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Many people with mobility disabilities (PwMD) rely on public transit to access crucial resources and maintain social interactions. However, they face higher barriers to accessing and using public transit, leading to disparities between people with and without mobility disabilities. In this paper, we use high-resolution public transit real-time vehicle data, passenger count data, and paratransit usage data from 2018 to 2021 to estimate and compare transit accessibility and usage of people with and without mobility disabilities. We find large disparities in powered and manual wheelchair users' accessibility relative to people without disabilities. The city center has the highest accessibility and ridership, as well as the highest disparities in accessibility. Our scenario analysis illustrates the impacts of sidewalks on accessibility disparities among the different groups. We also find that PwMD using fixed-route service are more sensitive to weather conditions and tend to ride transit in the middle of the day rather than during peak hours. Further, the spatial pattern of bus stop usage by PwMD is different than people without disabilities, suggesting their destination choices can be driven by access concerns. During the COVID-19 pandemic, accessibility disparities increased in 2020, and PwMD disproportionately avoided public transit during 2020 but used it disproportionately more during 2021 compared to riders without disabilities. This paper is the first to examine PwMD's transit experience with large high-resolution datasets and holistic analysis incorporating both accessibility and usage. The results fill in these imperative scientific gaps and provide valuable insights for future transit planning. © 2023 Elsevier Ltd
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Natural products, along with food, clothes, and shelter, serve as the basis of treatment since the dawn of human civilization;while the modern medicine has developed over the years by observational and scientific efforts from ancient traditions. Impressive array of bioactivities with minimum or no toxicity was reported with diverse botanicals against several chronic and difficult-to-treat diseases when most synthetic drugs showed unacceptable side effects. A whole range of viral diseases including Dengue, Ebola, drug-resistant Herpes, HIV/AIDS, Japanese Encephalitis, Rabies, SARS, and recent pandemic of SARS Coronavirus-2 need effective prophylactic or therapeutic agents. Considerable research carried out for last few decades on the Pharmacognosy, chemistry;pharmacology and therapeutics of traditionally used medicines of diverse cultures forced most pharmaceutical companies to renew their strategies of drug discovery, from ‘synthetic to green chemistry', against different stages of virus infection cycle or host-virus interaction where no effective vaccine or drugs exist. Thus, plants or phytochemicals having potentials of preventing or inhibiting viral infection cycle need to studied in-depth with the purity, safely and potency including their standardization, isolation, efficacy, mechanism of action, along with adverse effect on the host to reduce the time and cost of drug discovery. This updated review will portray the in-depth scientific knowledge and steps for the development of nature-based solutions against genetically and functionally diverse viral diseases from age-old traditional medicines. © 2022 Elsevier Inc. All rights reserved.
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Purpose: Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption. Design/methodology/approach: The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory. Findings: Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment. Practical implications: The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge. Originality/value: The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems. © 2022, Emerald Publishing Limited.
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The customers use social media platforms to share their grievances and unresolved concerns about a product or service. This behaviour was rampant during the ongoing pandemic, COVID-19. The airline industry could not handle the uncertainties and manage the customer distress. The extant research on how airlines could address social media grievances needs further enrichment. The present paper presents a model of low-cost carriers (LCCs) response to social media customer complaints. It uses content analysis, followed by logistic regression for the model verification. Results highlighted that the type of complainer, emotions, lockdown situation, complain text, and complain concerns can impact the firm’s response. The paper contributes to understanding firms’ responses to social media customer complaints. © 2022, IFIP International Federation for Information Processing.
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Artificial Intelligence (AI) with its highly cognitive features has been increasingly adopted by FinTech firms. With increasing market and economic fluctuations during the unprecedented times of Covid-19, AI offers high computational and easily accessible personalized financial solutions. During the Covid-19 pandemic, customers showed keen interest in AI-assisted financial services. AI in the FinTech industry is now gaining a lot of traction in terms of customer engagement and business prosperity. But with the benefits of availability of consumer data and automation for offering customized and personalized services, the black box effect of AI has a potential dark side affecting both consumers and employees. Lack of human intervention has questioned the accountability and transparency of these financial wealth management solutions that are susceptible to security threats and biased decisions. The purpose of this empirical study is to better understand the adoption of AI in the disruption of the FinTech ecosystem. A mixed approach of focus group and interviews for the purpose of data collection, and qualitative content analysis using natural language processing (NLP) for data analysis have been used to conduct this exploratory study. The findings of the study help to develop an understanding of the social, ethical, and economic consequences of strategic AI adoption for both consumers and businesses. © 2022, IFIP International Federation for Information Processing.
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INTRODUCTION: The American College of Obstetrics and Gynecology (ACOG) recommends screening for depression and anxiety at least once during the perinatal period and again during postpartum checks. The delivery of validated screening tools varies amongst institutions and individual obstetricians. The objectives of this study were to assess our institution's baseline screening rates and the impact of the COVID-19 pandemic on maternal mental health. METHODS: Our patient population was pregnant and postpartum patients at Carilion Clinic from January 2019 to July 2020. Data collected from medical records included scores of the Edinburgh Perinatal Depression Screening (EPDS), Personal Health Questionnaire (PHQ) 2 and 9, demographics, and psychiatric history. Screening rates and incidence of mood disorders were compared between pre- and intra-COVID-19 cohorts. RESULTS: Of the 850 women included, 43.5% (n=370) were screened during perinatal visits and 49.8% (n=424) postpartum. Screenings were completed more frequently during postpartum checks pre-COVID-19 compared to during the pandemic with PHQ-2 (27.4% vs. 16.1%, P=.0001) and PHQ-9 (10.3% vs. 5.4%, P=.011). More women screened positive for depression at perinatal checks during the pandemic compared to pre-pandemic (13.2% vs. 4.7%, P=.0377). CONCLUSION: The COVID-19 pandemic has affected rates of maternal depression screening and has significant mental health impacts on this population. This study reveals baseline rates of screening in perinatal and postpartum visits at our institution, which is critical to delivery of quality care. This information will help inform strategies to increase rates of screening and ensure that mental health needs are being addressed, especially in times of emergency.
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Purpose: Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption. Design/methodology/approach: The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory. Findings: Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment. Practical implications: The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge. Originality/value: The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems. © 2022, Emerald Publishing Limited.
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Coronavirus Disease 2019 (COVID-19) is a respiratory and systemic illness that may progress to severe Acute Respiratory Distress Syndrome (ARDS). There is a pressing need to identify clinical predictors of severe COVID-19 which can help in risk stratification and prognostication. The COVID-19 pandemic tends to have more severe clinical presentation in older age group and in chronic diseases;Chronic Obstructive Pulmonary Disease (COPD) is one of them. COPD is the common cause of high mortality and morbidity worldwide. It is obvious to fear for patients with underlying COPD. Acute episode of exacerbation and COVID-19 pneumonia are the two pivotal differential diagnoses in contemporary era, in patients of COPD presenting with worsening dyspnoea. Mortality rate have been higher among COPD group of patients with the development of hypoxemia. Literature shows that pre-existing COPD worsens the risk of COVID-19 progression and leads to poorer prognosis. Even after recovery from the acute event, proper adherence to maintenance therapy for COPD (inhalational agents) continues to be of paramount importance and remains the standard of care. Because COPD remains a subset that is highly vulnerable for adverse outcomes with COVID-19 infection, preventive therapy should be directed towards-attenuation of contact with droplets, proper hand hygiene and maintenance of adequate nutritional status. The aim of this brief review is to know the burden and impact of COPD on COVID-19 pandemic and challenges in diagnosis and management of COPD patients.
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Purpose: Aligning business innovation with the sustainable development goals (SDGs) creates immense opportunities to solve societal challenges along with business growth and productivity. This study aims to understand the evolution of Fortune firms' strategic addressing of SDG on social media as a step towards post-pandemic recovery. Using attribution theory as a theoretical lens, the authors try to investigate how entrepreneurial orientation (EO) and SDG orientation evolve with the crisis and affect the appreciation and advocacy of the SDG-related posts. Design/methodology/approach: A mixed methodology of machine learning and Social media analytics such as content analysis, sentiment analysis and space–time analysis have been used, followed by multivariate analysis to validate the findings. Findings: An evolution in CEOs’ strategic focus surrounding SDG dimensions was found, from economic in pre-pandemic phase to social and environment during the pandemic. The SDG disclosure on social media by the Fortune CEOs seems to have an influence on their social media reputation, whereas EO has no impact on social media reputation. Research limitations/implications: Wise practice of EO in information diffusion by CEOs on social media may lead to a healthy relationship with the stakeholders and better firm performance. The SDG adoption at organisation level contributes towards a sustainable society and helps tackling the challenges faced during the pandemic. Originality/value: This study analyses the contribution of the Fortune firms to achieve a sustainable society in a pandemic environment by strategic adoption of SDGs and effective use of digital platforms. © 2021, Emerald Publishing Limited.
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Sports watching both through offline as well as online mode has always been fancied by the sports lovers. We investigate the explicit use of social media by sports enthusiasts to show their support and solidarity for their favorite sports team or a particular sportsperson virtually i.e., via e-participation. For experimentation, we have considered the fourth Test match played between India versus Australia from 15–19 January, 2021 during Border-Gavaskar Trophy 2020–2021. During these five days period, a total of 69,965 tweets on Twitter were collected by us favoring both teams. Various statistical techniques coupled with social media analytics such as polarity and emotion analysis have been applied on the collected data to get valuable insights for our results. Our experimental results unambiguously indicate that sports enthusiast globally is using social media as important alternate media to show their support towards their favorite sports team virtually, via e-participation. The emergence and amalgamation of social media and marketing has provided newer horizons to various stakeholders i.e., both viewers and broadcasters to maximize e-participation. © 2021, IFIP International Federation for Information Processing.
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Purpose: Presently, Indian sectors are manifesting a higher level of interdependency and making the economy more vulnerable to human-caused and natural disasters. COVID-19 pandemic creates a devastating effect on the world economy. The Indian economy was expected to lose around ₹ 32,000 crores every day during the first 21 days of complete lockdown. This motivates to conduct the research on how the COVID-19 pandemic affects the port logistics sector and how the effects of COVID-19 on port logistics propagate to other sectors owing to its interconnectedness and affect the economy of the country. Design/methodology/approach: The purpose of the study is analyze how perturbation in one sector can affect the system of interdependent sectors and it is done with interdependency analysis. It uses Wassily Leontief’s inoperability input-output model (IIM) and interval programming (IP) to develop a framework. IP is used to address situations where assumptions are not valid because of uncertainties associated with disruptive events. Findings: The model helps in describing how the effect of the COVID-19 pandemic in port logistics can propagate owing to the interconnectedness across other sectors. The model uses the latest five-year data available on the Organisation for Economic Co-operation and Development database. It uses metrics like inoperability and economic loss to study the consequences of COVID-19 pandemic on various sectors. This study also presents the ranking of the affected sectors based on their inoperability and economic loss Research limitations/implications: In the future study, other techniques like dynamic evolution, multiplex network analysis, analytical hierarchy process, pinch analysis, stochastic evolution and pinch graph could be integrated with input-output (I-O) modelling. Integrated stochastic evolution with an I-O model allows capturing the likelihood of the events;it includes probability distributions instead of point estimates for scenario parameters. Methods like dynamic evolution and multiplex network analysis can be introduced in future work to shed lights on interdependency among the sector, which could potentially provide additional insights for transport policy formulations. Originality/value: This study discusses the theory, methodology and application of the IIM-IP model in the domain of port logistics. The developed IIM-IP model helps decision-makers to manage risk in port logistics. Firstly, it studies how different sectors are interconnected with each other. Secondly, it helps in identifying the most vulnerable sectors based on economic loss and inoperability. Thirdly, it provides the ranking of the sectors based on their economic losses. © 2021, Emerald Publishing Limited.
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Introduction: The barrier method is one of the most effective methods to control the spread of infectious diseases. Objectives: Intubation and extubation are aerosol-generating procedures and to safeguard from getting the infection in a pandemic situation like SARS-COVID19, the aerosol boxes are popular among health care workers. This questionnaire survey was carried out on the anesthesiologist resident doctors working in various medical colleges across India to identify the views of front-line professionals’ on the worth of the aerosol boxes during various procedures. Methods: This survey was conducted on 153 respondents with asking 25 questions regarding various usage of aerosol boxes related to intubation, extubation and sterilization. Gender and experience of more than 10 intubations were sought to find out whether it has any influence on the overall decision making. Statistical analysis was done with SPSS, chi-square tests used for categorical variables. Results: Out of 153 participants 64.5% of respondents were female and 35.5% were males. 49.3% had more than 10 intubation experience with the boxes. Mask ventilation was difficult for 91% and intubation was difficult for 98% of respondents. 90% of respondents were against the use of the box for difficult intubations. More experienced one was in favour of selectively removing the mask while intubation (P<0.001). Use of boxes for extubation and in ICU was better among experienced with P<0.001 and P=0.010 respectively. Patient contamination (54%) and inadequate sterilization (55%) of boxes believed by many as problems related to its use. Conclusions: Aerosol boxes are used by good numbers for mask ventilation and easy intubation, the experienced ones were more comfortable in using them for extubation and ICU procedures, however, sterilization and contamination is an issue to deal with. © IJCRR.
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As the world battles the COVID-19 pandemic, artificial intelligence, epidemiological analysis and novel sensing technologies can play key roles in mitigating the impacts of this unprecedented global crisis. This paper reviews how the domains of deep learning, numerical modelling and bio-sensing have rapidly responded with solutions to this grim pandemic scenario through the development of new methods for early detection and forecasting of the impacts of the COVID-19 virus. The recent applications in the area of deep learning-based computer vision and image analysis tools are discussed which have emerged with promising early COVID-19 detection methods using clinical chest imagery. In addition, a variety of predictive models developed in the current year for estimating the transmission, infection and mortality rates due the novel coronavirus are described which provide crucial information for determining social and governmental measures for containing the viral outbreak. Finally, state-of-the-art clinical test methodologies using nano-level sensors for point-of-care testing practices are highlighted which may enable rapid and accurate diagnosis of the COVID-19 infections. Overall, this paper brings forward some of the most advanced technologies available today and analyses how these may help mankind in defence of the survival challenges posed by the COVID-19 virus. In order to allow readers to further explore the concepts presented in this paper, an open repository named Coro-Lib containing implementations of the computational methods reviewed in this paper is created and described at the end. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Corona virus (COVID-19) outbreaks have severely disrupted the economy, with devastating effects on global trade and it has simultaneously affected households, businesses, financial institution, industrial establishments and infrastructure companies. The economic crisis caused by the virus has hit many more organizations around the world. Similarly, construction and engineering projects around the world have been jeopardize in various way by the COVID-19 pandemic and many projects have closed. As a result, there has been a financial recession in the construction industry in almost all countries and has created unemployment. All in all, this situation has caused great concern, uncertainty and unrest in the construction industry. This paper observes in several countries and describes the global impact of the Corona virus on the construction industry. This paper also explains how it is possible to continue construction work in this situation. If construction work continues, the economic downturn will be reduced and unemployment will be reduced. © 2021 Institute of Physics Publishing. All rights reserved.