surge in coronavirus cases causing shortage of hospital beds, oxygen supplies, vaccine and turning away patients from hospitals, put creaky health infrastructure in spotlight. The plenty of data is available in the medical field of these conditions. To analyse the problems, there are many data mining approaches which can be used to extract useful patterns from these types of data to follow the upcoming trends. This study is to compare the various models like KNN, improved RF model and multilayer perceptron by using SPSS and python software. The data of COVID-19 has been taken from Kaggle's website which is based on the symptoms and the forecasted results has been shown. In results and conclusion, the performance of every model has shown along with this, it also shows the models and mathematical algorithms in various fields of healthcare accordingly which can be used and benefitted in medical industries. © 2022 by the Author(s).
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Background Pulmonary embolism (PE) is a common and fatal complication of COVID-19 infection. COVID-19's main clinical manifestations are not only pneumonia but also coagulation disorders. This study evaluates the prevalence of pulmonary embolism at CT pulmonary angiography (CTA) for positive coronavirus patients as well as the factors associated with PE severity. Materials and methods This is a retrospective cross-sectional study that was conducted at King Faisal Medical Complex (KFMC) in Taif city of Saudi Arabia from June 2020 to June 2021. Data was collected from the picture archiving and communication system (PACs) for a total of 445 positive patients who underwent CT pulmonary angiography and analyzed using SPSS. Results The mean age and gender of the male were 57.3 ± 15.8 years and 64.5%, respectively. The prevalence of pulmonary embolism at CTA among patients with COVID-19 was found to be 8.1%. Bilateral segmental and bilateral subsegmental pulmonary embolism were found to be the most common sites for PE (16.7% for each). Furthermore, shortness of breath (SOB) was found to be the most common reported symptom among the respondents. Lastly, shortness of breath, chest pain, loss of taste or smell, D-dimer, and cardiac troponin were found to be significantly associated with PE (P-value = < 0.001, <0.001, 0.001, <0.001 and 0.037 respectively). Conclusion Present results show that the prevalence of pulmonary embolism among COVID19 patients with CT Pulmonary Angiography at KFMC is relatively low (8.1%) and most of the patients were from the ICU department. Early detection and treatment of COVID-19 patients with PE and APE complications are critical for lowering the mortality rate.
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The epidemic has had a profound impact on Chinese economy. In order to explore which factors have played an important role in Chinese economic development, this paper uses Internet software such as SPSS to construct a regression model to process and analyze economic data and evaluate its impact. First, we use SPSS software to construct a regression equation model that affects China's economic development. After that, we select four new factors affecting China's economic development : personal consumption level, financial data governance level, big data support capabilities, and robotics capabilities. After that, we use the SLOPE regression function model to calculate the P value, the correlation coefficient beta and the variance var value, and derived the regression parameter equation from this. Finally, based on regression equations and regression coefficients, new suggestions for China's economic development are put forward. © 2021 IEEE.
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The challenges and problems that the educational programs are facing nowadays are those that previously have not been present, therefore, the solutions of these concerns should be compatible and reasonable in order to have a complete function of the educational institutions, especially the universities that are in transition such as University 'UH' of Prizren. The main reasons for addressing this topic through this paper are the ongoing discussions from students for not being able to learn enough during classes lectured by different professors in the Faculty of Economics. In order to get the most reliable results, this paper used the statistical program SPSS v.26 in which various methods such as descriptive statistics, factor analysis, reliability, linear regression, and One-Way ANOVA analysis are implemented. Moreover, this study shows the analysis of the connection and comparison of these methods. The results of this research are sustainable of e-learning services and the form of generating of the quality model. Further, the relationship of these models highlights among factors and provides a research foundation for elaboration in other contexts.
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Migration and remittances in Kosovo are promoters of local economic development and have an important role in the economic well-being of citizens, as well as other aspects in financing and developing the economy through stimulation. This article will evaluate and assess using subjective research methodologies the impact of diaspora during the pandemic period time. Anytime was crucial for many citizens that depend on the remittances, according to this statement, we mention that diaspora has a major role also in economic development in general. So, the purpose of this paper is to define and deeply explain the socio-economic outcomes of diaspora during the pandemic of COVID-19. In this way, we have used two types of data, primary and secondary for further analysis where we have used different techniques such as descriptive, crosstab, and Chi-square, which we have analyzed and shown by using SPSS software. Also, our paper is based on Hamdi Hoti and Hoxha’s (2018) and Jusufi and Ukaj’s (2020) findings and suggests that remittances have always been one of the most important and stable sources of external financing for the country. This is very important for states such as the Republic of Kosovo. © 2022 The Authors.
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Background: In the era of the COVID-19 pandemic, nonadherence to the recommended physical exercise for diabetic patients is a difficult issue. Regular physical exercise is critical for reducing further complications of diabetes mellitus and the COVID-19 pandemic. The purpose of this study was to determine the predictors of type 2 adult diabetes patients' exercise recommendations during the COVID-19 pandemic. Methods: An institution-based cross-sectional study was conducted among 576 diabetes mellitus patients from August 1, 2020, to September 28, 2020. A systematic random sampling technique was used to select the study participants. An interviewer-administered questionnaire was used to collect the data. Frequency tables and percentages were used to explain the study variables. A binary logistic regression was used to investigate the relationship between the dependent and independent variables. Result: A total of 576 diabetes mellitus patients participated in the study, with a response rate of 99.3%. The overall prevalence of exercise adherence was 26.4%, whereas 73.6% were non-adherents to exercise recommendations. Rural residency (AOR = 1.95, 95% CI: 1.16-3.27) and COVID-19 related knowledge (AOR = 9.95, 95% CI: 41.14-5.24) were both strongly associated with exercise recommendations. Conclusion: In this study, only one-fourth of patients had exercised adherence during the era of the COVID-19 pandemic. Knowledge about COVID-19 was one of the factors that was strongly associated with adherence to exercise recommendations for diabetes patients. During the COVID-19 pandemic, encouraging home-based exercises can improve adherence to exercise recommendations.
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BACKGROUND: Vaccination intent is defined as the willingness to get vaccinated against a COVID-19 pandemic in a situation where the vaccine is available at no cost. Nevertheless, even with the availability of COVID-19 vaccines, some part of the public is not expected to get vaccinated, mainly due to a phenomenon known as vaccine hesitancy or lack of intention. Furthermore, there is little information available on the intention of people with chronic medical conditions about the COVID-19 vaccines in Ethiopia. OBJECTIVE: The study aimed to assess the intent to get vaccinated against COVID-19 and its associated factors among adults with a chronic medical condition. METHOD: An institutional-based cross-sectional study was conducted from February 15 to March 15, 2021. Simple random sampling was employed to get representative samples. Data were collected by using a structured questionnaire through face to face interviews. The data were entered by Epi Info version 7 and analyzed with SPSS version 20. The data were analyzed by using binary logistic regression. Those variables with a P-value of ≤ 0.05 were considered significantly associated with the outcome variable. RESULT: In this study, 423 study participants took part with a response rate of 100%. The mean age of the study participants was 50.07 (SD ± 13.7) with a range of 18-85 years. The intention to get vaccinated against the COVID-19 pandemic was 63.8% [95% CI (58.6-68.2)]. In the multivariable analysis the variables, retiring from the job was [AOR = 2.65, 95% CI (1.02-10.35)], having health insurance coverage [AOR = 1.38, 95%CI (1.04-3.65)], being in the high socio-demographic status [AOR = 1.67, 95%CI (1.01-2.78)], being confident with the Country's health care system [AOR = 2.00, 95%CI (1.15-3.49)], and having good knowledge about COVID-19 [AOR = 6.59, 95% CI (4.02-10.78)] were significant predictors of intent to get vaccinated against COVID-19 pandemic compared. CONCLUSION: The intention of getting vaccinated against the COVID-19 pandemic was relatively low. There has to be a great effort by the health caregivers as well as the government to increase vaccination intake, particularly for these priority groups.
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Background: COVID-19 emerged as a global pandemic in 2020, spreading rapidly to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via serosurveillance, making it a valuable tool for planning control measures. Our serosurvey study aimed to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. Methods: This cross-sectional survey, conducted in January 2021 and including males and females aged 10 years and above, used multi-stage random sampling. 9363 samples were collected from 30 wards distributed over six zones of Hyderabad, and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. Results: Overall seropositivity was 54.2%, ranging from 50% to 60% in most wards. Highest exposure appeared to be among those aged 30-39 and 50-59 years, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for COVID-19 testing. Conclusion: Over half the city's population was infected within a year of onset of the pandemic. However, â¼ 46% of people remained susceptible, contributing to subsequent waves of infection.