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In the 21st century, tourism has arisen as the heart and soul of societies, communities and nations across the globe, for the plethora of benefits it carries for the host societies and markets. It has thus, established itself as an endeavor of immense importance facilitating enriched connections, interactions, and transactions at global as well as local levels. However, the coin of tourism has a flip side to it as well, for it has also proved to be a potential catalyst in facilitating the undue spread of coronavirus through the people carrying it, knowingly or unknowingly. Such incidences have led to the generation of stigmatising attitudes towards those who are considered to be the potential carriers of it to varied geographical regions. Stigma is the practice of derogation, exclusion, and avoidance of people deemed dangerous to the affective dynamics of public health and well-being and/or social interactions. Engrossing with the view of social vis-à-vis spatial stigmatisation at tourist destinations. This paper aimed to explore and discuss the notion and consequences of apparent stigma, based on secondary evidence collected from various sources, the perceived condition of tourism in Bihar after the homecoming of people (who are apprehended to be the fomicides of COVID-19). It also seeks to explore the likely consequential effects the tourism industry of Bihar might have to bear in the present state of pestilence, and the challenges that the region would have to overcome in order to re-establish its position in the tourism sector. ©Copyright IJHTS.
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In 2020, the COVD-19 pandemic emerged as the most severe crisis of the century. Several vaccine manufacturing firms have taken the necessary initiatives to combat this problem. However, profitability issues can bring down these firms' vaccine manufacturing efforts, thus leading to lower vaccination coverage. Motivated by this issue, we depict a private COVID-19 vaccine supply chain with a supply chain framework comprising of one vaccine manufacturer and multiple private hospitals under demand uncertainty. We incorporate a Stackelberg game-theoretic approach to demonstrate the collaboration between the vaccine manufacturer and the private hospital using wholesale price, two-part tariff and revenue sharing contracts. We determine the optimal number of vaccines and coordination criteria for each contract. Using a real-life approximation of Indian data, we conduct several numerical studies and facilitate the visual depiction of all the theoretical insights obtained from the model. We also discuss the managerial implications of this study. As per our analysis, when private hospitals procure a higher number of vaccines from the vaccine manufacturer, the two-part tariff contract-based collaboration mechanism yields a win-win situation for both the private hospitals and the vaccine manufacturer and is better than the wholesale price contract.
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We examine the role of firm-initiated social media communication using Twitter in mitigating the negative impact of large-scale disruptions, such as the Covid-19 pandemic, on the shareholder value of firms. We develop our hypotheses using signaling theory and test them using data collected from Twitter and Bloomberg (R). Our data set consists of 121,988 firm-generated tweets from 467 S&P 500 firms collected in March 2020 at the time of the lockdown announcement in the United States. We find that frequent and relevant communication reduces latency and increases the observability of messages, preserving a firm's shareholder value. We also find that a positive outlook and extent of interest from stakeholders results in preserving shareholder value. On average, firms lost about 1.08% of their market value per day (about 9.72% during the 9-day period around the lockdown announcement). Our study contributes to the extant literature in three ways: (1) adds to the literature on disruptions-shareholder value by considering large-scale disruptions such as the Covid-19 pandemic, (2) highlights informational and communication elements of risk management strategy, and (3) adds to the growing body of literature on Twitter by considering firm-generated tweets. The results of our study are of importance to managers as well. For instance, firms tweeted about 57 times per week, and each additional tweet could preserve about $5.85 million of a firm's market valuation, on average. Also, it is not enough that the firms took appropriate actions during a large-scale disruption;they also need to communicate their actions and its implications to their stakeholders effectively. These results can help managers devise their Twitter communication strategy during large-scale disruptions.
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Aim: To evaluate the prevalence of liver dysfunction and its correlation with severity and mortality in patients with Covid-19 infection. Materials and methods: Total 120 patients fulfilled the inclusion criteria were enrolled for the study after giving informed consent and were divided into two groups (moderate and severe Covid-19 infection). Patients were treated as per national guideline for Covid-19 infection as mentioned in flow chart above. Hemogram and Liver function test and inflammatory markers (C-reactive protein, Lactate dehydrogenase, D-dimer and ferritin) were performed on every alternate day of hospitalization. Patients were followed during whole hospitalization course and weekly for 1 month after discharge with these tests. Approval for the study was sought from Institutional Ethical committee. Results: The median levels of ALT, AST, ALP, GGT, LDH, TBIL, DBIL, and albumin were 20 U/L (IQR, 14–31), 20 U/L (IQR, 17–26), 75 U/L (IQR, 55–193), 21 U/L (IQR, 14–36), 198 U/L (IQR, 172–232), 8.4 umol/L (IQR, 6.5–11.3), 3.4 umol/L (IQR, 2.3–4.6), and 45 g/L (IQR, 41–47), respectively. Severe patients had significantly higher levels of ALT (26 vs 20 U/L, p=0.017), AST (31 vs 20 U/L, p < 0.001), GGT (30 vs 21 U/L, p < 0.001), LDH (334 vs 197 U/L, p < 0.001), TBIL (10.2 vs 8.3 umol/L, p=0.029), DBIL (4.9 vs 3.3 umol/L, p < 0.001), but significantly lower albumin (37 vs 45 g/L, p < 0.001) than non-severe patients. Abnormal AST (40% vs 7%, p < 0.001), LDH (90% vs 35%, p < 0.001), DBIL (20% vs 7%, p < 0.001), and albumin (50% vs 8%, p < 0.001) were commonly observed in severe patients, compared with non-severe patients. On multivariate analysis, age >60 years, male gender, BMI > 30 kg/m2, comorbidity, abnormal LDH and albumin on hospital admission, and abnormal peak hospitalization LDH and albumin were associated with progression to severe COVID-19 (OR > 1;p < 0.05). Conclusion: This large sample retrospective cohort study, we described the longitudinal changes of liver function parameters in patients with COVID-19. In addition, we con-firmed patients with abnormal liver function parameters were at increased risk of severe COVID-19 and death.
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Aim: Quantitative Assessment of Interleukin-6 and Ferritin Levels and its Clinical Correlation among COVID-19 Patients. Methods: The cross-sectional analytical study was conducted in the Department of Pathology, Darbhanga Medical College and Hospital, Darbhanga, Bihar, India for 1 year after taking the approval of the protocol review committee and Institutional Ethics Committee. 120 COVID-19 positive patients, diagnosed upon admission by RT-PCR of oropharyngeal swabs with or without respiratory symptoms were included in the study group. Results: Group A had 55 patients among which 7 patients were asymptomatic and 48 had mild symptoms with RR <24/m and SpO2 >94% in room air, the number of patients with co-morbidities like type 2 diabetes mellitus were 15, with hypertension and cardiac disorders were 10 and with respiratory disorders were 5 in Group A, Group B there were 30 patients among which 9 had mild symptoms and 21 patients had moderate symptoms with RR: 24-30/m (or) SpO2: 90%-94% at room air. The mean levels with standard deviation of Serum IL-6 and serum ferritin in Group A, Group B and Group C patients, respectively has depicted in. table 2. On pairwise comparison by Mann-Whitney U test among the groups it shows that the mean IL-6 levels are significantly different in all the three groups. Kruskal Wallis pairwise comparison shows IL-6 levels to be significantly increased in Group C (35) patients with severe disease compared to Group A and Group B patients with mild and moderate disease respectively (p-value <0.001). Serum Ferritin levels did not show any statistically significant difference among Group A, Group B and Group C;however, ferritin levels were markedly increased in Group C patients with severe disease (p-value=0.44). Conclusion: Serum IL-6 levels independently showed a good correlation with disease severity among COVID-19 patients, and serum ferritin levels was elevated only in severely symptomatic individuals with COVID-19 infections. Hence, Serum IL-6 could have a significant role in assessment of disease severity and Prognosis among COVID-19 patients.
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Purpose This study aims to analyze the socio-ecological policy trade-off caused by technological innovations in the post-COVID-19 era. The study outcomes are utilized to design a comprehensive policy framework for attaining sustainable development goals (SDGs). Design/methodology/approach Study is done for 100 countries over 1991-2019. Second-generation estimation method is used. Innovation is measured by total factor productivity, environmental quality is measured by carbon dioxide (CO2) emissions and social dimension is captured by unemployment. Findings Innovation-CO2 emissions association is found to be inverted U-shaped and innovation-unemployment association is found to be U-shaped. Research limitations/implications The study outcomes show the conflicting impact of technological innovation leading to policy trade-off. This dual impact of innovation is considered during policy recommendation. Practical implications The policy framework recommended in the study shows a way to address the objectives of SDG 8, 9 and 13 during post-COVID-19 period. Social implications Policy recommendations in the study show a way to internalize the negative social externality exerted by innovation. Originality/value This study contributes to the literature by considering the policy trade-off caused by innovation and recommending an SDG-oriented policy framework for the post-COVID-19 era.
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The novel Coronavirus or severe acute respiratory syndrome virus or SARS-CoV-2 has spread throughout the world in a very short period. Till date, there is no approved medicine or pharmaceuticals product found to be effective against COVID-19. Sulphated polysaccharides from seaweed possess antiviral, antiinflammatory, anticoagulant, antinociception, antitumor, antiallergic and immunological activities which can be useful to fight Coronavirus COVID-19 pandemic.
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Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), has become an unprecedented public health crisis. To tackle this crisis in an effective way different computational solutions involving artificial intelligence and machine learning have been propounded by researchers across the world. Artificial Intelligence has changed the landscape of the healthcare industry and is being used by many corporations and governments around the world to tackle health care issues and hence, it finds applications in these troubling times as well. The internet specially google scholar scoured for relevant and accurate applications of machine learning and deep learning in solving the issues of this pandemic. The different applications include diagnosis, mortality rate prediction, vaccine development, drug development, sentiment analysis regarding COVID-19 comments and misinformation detection. A systematic study presents the best working models in the respective field. © 2020 IEEE.
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Patients with novel coronavirus disease 2019 (COVID-19) are at significantly increased risk for mortality and morbidity. Current management remains supportive care, ranging from symptomatic outpatient management to full-intensive care support, including intravenous fluids, invasive, and non-invasive oxygen supplementation. In patients with septic shock, treatment with antibiotics and vasopressors are recommended to keep mean arterial pressure (MAP) ≥ 65 mm Hg and lactate < 2 mmol/L. Because of the lack of effectiveness and possible adverse effects, routine corticosteroids should be avoided unless they are indicated for another reason (exacerbation of asthma or chronic obstructive pulmonary disease [COPD], and septic shock in whom fluids and vasopressors do not restore hemodynamic stability). There is currently no sufficient evidence of efficacy of hydroxychloroquine/chloroquine, remdesivir, and other antivirals in the treatment or prevention of COVID-19. Limited evidence shows that COVID-19 convalescent plasma can be used as a treatment of COVID-19 without the occurrence of severe adverse events. Drug regulatory agencies granted an emergency-use authorization of chloroquine/hydroxychloroquine and remdesivir to treat patients when a clinical trial is not available or participation is not feasible. Chloroquine and hydroxychloroquine are associated with QT interval prolongation and life-threatening cardiac arrhythmia in patients with pre-existing cardiovascular disease. Guidelines are issued for use of convalescent plasma in patients with serious or immediately life-threatening COVID-19. Data from several ongoing randomized controlled trials will provide further evidence regarding the safety and efficacy of these drugs for the treatment of COVID-19.