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This study is designed to explore the impacts of the COVID pandemic on the socio-economic status of textile workers and to suggest ways for balancing the turnover rate. For the study, a cross-sectional study design and mixed-method approach were employed. The researchers conducted a questionnaire survey of 357 textile workers using convenience sampling and, 5 KIIs, 20 IDIs, and 5 FGDs using purposive sampling. The study area was the Gazipur district of Bangladesh, a hub of the textile industry. Findings from Principle component analysis revealed that 54.38% of the total observed variation can be explained by five components. Working Environment (r = –0.699), Payment System (r = .987), Savings (r = .920), Employee Turnover Rate (r = .769), and Social Status (r = .558) of employees are identified by PCA as the most strongly correlated variables that have significant impacts on the socio-economic condition of textile workers due to Covid 19 pandemic. Finally, through Logistic Regression Analysis, the study has found that Safe Working Environment (OR = 0.203, 95% CI 0.098-0.419), Satisfactory Payment Structure (OR = 2.196, 95% CI 1.354-3.561), and Provident Fund Facilities (OR = 2.908, 95% CI 1.497-5.651) can reduce the turnover rate of textile workers. Additionally, effective labor unions and adequate training facilities can also balance the adverse socio-economic impacts on the textile workers. © 2023 DMICS.
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Introduction: COVID-19 disease has been declared as a pandemic since February 2020. Resulting from this, home peritoneal dialysis training programme was implemented. However, infectious complications was one of our major concerns. Material(s) and Method(s): This is a single centre, observational, retrospective study. We recruited patients who were newly enrolled into the peritoneal dialysis programme from January 2020 until March 2021 and follow up them for 6 months duration. Patients' demographic data, baseline characteristic, clinical outcome were collected through electronic health record (eHIS) and data were analysed using SPSS version 23. Result(s): A total of 133 patients were enrolled into the peritoneal dialysis programme. The median age of the patients was 55(42-65) years old. Most of the patients were on CAPD, 87(65.4%), and 76(57.1%) of them were on self-care peritoneal dialysis (PD). During this observational period, 29(21.8%) patients underwent hospital based training, while a total of 104(78.2%) patients underwent home based training. The PD peritonitis rate for hospital based training was 1 episode per 55.8 patient months while home based training group was 1 episode per 25.4 patient month. The survival free to 1st PD peritonitis for home based training was 83.7% over 6 months. The exit site infection rate was 1 episode per 73.1 patient month. Conclusion(s): Home based PD training should be encouraged especially during Covid-19 pandemic period, but standardised training protocol should be implemented to improve the clinical outcome of our patients.
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Purpose The purpose of this paper is to develop a model to examine how different technological and cognitive cues related to mobile food ordering applications (MFOAs) impact diners' intentions to use MFOAs continuously. The moderating role of national household demographics was also assessed in the online-to-offline (O2O) food delivery services (FDS) context. Design/methodology/approach Drawing insights from the uses and gratification (U&G) theory, an online sample survey of 968 valid respondents who had ordered or purchased food through delivery apps during the COVID-19 outbreak in China was used for the analysis. The proposed model was empirically tested using structural equation modeling. Findings The results revealed that cues in MFOAs (i.e. ease of use, convenience, price saving orientation, the listing of various food choices, exploring restaurant patterns, and compatibility) directly influenced diners' e-satisfaction and that intention to use continuously is triggered by e-satisfaction during the COVID-19 crisis. Moreover, this study found that collectivist household diners emphasized ease of use, convenience, and compatibility. Comparatively, individualistic household diners placed more importance upon price saving orientation and listing of various food choices during the pandemic. Originality/value The authors offer a new insight into customers' dining choices by extending the scope of O2O services in the food industry. The findings contribute to understanding diners' purchase decision-making processes regarding MFOAs' O2O-FDS during the COVID-19 crisis. The multi-group comparison via national household demographics also provides a new perspective regarding different dining preferences toward O2O-FDS.
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Amplicon-based sequencing methods have been central in characterizing the diversity, transmission and evolution of SARS-CoV-2, but need to be rigorously assessed for clinical utility. Here, we validated the Swift Biosciences SARS-CoV-2 Swift Normalase Amplicon Panels using remnant clinical specimens. High quality genomes meeting our established library and sequence quality criteria were recovered from positive specimens with a 95% limit of detection of 40.08 SARS-CoV-2 copies/PCR reaction. Breadth of genome recovery was evaluated across a range of Ct values (11.3 - 36.7, median 21.6). Out of 428 positive samples, 406 (94.9%) generated genomes with < 10% Ns, with a mean genome coverage of 13,545X/SD 8,382X. No genomes were recovered from PCR-negative specimens (n = 30), or from specimens positive for non-SARS-CoV-2 respiratory viruses (n = 20). Compared to whole-genome shotgun metagenomic sequencing (n = 14) or Sanger sequencing for the spike gene (n = 11), pairwise identity between consensus sequences was 100% in all cases, with highly concordant allele frequencies (R2 = 0.99) between Swift and shotgun libraries. When samples from different clades were mixed at varying ratios, expected variants were detected even in 1:99 mixtures. When deployed as a clinical test, 268 tests were performed in the first 23 weeks with a median turnaround time of 11 days, ordered primarily for outbreak investigations and infection control.
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AcrodyniaABSTRACT
Emerging voices of patients in the form of opinions and expectations about the quality of care can improve healthcare service quality. A large volume of patients' opinions as online doctor reviews (ODRs) are available online to access, analyze, and improve patients' perceptions. This paper aims to explore COVID-19-related conversations, complaints, and sentiments using ODRs posted by users of the physician rating website. We analyzed 96,234 ODRs of 5,621 physicians from a prominent health rating website in the United Kingdom (Iwantgreatcare.org) in three-time slices (i.e., from February 01 to October 31, 2020). We employed machine learning approach, dynamic topic modeling, to identify prominent bigrams, salient topics and labels, sentiments embedded in reviews and topics, and patient-perceived root cause and strengths, weaknesses, opportunities, and threats (SWOT) analyses to examine SWOT for healthcare organizations. This method finds a total of 30 latent topics with 10 topics across each time slice. The current study identified new discussion topics about COVID-19 occurring from time slice 1 to time slice 3, such as news about the COVID-19 pandemic, violence against the lockdown, quarantine process and quarantine centers at different locations, and vaccine development/treatment to stop virus spread. Sentiment analysis reveals that fear for novel pathogen prevails across all topics. Based on the SWOT analysis, our findings provide a clue for doctors, hospitals, and government officials to enhance patients' satisfaction and minimize dissatisfaction by satisfying their needs and improve the quality of care during the COVID-19 crisis. © 2021 University of Kuwait. All rights reserved.
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Background: People of minority ethnic backgrounds may be disproportionately affected by severe COVID-19. Whether this relates to increased infection risk, more severe disease progression, or worse in-hospital survival is unknown. The contribution of comorbidities or socioeconomic deprivation to ethnic patterning of outcomes is also unclear. Methods: We conducted a case-control and a cohort study in an inner city primary and secondary care setting to examine whether ethnic background affects the risk of hospital admission with severe COVID-19 and/or in-hospital mortality. Inner city adult residents admitted to hospital with confirmed COVID-19 (n = 872 cases) were compared with 3,488 matched controls randomly sampled from a primary healthcare database comprising 344,083 people residing in the same region. For the cohort study, we studied 1827 adults consecutively admitted with COVID-19. The primary exposure variable was self-defined ethnicity. Analyses were adjusted for socio-demographic and clinical variables. Findings: The 872 cases comprised 48.1% Black, 33.7% White, 12.6% Mixed/Other and 5.6% Asian patients. In conditional logistic regression analyses, Black and Mixed/Other ethnicity were associated with higher admission risk than white (OR 3.12 [95% CI 2.63–3.71] and 2.97 [2.30–3.85] respectively). Adjustment for comorbidities and deprivation modestly attenuated the association (OR 2.24 [1.83–2.74] for Black, 2.70 [2.03–3.59] for Mixed/Other). Asian ethnicity was not associated with higher admission risk (adjusted OR 1.01 [0.70–1.46]). In the cohort study of 1827 patients, 455 (28.9%) died over a median (IQR) of 8 (4–16) days. Age and male sex, but not Black (adjusted HR 1.06 [0.82–1.37]) or Mixed/Other ethnicity (adjusted HR 0.72 [0.47–1.10]), were associated with in-hospital mortality. Asian ethnicity was associated with higher in-hospital mortality but with a large confidence interval (adjusted HR 1.71 [1.15–2.56]). Interpretation: Black and Mixed ethnicity are independently associated with greater admission risk with COVID-19 and may be risk factors for development of severe disease, but do not affect in-hospital mortality risk. Comorbidities and socioeconomic factors only partly account for this and additional ethnicity-related factors may play a large role. The impact of COVID-19 may be different in Asians. Funding: British Heart Foundation;the National Institute for Health Research;Health Data Research UK. FAU - Zakeri, Rosita