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India-one of the world's most densely populated countries is severely affected by the COVID-19 pandemic and has the second largest number of confirmed cases followed by the USA as on September 15, 2020. This chapter analyzes the overall features of the outbreak within the country as well as the micro social impacts caused by the coronavirus in India. Based on thematic content of various newspapers, magazines, and other media reports qualitative analyses, it is possible to understand the country features and social impact of the novel coronavirus pandemic. The first part of the chapter gives a general overview of the outbreak and government responses, and the second section scrutinizes the social impact in relation to micro level socio-economic consequences and epidemiological concerns. In mainstream reports, the impact of COVID-19 outbreak in India has been presented through the macro-economic indicators and emphasis on the negative economic impacts such as decline of growth rate, shrinking Gross Domestic Product (GDP), etc. However, the micro level socio-economic impacts of the outbreak, which are largely caused by the government interventions i.e., lock down, social distancing, etc., persist beyond the statistical number and have spread to every corner of the society. Although statistics revealed that the case fatality rate and death per hundred thousand is relatively low in India compared to other severely affected countries there are reasons beyond the standard epidemiological claims for this trend, reasons which are not properly addressed. This chapter concludes that while, from an epidemiological point of view, India has, thus far, been successful in handing the crisis brought by the global outbreak;however, the social consequences are much larger and need to be taken in consideration before claiming any success. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.
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Background The COVID-19 pandemic has disrupted routine HbA1c testing. This has led to difficulties in monitoring glycaemic control and identifying people with suboptimal glycaemia. Delayed diagnosis of diabetes and suboptimal glycaemic control over extended periods can increase the risk of developing long-term complications of diabetes. The self-collection of capillary blood remotely (at home) for routine HbA1c testing can facilitate monitoring of glycaemic control whilst supporting virtual consultations. The aimof this study was to assess the clinical performance and user acceptance of capillary blood samples prepared remotely using the MiniCollect capillary blood collection device as an alternative to standard venous blood collection for HbA1c analysis. Methods Adult men and women with any type of diabetes were recruited. Following informed written consent, eligible participants provided a venous blood sample at their routine clinic appointment and subsequently prepared a capillary blood sample remotely. Participants also completed a bespoke usability questionnaire. Results Of 84 participants recruited, 62 capillary samples returned to the laboratory, with 41 having a paired venous sample for HbA1c analysis. HbA1c results using both collection methods demonstrated good agreement;Passing-Bablok Regression analysis, y=0 + 1x;R=0.986, Bland-Altman Difference Plot providing a mean difference of 0.3 mmol/mol. Conclusions Over half of participants found the MiniCollect device easy to use. The majority were in favour of the remote capillary blood collection service and would use it if routinely available. The remote self-collection of capillary blood for HbA1c is a convenient alternative for people with diabetes living and working in rural or urban settings ensuring optimal continuance of care.
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Counterfeit and falsified medicines have become a threat to public health around the world. The objective of this review study is to analyze all the relevant studies on preventing or reducing falsified and counterfeit medicines through digital intervention following a Systematic Literature Review (SLR) approach. A total of 51 articles were reviewed from an initial set of 1253 articles following an inclusion-exclusion criterion. As an outcome, this review study found that falsified and counterfeit medicines have become a crucial issue for research and investigation over time. Various advanced technologies (like Blockchain, IoT, RFID, image processing, pattern recognition, etc.) are being used to fight against this issue efficiently. The review also reveals future research opportunities to facilitate the existing initiatives for preventing medicine counterfeit that includes: exploring the implications of emerging technologies;discovering the contaminated point over the medicine supply chain;investigating the less emphasized concern of counterfeit and falsified medicines;exploring all possible use-cases or features of any digital solution to reduce falsified and counterfeit medicines;and the development of counterfeit/ falsified incidents reporting system. Thus, the implication of this study is to discover the research gaps and provide future research directions focusing on the prevention of usage of falsified and counterfeit medicines through the effective use of Information and Communication Technology (ICT). (c) 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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The rapid spread of COVID-19 and subsequent restriction measures become a growing concern for its economic impacts as well. To address it, a study was undertaken to investigate the impacts upon the low-income people employed in the informal sectors in Bangladesh. The data of 372 respondents was collected through a structured questionnaire from the informal sectors in the cities of Dhaka and Chattogram, the most predominant hubs of the country's informal workers. This study covered the period of the first wave of the pandemic in Bangladesh from its first detection (8 March 2020) to the onset of the second wave (February 2021). It was a little over the one year period that had been divided into four-time segments considering as before pandemic (January – March 2020), and during pandemic (1st quartile: April – July 2020;2nd quartile: August – November 2020 and 3rd quartile: December 2020 - February 2021). In the 1st quartile during the pandemic, 65% of respondents' income revealed a sharp decline. This scenario continued in the 2nd and 3rd quartiles with the figure of 35% and 24% respectively. Thus, in each of the three quartiles during pandemic time slots, the majority of respondents' consumption, living standard, schooling, and access to health care facilities were found negatively impacted. By the continuity of time some of the respondents were able to settle them in the new socio-economic condition. Overall, these results indicated several recommendations, including extending basic assistance to these vulnerable groups. © 2021 AESS Publications. All Rights Reserved.
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Introduction: Severe acute respiratory syndrome coronavirus 2 associated pneumonia (COVID-19) is a modern pandemic. Recent evidence suggests that kidney is an important target organ in COVID-19. High concentration of Angiotensin converting enzyme receptors in the proximal tubules make them an early target. Proximal tubular dysfunction (PTD) may act as an early predictor of acute kidney injury (AKI), need for renal replacement therapy (RRT), intensive care unit (ICU) transfer, mechanical ventilation, hospital length of stay (LOS) and death. Method(s): This prospective observational study was conducted in the COVID unit, Bangabandhu Sheikh Mujib Medical University. 87 COVID-19 patients without preexisting kidney disease were screened for markers of PTD on admission. Patients having at least 2 of the 4 defining markers of PTD (inappropriate uricosuria, renal phosphate leak, normoglycemic glycosuria and proteinuria) positive on admission were considered to have PTD. 35 patients with PTD and 35 without PTD were followed up throughout their hospital stay and compared. Result(s): 52.9% of the patients had at least 2 of the 4 defining markers of PTD positive on admission. The most prevalent markers were proteinuria (66.7%), followed by hyperuricosuria (42.5%), renal phosphate leak (28.7%) and normoglycemic glycosuria (20.7%). Also, 67% patients had renal sodium leak and 32.2% patients had renal potassium leak. Mean age was 55.7 years. 50% of the patients were diabetic. The PTD group had significantly lower oxygen saturation and higher parenchymal involvement on HRCT chest, CRP and LDH compared to the non PTD group on admission. 32.9% patients developed AKI during their hospital stay. PTD group had higher odds of developing AKI (odds ratio 17.5 for stage 1, 24.8 for stage 2 and 25.5 for stage 3;p<0.0001). The mean duration of hospital stay was 9 days higher in the PTD group (p<0.001). PTD group also had higher odds of transferring to ICU (OR=9.4, p=0.002), need for mechanical ventilation (OR=10.1, p=0.002) and death (OR=10.3, p=0.001). There was complete recovery of PTD in 32.6% and complete renal recovery in 47.8% of patients during their hospital stay. 26.1% of the patients who developed AKI required hemodialysis. 11.4% of all patients died. Conclusion(s): Proximal tubular dysfunction is highly prevalent in COVID-19 patients very early in the disease and may act as a predictor of AKI, ICU transfer, need for mechanical ventilation and death. No conflict of interestCopyright © 2023
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To cope with global crises, organizations go through various internal changes and adopt different survival strategies. Several researchers and practitioners have highlighted that employees are the key factors in implementing such changes. However, organizations often face difficulties in managing manpower effectively due to the complexities and ambiguities related to the said changes. To address this challenge, the present study proposes a comprehensive model to manage organizational change to effectively respond to global crises. This study highlights that "employee change-championing behavior” (ECB) – also known as effective change-supportive behavior of employees – is the key to successfully implementing the necessary organizational changes to tackle global crises. Utilizing the 3-Stage Lewin's Model of Change as the foundation for analysis, this study proposes for "transformational leadership style” to substitute the "unfreezing stage,” "trust in leadership and work engagement” to substitute the "moving stage,” and "employee change championing behavior” to substitute the "refreezing stage.” Additionally, this study found that transformational leadership (TL) influences employee change-championing behavior, while employee trust in leadership (ETL) influences employee work engagement (EWE). Moreover, trust in leadership and work engagement individually and sequentially mediate the relationship between TL and employee change-championing behavior. This study offers a unique perspective for business leaders on how to manage organizational changes during global crises. © 2022 Wiley Periodicals LLC.
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To cope with global crises, organizations go through various internal changes and adopt different survival strategies. Several researchers and practitioners have highlighted that employees are the key factors in implementing such changes. However, organizations often face difficulties in managing manpower effectively due to the complexities and ambiguities related to the said changes. To address this challenge, the present study proposes a comprehensive model to manage organizational change to effectively respond to global crises. This study highlights that "employee change-championing behavior” (ECB) – also known as effective change-supportive behavior of employees – is the key to successfully implementing the necessary organizational changes to tackle global crises. Utilizing the 3-Stage Lewin's Model of Change as the foundation for analysis, this study proposes for "transformational leadership style” to substitute the "unfreezing stage,” "trust in leadership and work engagement” to substitute the "moving stage,” and "employee change championing behavior” to substitute the "refreezing stage.” Additionally, this study found that transformational leadership (TL) influences employee change-championing behavior, while employee trust in leadership (ETL) influences employee work engagement (EWE). Moreover, trust in leadership and work engagement individually and sequentially mediate the relationship between TL and employee change-championing behavior. This study offers a unique perspective for business leaders on how to manage organizational changes during global crises. © 2022 Wiley Periodicals LLC.
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Introduction: Angiotensin converting enzyme 2 (ACE2) is expressed in several cell types in the body including the gastrointestinal (GI) epithelium. Objective:To provide an overview of the normal distribution of ACE2 in the GI tract, altered ACE2 expression notably in coronavirus infection and its consequences. Materials and Methods: Pubmed and google scholar were searched using the key words ACE2 paired with GI tract, intestinal permeabilty, gut microbiota, inflammatory bowel disease. Results and Discussion: ACE2 is highly expressed in the ileum and colon in human being as well as in rodents. In this current situation of COVID-19 pandemic, downregulation of ACE2 has been reported due to internalization of the ACE2-virus complex within the cells. Although researches are still in infancy in this topic, altered luminal microbiota, increased intestinal permeability, higher level of inflammatory markers and deficient nutrient transport has been reported due to altered ACE2 expression. Conclusion:Altered expression of ACE2 has the possibility to hamper normal physiological function of the GI tract and might affect GI disease progression and prognosis.
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In this paper, we present a framework that automatically labels latent Dirichlet allocation (LDA) generated topics using sentiment and aspect terms from COVID-19 tweets to help the end-users by minimizing the cognitive overhead of identifying key topics labels. Social media platforms, especially Twitter, are considered as one of the most influential sources of information for providing public opinion related to a critical situation like the COVID-19 pandemic. LDA is a popular topic modelling algorithm that extracts hidden themes of documents without assigning a specific label. Thus, automatic labelling of LDA-generated topics from COVID-19 tweets is a great challenge instead of following the manual labelling approach to get an overview of wider public opinion. To overcome this problem, in this paper, we propose a framework named SATLabel that effectively identifies significant topic labels using top unigrams features of sentiment terms and aspect terms clusters from LDA-generated topics of COVID-19-related tweets to uncover various issues related to the COVID-19 pandemic. The experimental results show that our methodology is more effective, simpler, and traces better topic labels compare to the manual topic labelling approach. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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This study was designed to modify the recently developed “Fear of COVID-19” scale (FCV-19S) as a diagnostic criterion and to evaluate its psychometric properties and potential to predict risk of psychological problems. Through an e-questionnaire, data for this study were collected from 1,317 university students from 49 universities in Bangladesh. The modified “Fear of COVID-19” scale (MFCV-19S) showed good internal consistency (ω =.867) and concurrent validity;there was significant association with anxiety and depression. The unidimensionality was confirmed by an acceptable average variance extracted (0.49) and construct reliability (.87). The MFCV-19S differentiates fairly between persons with and without anxiety disorder, using an optimized cut score of ≥ 8 (93% sensitivity and 78% specificity). The multivariate analysis also suggested that MFCV-19S can significantly predict risk of mental health problems. The results indicated that the MFCV-19S is an efficient and valid psychometric tool for screening fear of COVID-19 among students and could be used for general people © Copyright: The Author(s). All articles are licensed under the terms and conditions of the Creative Commons Attribution 4.0 International License (CC-BY 4.0 <http://creativecommons.org/licenses/by/4.0/>)
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Climate diplomacy is the strategy and technique for building and implementing an international environmental framework, which is now one of the leading reasons for deprivation in the Bay of Bengal’s coastal belt. South Asia and the Bay of Bengal Coastal Region are among the highly endangered regions due to climate change impact and natural clamaties, according to the Intergovernmental Panel on Climate Change (IPCC). Southeast Asia will be one of the world’s most vulnerable regions to climate change unless countries make dramatic cuts in greenhouse gas pollution and ensuring to reduce the environmental degration. Global warming poses a threat to food security, hobbles economic growth, prompts political instability, and catalyzes pandemics like Covid-19 severity. The government and policy makers are trying to fix the climate issues and to develop some mitigation strategies but the initiatives are not working well. Because the initiatives are based on the belief that considerable ideological commitment is required at the international, regional, and county level in South Asian nations in order to further enhance awareness of environmental disruption and security and to obtain support for preventative measures. Climate change might have a significant influence in South Asia, and then it will affect regions in different ways depending on how it is perceived spatially and temporally. The region encompasses several different climatic conditions spread over a wide and diverse geographic area. Landscapes in the region include arid areas subject to severe droughts, low-lying coastal areas subject to flooding and coastal erosion, islands whose survival is challenged by the expected sea-level rise, tropical zones subject to increasingly frequent and devastating cyclones, and mountainous ranges affected by the melting of glaciers. Apart from taking early steps for climate change adaptation, South Asian country has enacted any laws or regulations to directly address climate change adaptation. Despite the considerable progress that the Government of Bangladesh and the Bangladeshi people have made, they face continuous challenges associated with climate change. Though the SAARC has taken several initiatives on regional cooperation in the areas relating to climate change that have a bearing on adaptation, India can still play a vital role to develop a smart policy for climate change adaptive capacity in South Asia. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The education sector in Bangladesh has been affected severely by the COVID-19 pandemic crisis like many other countries around the globe. Both the public and private universities faced different types of challenges to continue the teaching-learning process during this time. The chapter has explored these challenges and mitigation strategies based on quantitative and qualitative studies with undergraduate and graduate students of public and private universities. The study has covered both public and privately owned general and engineering universities to explore more specific issues and directives. Moreover, indepth interviews were conducted with teachers to learn the problems they faced and subsequent strategies to cope with the challenges to minimize these challenges and educational loss. The study identified the infrastructural, technical, psychological, health, educational policy, and financial-related challenges faced by key stakeholders. The study incorporated directives to overcome these challenges and provide guidelines for policymakers at home and abroad. © 2021, IGI Global.
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The enormous sway of COVID-19 on the international financial market has been felt across the globe. The financial markets of Bangladesh have also been similarly affected by the global epidemic and experienced a significant increase in volatility. To scrutinise the connection between COVID-19 and the Dhaka Stock Exchange (DSE) indices' return and instability, this study uses data of the DSE from February 2014 to September 2021. A comparative examination of the return and instability of the stock indices of the DSE has also been done considering the outbreak of the current COVID-19 situation. After using the GJR-GARCH (1,1) model, this review uncovers that the outbreak of COVID-19 has a statistically positive noteworthy association with the DSE stock indices' instability, which increases the market's volatility. Traders' fear and the rising frequency of COVID-19 reported patients could cause this. Besides, according to this study, COVID-19 shows a substantial positive linkage with stock market returns that increases the market's return. An appealing valuation, lower interest rates in the banking channel, economic rebound following the closure to prevent coronavirus transmission, improved remittance inflows, and a return of export revenues could all have contributed to this outcome. In addition, the findings also reveal that all market indices are in a mean-reverting phase.
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Over the last decade, corporate networks have undergone significant changes and have been increasingly reliant on cloud-based services to run their businesses. The Covid-19 pandemic has expedited this pattern. In this scenario, there is a need to provide security to infrastructures in an advanced and integrated way. Gartner invented the term "Secure Access Service Edge (SASE)"to meet the above-mentioned goal. SASE is a single framework cloud-native architecture that integrates various network and security functions. SASE is seen as a new cybersecurity solution that impacted established vendors but has received little academic attention. Therefore, in this paper, we present a Multivocal Literature Review (MVLR) aiming to gather an illustration of SASE, including definition, key characteristics, reported benefits and challenges and, finally, critiques of this new term. SASE is adopting the benefits of cloud approaches adding security to the service, however, challenges remain in several setups, including legacy systems. © 2021 IEEE.
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The study was aimed to assess the psychological aspects and relevant factors of the health-care workers (HCWs) working in COVID 19 pandemic condition in Bangladesh. This online cross-sectional survey was conducted from different tertiary, secondary and primary hospitals in Bangladesh. Eligible 638 HCWs who were directly involved in the caring of confirmed or suspected COVID-19 patients were recruited in this study. The mental health was assessed by the Patient Health Questionnare-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Athens Insomnia Scale (AIS). High frequency of depression 536(84.0%), anxiety 386(60.5%) and insomnia 302(47.3%) was found among the HCWs, which were significantly higher in physicians (p<0.001) than nurses. Moderate to severe depression was significantly higher in female, whereas minimal to mild depression was significant in male HCWs (p=0.014). Symptoms of depression (p<0.001), anxiety (p<0.001) and insomnia (p=0.004) were significantly higher among the HCWs of primary and secondary compared to the tertiary level. The HCWs developed psychological trauma due to family health (45.3%) and contagious disease property (66.6%). After adjusting confounders, multivariable logistic regression analysis showed that physicians and HCWs of secondary hospital had significant symptoms of severe depression (OR=2.95, 95% CI=0.50-17.24;p<0.001), anxiety (OR=2.64, 95% CI=0.80-8.72;p<0.001) and insomnia (OR=2.67, 95% CI=1.23-5.84;p=0.018);whereas female HCWs had more risk of developing symptoms of severe insomnia (OR= 1.84;95% CI=1.23-2.75;p=0.003). High rate of depression, anxiety and insomnia was found among HCWs working in the COVID-19 pandemic condition in this survey.
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Covid 19 continues to have a catastrpoic effect on the world, causing terrible spots to appear all over the place. Due to global epidemics and doctor and healthcare personel shortages, developing an AI-based system to detect COVID in a timely and cost-effective method has become a requirement. It is also essential to detect covid from chest X-ray and CT radiographs due to their accuracy in detecting lung infection and as well as to understand the severity. Moreover, though the number of infected people around the globe is enormous, the amount of covid data set to build an AI system is scarce and scattered. In this letter, we presented a Chest CT scan data (HRCT) set for Covid and healthy patients considering a varying range of severity of COVID, which we published on kaggle, that can assist other researchers to contribute to healthcare AI. We also developed three deep learning approaches for detecting covid quickly and cheaply. Our three transfer learning-based approaches, Inception v3, Resnet 50, and VGG16, achieve accuracy of 99.8%, 91.3%, and 99.3%, respectively on unseen data. We delve deeper into the black boxes of those models to demonstrate how our model comes to a certain conclusion, and we found that, despite the low accuracy of the model based on VGG16, it detects the covid spot of images well, which we believe may further assist doctors in visualizing which regions are affected. © 2021 IEEE.
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The emergence of several SARS-CoV-2 variants, especially, the new variant strains B.1.1.7 lineage and 20C/501Y.V2 have highly accelerated the COVID-19 pandemic. A large number of COVID-19 patients are not getting the chance of admitting to the hospitals. Therefore, this pandemic situation accelerates the method of non-contact evaluation of patients along with prediction system of COVID-19 suspects. To feed this interest, a non-contact vital signs monitoring and COVID-19 suspect prediction system is developed. The study can measure heart rate, respiratory rate, and blood oxygen saturation simultaneously using low-cost RGB camera. A predictive model is developed using supervised learning algorithms for predicting the COVID suspect. Among the implemented algorithms, Support Vector Machine ensures a high accuracy of 97.92%. The accuracy of the non-contact vital signs monitoring system is also compared with commercial sensors. Among seven participants, the absolute error (AE) of heart rate was 2.11 for two participants and AE ≤ 4.06 for the other five participants. AE for oxygen saturation was 0.0 for four participants and AE ≤ 1.0 for three participants. Commercially, mean bias for heart rate varies from 2.08 to 8.06 and mean bias for SpO2 is ± 2. The mean bias of the heart rate for this research varies from 2.11 to 4.06 and for SpO2 varies from 0 to 1. Both of them are in a commercially acceptable range. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Due to its geographical condition and geophysical location Bangladesh is one of the world’s most vulnerable country, which will become more vulnerable to the impact of climate change. According to the Global Climate Risk Index 2020 and Intergovernmental Panel on Climate Change (IPCC) 2011, Bangladesh is the seventh most climate change-affected nation in the world. This chapter elaborates on the possible impacts of climate change in Bangladesh through various natural disasters, i.e., increasing temperature, sea level rise, salinity intrusion, cyclone, storm surges, drought, etc. and also discusses the comprehensive disaster management approach in Bangladesh. It is now a worry in the scientific community that climate change could dramatically change weather patterns like the disease spread of epidemics (such as COVID-19) from vulnerable regions to invulnerable regions. All sectors will be affected by the impact of climate change, not only Bangladesh but also other South Asian countries. In Bangladesh, both the government and nongovernmental organizations (NGOs) are trying to prevent and alter the impacts of climate change by enhancing several adaptation and mitigation approaches. But still, coastal districts and northern areas in Bangladesh are facing many climatic issues, such as flash floods, super cyclones, salinity intrusion, storm surges, drought and riverbank erosion etc. Moreover, the government is taking the immediate response of shifting people in a cyclone center at the moment of extreme natural events but most of the peoples of the coastal districts in Bangladesh are illiterate so that they very careless about the awareness. On the basis of current information, it is suggested that the government should make some policy in disaster management for a sustainable solution for coastal areas in Bangladesh. © 2021, SpringerNature Switzerland AG.
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Over years, the voting system has been a democratic way to make a collective decision to express an opinion or selecting a leader. In organizations, voting can occur to elect members of the committee or to choose the roles of candidates. At present, in this era of technological advancement, the voting process became a major issue in order to avoid vulnerabilities like missing votes, multiple voting, and miscount in an election. The manual or semi-automated systems of voting are quite a time consuming, inefficient and unfortunately lack security. Moreover, for COVID-19, physical manual vote taking has become colossal. In this paper, a secure android based mobile voting system named 'mVote' is developed for conducting vote at different institutes and organizations during and post-pandemic situation. The usability and usefulness of the 'mVote' mobile application were evaluated through the System Usability Scale (SUS) which was replicated with 75 participants. The findings of the evaluation study showed that the developed 'mVote' application is usable and will help different organizations and institutes to improve the voting experience during and post-pandemic situation.