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Background: SARS-CoV-2 continues to change over time due to genetic mutations and viral recombination.1 Given the changing landscape of COVID-19 variants and availability of COVID-19 vaccinations, disease severity during acute infection has also been variable. However, most research related to COVID-19 to date has not focused on evaluating differences in outcomes by the dominant variant and the impact it might have on post-acute sequalae of COVID-19 (PASC). Method(s): We developed a data mart of electronic health record data pertaining to COVID-19 in a single North American metropolitan health system (RUSH University Medical Center). Patients were selected for analysis if they had at least one documented infection of COVID-19. Date ranges were established per dominant variant, and the date of diagnosis was matched to variant. Variants were determined by the most prominent variant of concern (VOC) circulating in the city of Chicago. Variants were categorized by the following by date ranges: Wildtype+D614G (3/7/20-3/20/21), Alpha (3/21/21-6/19/21), Delta (6/20/21-12/11/21), Omicron BA.1 (12/12/21-3/19/22), Omicron BA.2 (3/20/22- 6/18/22), and Omicron BA.4/BA.5 (6/19/22-present (9/30/22). Subsequent clinical outcomes were examined, including hospitalization, intensive care unit admission, or death. We characterized our sample by conducting descriptive statistics including frequency and percent of outcome by variant. Result(s): 44,499 patients were included in this analysis with 30.23% requiring hospitalization, 4.25% being admitted to intensive care unit (ICU), and 2.35% resulting in death. The greatest percentage of hospitalizations occurred with the Alpha variant at 41.88% (N=928), and the greatest percentage of ICU admissions (6.43%) and death (3.15%) occurred with the Delta variant. The latest Omicron variant (Wave 6) showed an increase in hospitalizations (35.18%), as compared to early Omicron waves (Wave 4 and 5) but maintained similar ICU rates. Death rates continued to decline during the Omicron waves (Table 1). Conclusion(s): Although Alpha and Delta variants seem to have more severe outcomes compared to other variants, it is important to note that COVID-19 prevention, treatment access, and management continues to change, potentially influencing how outcomes may differ over time. Future work should determine factors to adjust for when examining variant-level differences.
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The outbreak of COVID-19 at the end of 2019 spreads over the world extensively and rapidly. The daily lives are affected by lockdowns, work-from-home, and travel bans. The economic growth is stagnated. Many industries are severely affected by this pandemic. There are, however, also industries that are unexpectedly benefited from the pandemic. The objective of this paper is to investigate the industries in Taiwan that are affected by the pandemic. Samples of the top 1,000 manufacturing and the top 500 service companies in Taiwan are collected to calculate their productivities before the pandemic, in the period of 2016–2019, and during the pandemic, in the year of 2020. The results show that three industries: automobile, tourism, and electronic products distribution, have their productivities significantly decreased by 3.98%, 4.92%, and 1.27%, respectively. There are also four industries: electronic components, optoelectronic, electrical and cable, and oil, gas and electricity, whose productivities are unexpectedly increased significantly by 1.37%, 1.98%, 3.32%, and 4.31%, respectively. The impact of COVID-19 to large companies in Taiwan seems to be not severe. In 2021, approximately five sixths of the industries have their productivities increased. There are only five industries whose productivities become lower;however, the decreases are not significant, indicating that the economy in Taiwan is recovering from the pandemic. © 2023 The Authors
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Stress is integral to biological survival. However, without an appropriate coping response, high stress levels and long-term stressful situations may lead to negative mental health outcomes. Since the COVID-19 pandemic, remote assessment of mental health has become imperative. The majority of past studies focused on detecting users' stress levels rather than coping responses using social media. Because of the diversity of human expression and because people do not usually express stress and the corresponding coping response simultaneously, it is challenging to extract users' tweets about their coping responses to stressful events from their daily tweets. Consequently, there are two goals being pursued in this study: to anchor users' stress statuses and to detect their stress responses based on the existing stressful conditions. In order to accomplish these goals, we propose a framework that consists of two phases: the construction of stress dataset and the extraction of coping responses. Since the stressed users' data are lacking, the first phase is to construct a stress dataset based on stress-related hashtags, personal pronouns, and emotion recognition. In addition, to ensure the collection of enough tweets to observe the coping responses of stressed users, we broadened the survey's scope by collecting all tweets from the same user. In the second phase, stress-coping tweets were extracted by utilizing bootstrapping-based patterns and semantic features. The bootstrapping method was used to enrich word patterns for text expression and the semantic feature to assess the meaning of sentences. The collected data included the tweets of the stressed users identified in Phase 1 and the various coping responses from Phase 2 can contribute to developing a tool for the remote assessment of mental health. The experimental results show that our two-phase method outperforms the baseline and can help improve the efficiency of extracting stress-coping tweets. © 2022 IEEE.
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The imposition of COVID-19 lockdown restricted the daily activities of many people, including athletes. This study investigated the training practices of athletes in the Philippines during the early COVID-19 lockdown. A total of 442 athletes answered an online survey (May-July 2020), with questions pertaining to training practices, such as training frequency and duration. Data were analyzed according to: athlete classification (world-class, international, national, state, or recreational), sport category (individual or team), and sex (male or female). During lockdown, significant reductions in training frequency (except recreational, i.e., lower pre-lockdown training) and duration were observed for all athletic classifications. Similarly, training frequency and duration decreased significantly irrespective of sport category and sex. World class athletes appeared to be less affected by lockdown (types of exercise and specific training) as compared to lower-classification athletes. Athletes grouped in accordance with sex and sport category demonstrated little to no difference in training practices during the COVID-19 lockdown. The findings of the current study highlight the challenges experienced by athletes during lockdown, which may aid policy makers in the development of guidelines related to lockdown or lockdown-like situations to establish appropriate support for affected athletes. © 2022, University of Zagreb - Faculty of Kinesiology. All rights reserved.
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Background: The COVID-19 pandemic has renewed attention to the conflicting demands placed on caregivers worldwide. Nowhere is this more evident than in South Asia, where cultural norms and a scarcity of long-term care facilities have made the home the locus of caregiving for individuals with brain health conditions and disabilities. A hidden cost of this informal arrangement is the burden experienced by the primary caregiver. This may be exacerbated when traditional caregiving expectations clash with personal aspirations outside the family. Method(s): The COVID-19 pandemic has renewed attention to the conflicting demands placed on caregivers worldwide. Nowhere is this more evident than in South Asia, where cultural norms and a scarcity of long-term care facilities have made the home the locus of caregiving for individuals with brain health conditions and disabilities. A hidden cost of this informal arrangement is the burden experienced by the primary caregiver. This may be exacerbated when traditional caregiving expectations clash with personal aspirations outside the family. Result(s): The COVID-19 pandemic has renewed attention to the conflicting demands placed on caregivers worldwide. Nowhere is this more evident than in South Asia, where cultural norms and a scarcity of long-term care facilities have made the home the locus of caregiving for individuals with brain health conditions and disabilities. A hidden cost of this informal arrangement is the burden experienced by the primary caregiver. This may be exacerbated when traditional caregiving expectations clash with personal aspirations outside the family. Conclusion(s): Role strain may be a significant driver of burden when the caretaker's educational and professional potential collide with traditional South Asian family obligations. The burden reported by our respondents suggests that role strain may elevate stress among young, educated caregivers. Our results, therefore, provide indirect evidence concerning the changing economic and socio-cultural context of caregiving in South Asian households. Copyright © 2022 the Alzheimer's Association.
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Background: Public health restrictions due to the COVID-19 pandemic have affected care partners of people living with dementia and/or mental health conditions. This qualitative study explores care partners' ability to offer care, and changes and interruptions to care provision during the period of the COVID-19 pandemic (2020) in English-speaking regions worldwide. Method(s): As part of an international cross-sectional online survey, qualitative data were collected from over 1,000 English-speaking care partners of people living with dementia and/or mental health conditions. Responses to an open-ended question about ability to care were coded and analysed thematically. The analysis was undertaken by three independent interdisciplinary coding dyads. Result(s): A number of main themes and subthemes were generated through the analysis. Reduced in-person contact with the person with a brain health condition and restrictions in health and social care services created practical, psychological and emotional impacts for care partners. The lack of adequate information from health/social care services, deterioration in the condition of the person living with a brain health condition, and additional care hours/duties were identified. Care partners also mentioned the fear of virus transmission and increased awareness of public health measures as factors that changed or interrupted their ability to provide care. Conclusion(s): The ability of care partners to provide care was changed or interrupted, and disruption to routines and services available impacted on their well-being. These findings reflect the complexity of the care partner role and highlight the importance of supporting care partners, in particular during periods of service restrictions such as those experienced as a result of the pandemic. Findings will be of interest to policymakers and service providers. Copyright © 2022 the Alzheimer's Association.
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Background: Informal caregivers may experience high levels burden. Prior to COVID-19, loneliness and social isolation, and especially the discordance between them, were recognized for rapid aging-related cognitive decline. The COVID-19 has significantly increased social isolation and loneliness in caregivers. Thus, we aimed to explore the variables that were associated with higher care burden among all caregivers and only among caregivers for people living with dementia, and whether the increased burden could be associated with a discrepancy between loneliness and social isolation. Method(s): 'Comparing Loneliness and Isolation in COVID-19' was an online global survey of over 20,000 respondents, including 5243 caregivers across 50 countries with enduring brain or/and physical health conditions. We first used a multilevel modelling to identify risk factors associated with higher burden. Then, we defined profiles of discrepancy between loneliness and social isolation, based on the differences between standardized score on a scale of loneliness and of social connectedness and estimated the association between the discrepancy and higher burden. Result(s): In our sample, 74% of caregivers were female, 44% were caring for people with dementia, and 22% for people with multiple conditions, including dementia. The most prevalent age group was 60-69 years old. Factors significantly associated with higher care burden were being female, having poorer financial situation, worse mental health during the pandemic, caring for people with dementia or intellectual disabilities, caring in the same home, being diagnosed with COVID, and changes of care abilities. 40% of caregivers consistently reported high level of loneliness and social isolation, 38% reported consistent lower levels of both, and two groups reported discordance (low levels of loneliness and high social isolation in 13%;high levels of loneliness and mild social isolation in 12%). The latter group was at the highest risk of self-reported increased and intense care burden. Conclusion(s): This represents the largest, most widespread survey on the impact of the COVID-19 pandemic on caregivers of people with long-term conditions to date and reflects the importance of capturing the nuances in the relationship between loneliness and social isolation in caregivers. It will be an important resource for support agencies and to inform policy. Copyright © 2022 the Alzheimer's Association.
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Background: During the COVID-19 pandemic, loneliness has increased in the general population due to government measures to contain the spread of the disease. In Latin America (LA), caregiving is most often delivered informally by family members Family caregivers often face mental health challenges linked to their caregiving role and their social context. Pandemic-related social restrictions have been especially detrimental for older people with dementia or other brain health challenges, as well as their family caregivers. We aimed to investigate the associations of loneliness, social isolation and care burden in these family caregivers. Method(s): We undertook a cross-sectional survey of over 300 informal caregivers of people with dementia or enduring mental health problems living in 4 Latin American countries, Mexico, Brazil, Chile, and Peru. We categorized loneliness into 3 groups 'low', 'moderate' and 'severe loneliness'. Here, we analyzed factors related to changes in the prevalence of moderate and severe loneliness before and during the pandemic using a longitudinal multinomial logistic regression model. Result(s): During the pandemic, there was a significant increase in loneliness prevalence (p<.001) among caregivers in Latin America, with more people having moderate (6.25% pre-pandemic;17.67% mid-pandemic) and severe loneliness (2.78% pre-pandemic;15.19% mid-pandemic). Gender differences in the prevalence of loneliness or higher levels of loneliness among dementia caregivers compared to caregivers of other conditions were not seen. The regression model revealed that the increment in risk for moderate loneliness during the pandemic was related to caregivers' age, level of education, and social contact/isolation. Increased risk for severe loneliness was related to caregivers' social contact during the pandemic and perceived mental health. Conclusion(s): Public health interventions regarding COVID-19 pandemic should consider increased loneliness in Latin-American caregivers. This population will need both, short and long-term mental health and practical support. Next steps include gathering more evidence on specific risk factors for loneliness and its impact on caregivers' physical and mental health. Copyright © 2022 the Alzheimer's Association.
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Epidemics such as COVID-19, SARS, H1N1 have highly transmissible viruses and spread wildly through the population with negative consequences. Multiple studies have shown the correlation between the contact networks between individuals and the transmission of infections due to contact between colocated individuals. To mitigate the transmission of the virus, intervention measures have been applied without decisive success. Therefore, reducing transmissions through suitable epidemicaware POI recommendations to users is necessary to cope with user mobility. Current POI recommendation approaches do not take into consideration the transmission of infections between co-located users. In this paper, we formulate a new query named Epidemic-aware POI Recommendation Query (EPQ), to timely recommend a set of POIs to users at different time steps, while considering the spread of infection between co-located users, their social friendships, and their preference. We prove that EPQ is NP-hard and propose an effective and efficient algorithm, Epidemic-aware POI Recommendation (EpRec) to tackle EPQ. We evaluate EpRec on existing location-based social networks and pandemic datasets against state-of-the-art algorithms. The experimental results show that EpRec outperforms the baselines in effectiveness and efficiency. © 2022 IEEE.
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Emotional states are social and highly influenced by city attributes. Population, for example, has a direct impact on parameters such as connections, communication, and social interaction based on urban scaling laws. It is likely that population also influences emotional experiences, as emotions are regulated by social activity. To analyze emotional states in social interaction, that is, emotion interaction, urban scaling properties are applied to the Twitter activity and emotion interactions of major cities in the USA and UK. To our knowledge, emotion interaction has yet to be explored through urban scaling laws. Furthermore, the world is facing the COVID-19 pandemic, which has severely affected the physical and emotional well-being of humans. This study compares emotion interaction during COVID-19 and before it started to analyze the impact of population on deviating emotional states. The findings suggest that emotion interaction follows superlinear scaling, i.e., there is an increase in emotion interaction with an increase in population. However, negative emotion interaction tends to increase more in response to population. The statistics on emotional interaction in cities reflect cognitive experiences of cities as well as an understanding of human behavior in expanding urban environments, which can be useful in defining the narratives of cities and developing citizen-centric sustainable and resilient city plans. © 2021 IEEE.
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To investigate how tax analytics and automation have been deployed, the authors examined the following questions: * What were the potential benefits of TAA technologies when companies considered using them in their corporate tax departments? * How have these companies deployed TAA technologies? * How integrated have the TAA technologies been used in the corporate tax department of companies-specifically, tax compliance, tax provision, tax planning, tax strategy? * What are the key factors influencing the corporate tax department's ability to conduct tax analytics and automation? Benefits of TAA Technologies Question 1 in the online survey asked respondents to rate (on a 5-point scale ranging from "not significant" to "very significant") how significant each of the following potential benefits was when their organization was considering using TAA technologies in its corporate tax department: * To reduce cost in the tax department * To enter new tax services * To improve coordination of the tax department with other departments * To analyze large data sets * To expand tax services * To enhance tax reporting. The applications included the following: * Automating of repetitive or rulesbased tasks currently performed by tax professionals (e.g., state apportionment, tax treatment of travel expenses, likekind exchange matching, tax depreciation classifications) * Data mining and the process of finding previously unknown relationships and patterns (e.g., tax data exploration, fraud detection) * Leveraging advanced statistical or computer science tools to mimic human decision making in tax (e.g., artificial intelligence) * Other (please describe). Survey respondents offered coimnents, including leveraging workflows across different tax disciplines using various licensed tools to better analyze large data sets (Power BI, Alteryx), review tax returns (e.g., tax adjustments, wording of line descriptions, and comparison to prior year), improve data analysis of tax data warehouse to drive efficiency, adopt dashboard reporting of decision quality analytics, and financial modeling.
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In the diagnosis of severe contagious diseases such as Ebola, severe acute respiratory syndrome, and COVID-19, there is an urgent need for protein sensors with large refractive index sensitivities. Current terahertz metamaterials cannot be used to develop such protein sensors due to their low refractive index sensitivities. A simple method is proposed that is compatible with all geometrical structures of terahertz metamaterials to increase their refractive index sensitivities. This method uses patterned photoresist to float the split-ring resonators (SRRs) of a terahertz metamaterial at a height of 30 μm from its substrate that is deposited with complementary SRRs. The floating terahertz metamaterial has an extremely large refractive index sensitivity of 532 GHz/RIU because its near field is not distributed over the substrate and also because the complementary SRRs confine the field above the substrate. The floating terahertz metamaterial senses bovine serum albumin (BSA) and the protein binding of BSA and anti-BSA as BSA, and anti-BSA solutions with low concentrations that are smaller than 0.150 μmol/L are sequentially dropped onto it. The floating terahertz metamaterial is a great achievement to develop protein sensors with extremely large refractive index sensitivities, and has the potential to sense dangerous viruses. © 2021 Chinese Laser Press.
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Tour traffic prediction is very important in determining the capacity of public transportation and planning new transportation devices, allowing them to be built in accordance with people's basic needs. From a review of a limited number of studies, the common methods for forecasting tour traffic demand appear to be regression analysis, econometric modeling, time-series modeling, artificial neural networks, and gray theory. In this study, a two-step procedure is used to build a predictive model for public transport. In the first step of this study, regression analysis is used to find the correlations between two or more variables and their associated directions and strength, and the regression function is used to predict future changes. In the second step, the regression analysis and artificial neural network methods are assessed and the results are compared. The artificial neural network is more accurate in prediction than regression analysis. The study results can provide useful references for transportation organizations in the development of business operation strategies for managing sustainable smart cities.
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Background: Remdesivir (RDV) has been shown to shorten recovery time and was well tolerated in patients with severe COVID-19. Here we report safety of RDV in patients with moderate COVID-19. Methods: We conducted an open-label, phase 3 trial (NCT04252664) in hospitalized patients with confirmed SARS-CoV-2 infection, evidence of pulmonary infiltrates, and oxygen saturation >94% on room air. Patients were randomly assigned to receive RDV (5 or 10 days) or standard of care (SOC). RDV was dosed intravenously at 200 mg on day 1, 100 mg daily thereafter. Adverse events (AEs) and laboratory abnormalities were evaluated through the day 11 data cut;safety data through day 28 will be presented at the meeting. Results: 584 patients were randomized and treated (5d RDV: n=191;10d RDV, n=193;SOC: n=200). Baseline characteristics were balanced among groups;median (range) age was 57y (12-95y), 39% were female and 19% Black, 39% had arterial hypertension, 15% hyperlipidemia, 11% asthma. Briefly, across both the 5d and 10d arms, RDV was well tolerated with a similar rate of Grade 3 or 4 AEs and fewer SAEs compared to SOC (Table). AEs more common with RDV vs SOC included nausea, headache, and hypokalemia. Overall, across the 3 arms, incidence of AEs leading to discontinuation and death were low and no clinically relevant changes in laboratory parameters were observed. In addition, median changes in renal and liver function tests from baseline were not statistically significant between the RDV 5d and RDV 10d groups compared to the SOC only group at d14 (Table 1). Conclusion: RDV given for 5d or 10d was well tolerated in patients with moderate COVID-19. No clinically significant safety signals were observed with RDV vs SOC. (Figure Presented).
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Background: Remdesivir (RDV), a RNA polymerase inhibitor with potent in vitro activity against SARS-CoV-2, is the only treatment with demonstrated efficacy in shortening the duration of COVID-19. Here we report regional differences in clinical outcomes of severe COVID-19 patients treated with RDV, as part of an open-label, randomized phase-3 trial establishing RDV treatment duration. Methods: Hospitalized patients with oxygen saturation ≤94%, a positive SARS-CoV-2 PCR in the past 4 days and radiographic evidence of pneumonia were randomized 1:1 to receive 5d or 10d of intravenous RDV. We compared d14 clinical outcomes of patients from different geographical areas, as measured by mortality rates, change in clinical status from baseline (BL) on a 7-point ordinal scale and change in O2 requirements from BL. Based on previous analyses in compassionate use data showing region as an important predictor of outcome, Italy was examined separately from other regions. Results: 397 patients were treated with RDV, of which 229 (58%) were in the US, 77 (19%) Italy, 61 (15% in Spain), 12 (3%) Republic of Korea, 9 (2%) Singapore, 4 (1%) Germany, 4 (1%) Hong Kong and 1 (< 1%) Taiwan. BL clinical status was worse in Italy compared to other regions (72% vs 17% requiring high-flow oxygen delivery or higher), and Italian patients were more likely to be male than patients from other regions (69% vs 63%). Overall results showed 5d RDV was as effective as 10d. Mortality at d14 was higher in Italy (18%) compared to all other countries except Italy (7%). Similarly, clinical improvement at d14, measured as ≥2-point increase in the ordinal scale, was lower in Italian patients (39%) compared to all other countries combined (64%). (Fig.1). Conclusion: Overall, our results demonstrate significant geographical differences in the clinical course of severe COVID-19 patients treated with RDV. We observed worse outcomes, such as increased mortality and lower rate of clinical improvement, in patients from Italy compared to other regions. (Table Presented).
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In responding to United Nations' Sustainable Development Goals, using digital entrepreneurship to replicate proven sustainability innovation is an effective approach to scaling up the franchise systems to achieve the goals. The authors show a platform of sustainability innovation enabled by digital entrepreneurship in nurturing a trusted franchisor-franchisee relationship to grow the franchise system. The platform is a digital nervous system consisting of technology networks, social networks, value networks, and responsive networks. The platform is grounded in synergistically integrating the digital capability of developing and disseminating working knowledge globally and effective entrepreneurial solutions locally. Sustainability innovation through such a methodology is a win-win approach to both franchisor and franchisees. An exemplar illustration of how franchise systems help in the fight against COVID-19 is included. © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.