The spread of COVID-19 in stock returns along global value chains

This paper examines the performance of industries in the trade network in international stock markets during the onset of COVID-19. In general, the value of all industries in G20 countries declines significantly in the pandemic. Stock returns of industries in the central positions of global value chains exhibit remarkable resilience despite the economic hardship caused by COVID-19. This pattern is more pronounced when the disruptions caused by social distancing requirements are considered. We postulate that this is related to the essential services provided by the central industries.

Does Esg Rating Affect Stock Performance of Indian Companies? An Empirical Study

Purpose: The study tries to investigate the influence of the ESG (environmental, social, and governance) ratings on the stock performance of Indian companies. It further compares the stock performance of those companies that are ESG leaders with Design/Methodology/Approach: The current paper is retrieving the ESG data from a third party to look at the impact of the ESG ratings on the performance of Indian stocks. This is the first study to use a calendar-time approach to assess the impact of 621 ESG rating changes on the stock returns of Indian companies from 2017 to 2022. Findings: The study finds that while an improvement in ESG rating has resulted in statistically significant but unpredictably positive abnormal returns of approximately 0.7% per month, a decline in rating is detrimental to stock performance, resulting in statistically significant monthly risk-adjusted returns of nearly -1.7% on average. Originality/Value: This is one of the primary studies that has investigated the outcome of specialized ESG ratings (improved and declining) on the stock return performance of companies in India.

The mediating role of social connectedness and hope in the relationship between group membership continuity and mental health problems for vulnerable young people

Aims: The DisCOVery study sought to better understand the experiences of young people with complex emerging mental health problems over the longer-term social restrictions related to the COVID-19 pandemic. Following the 'social cure' theory, this study aimed to investigate the association, and potential mechanisms, of group membership continuity and reducing mental ill-health amongst vulnerable young people. Method(s): Cross-sectional survey data from a sample of 105 young people aged 16-35, collected approximately 1 year after the global COVID-19 outbreak (January-July 2021). Correlational and path analyses were used to test the associations between group membership continuity and mental health problems (depression, anxiety, psychotic-like experiences), and the mediation of these associations by hope and social connectedness (in-person and online). Results and Conclusion(s): Prior multiple group memberships were associated with the preservation of group memberships during the COVID-19 pandemic. In-person social connectedness, online social connectedness and hope mediated the relationship between group membership continuity and mental health problem symptoms. The results suggest that clinical and public health practice should support vulnerable young people to foster and maintain their social group memberships, hopefulness and perceived sense of social connectedness as a means to potentially help prevent exacerbated symptoms and promote recovery of mental health problems, particularly during significant life events.

Graph-Based Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction

This study proposes a graph convolutional neural networks (GCN) architecture for fusion of radiological imaging and non-imaging tabular electronic health records (EHR) for the purpose of clinical event prediction. We focused on a cohort of hospitalized patients with positive RT-PCR test for COVID-19 and developed GCN based models to predict three dependent clinical events (discharge from hospital, admission into ICU, and mortality) using demographics, billing codes for procedures and diagnoses and chest X-rays. We hypothesized that the two-fold learning opportunity provided by the GCN is ideal for fusion of imaging information and tabular data as node and edge features, respectively. Our experiments indicate the validity of our hypothesis where GCN based predictive models outperform single modality and traditional fusion models. We compared the proposed models against two variations of imaging-based models, including DenseNet-121 architecture with learnable classification layers and Random Forest classifiers using disease severity score estimated by pre-trained convolutional neural network. GCN based model outperforms both imaging-only methods. We also validated our models on an external dataset where GCN showed valuable generalization capabilities. We noticed that edge-formation function can be adapted even after training the GCN model without limiting application scope of the model. Our models take advantage of this fact for generalization to external data. © 2023 IEEE.

Not to Be Unworthy of the Event: Thinking Through Pandemics with Merleau-Ponty and Deleuze

This chapter examines the phenomenon of pandemics, particularly COVID-19, and attempts to conceptualize the excesses, surprises, and ruptures which epidemics introduce into the human lifeworld. The notion of a pandemic as an event on the personal and social levels requires a twofold investigation, and this chapter uses Merleau-Ponty's philosophy to look at the event structure of the body, and Deleuze's philosophy to think about the event structure of the socio-political world. The event as it unfolds in the body attunes us to the anonymity and generality of the body, its contingency, and the excess of its biological processes beyond human control-an awareness that induces vertigo, nausea, and a pervasive anxiety. The chapter ends with a reflection on what kind of ethics is implied in the COVID-19 pandemic and how we can be changed when we take the moral step and decide "not to be unworthy of what happens to us” (Deleuze G, Logic of sense. Bloomsbury Publishing, London, 2004, 174). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Zero-COVID policy and stock market sectoral performance in China

With the outbreak of COVID-19, the Chinese government implemented the "zero-COVID” policy as a measure to curb the spread of the virus. The different measures of the policy include widespread testing, contact tracing, and strict quarantine and isolation protocols. In view of recent changes in COVID-19 trends and other economic indicators, the Chinese government withdrew significant provisions of the zero-COVID policy in China. The present study investigates the sectoral performance of the Chinese stock market after the withdrawal of the zero-COVID policy. The study considers eighteen sectoral indices of the Shenzhen Stock Exchange of China as a sample and applies the event study methodology to study the impact of the policy withdrawal on the stock prices performance. The results of the study indicate that sectors such as hotel, consumer staples, the financial sector, real estate, media, and culture have reported significant positive movement after the withdrawal of the zero-COVID policy, while other sectors such as consumer discretionary, energy, healthcare, information technology, manufacturing, mining, technology, telecom, transportation, utilities, wholesale, and retail have shown insignificant reactions. These results also indicate that when the COVID-19 outbreak happened in China, different sectors of the economy reacted negatively except the retail and wholesale sectors, while with the withdrawal of the zero-COVID policy by the Chinese government, the reaction of investors is optimistic as different sectors are reporting either positive reactions in the stock price movement or no reaction. © Prashant Sharma, Surender Kumar, 2023.

What counts, safety and security or hygiene? Suggestions on the reopening of major events under pandemic conditions in Germany

PurposeBetween 2020 and spring 2022, health safety was the new pressing concern among the risks at major events. It seemed that it – respectively hygiene as part of infection control – was as important as event safety if an event in Germany was to be approved. Problems aroused in terms of an equal implementation in practice. This article therefore addresses how safety and hygiene aspects interacted during event planning and implementation phases.Design/methodology/approachThe authors draw on qualitative data from a German research project. They use results from eleven semi-structured expert interviews and four field observations at major events. One guiding assumption in the content analysis is that there are major interrelations between event and health safety concepts, which become visible during planning and the implementation of event-related technical, organisational and personal measures.FindingsThe empirical data shows that hygiene is not perceived as an integral part of event safety, but rather as a disconnected pillar beside the "classical” event safety. This is reflected in an imbalanced attention as well as in separate, disintegrated concepts. This disconnectedness leaves room for unwanted interplays between event and health safety as well as potential legitimacy facades.Originality/valueMost studies to date focus on the effectiveness of hygiene concepts and impacts of COVID-19 on the event sector in general without taking a closer look at interactions between event safety and health safety.

Stakeholders' Involvement, Organizational Learning and Social Innovation: Factors for Strengthening the Resilience of Moroccan Cooperatives in the Post-COVID-19 Era

The Moroccan cooperative sector is increasingly important, not only in the social and economic fabric of Morocco, but also in the sustainable development of the Kingdom. With the advent of COVID, the cooperative sector offers more inclusive and sustainable economic alternatives than ever before. In this context, organizational resilience is essential to preserve the sustainability of cooperatives and anticipate potential crises. This study addresses the following issue: What are the organizational factors necessary to strengthen the organizational resilience of the Moroccan cooperative in the Fez-Meknes region in times of COVID-19 crisis? The purpose of this paper was to test the hypothesized relationships between a set of latent constructs (actor involvement and mobilization, organizational learning in times of a crisis and social innovation) and the organizational resilience of cooperatives in times of a COVID-19 crisis. The methodology adopted is structural equation modeling based on the PLS-SEM method under the "SmartPLS Version 3” used on data collected through a printed questionnaire administered to 160 cooperatives in the Fez-Meknes region. The results show the significant and positive influence between the exogenous constructs on the strengthening of organizational resilience of cooperatives as an endogenous construct. The novelty of the study lies in the identification of the organizational resources needed to strengthen the organizational resilience of cooperatives in the Moroccan context. The results show that organizational resilience depends on three selected organizational factors: stakeholder involvement and mobilization, organizational learning in the times of a crisis and social innovation.

EVALUATING THE ETHICAL AND SOCIETAL IMPACTS OF MODELLING PANDEMIC CRISES: EXPERIENCES FROM A WORKSHOP

This paper describes a hybrid (virtual and online) workshop held as part of the EU STAMINA project that aimed to engage project partners to explore ethics and simulation modelling in the context of pandemic preparedness and response. The purpose of the workshop was to consider how the model's design and use in specific pandemic decision-making contexts could have broader implications for issues like transparency, explainability, representativeness, bias, trust, equality, and social injustices. Its outputs will be used as evidence to produce a series of measures that could help mitigate ethical harms and support the greater possible benefit from the use of the models. These include recommendations for policy, data-gathering, training, potential protocols to support end-user engagement, as well as guidelines for designing and using simulation models for pandemic decision-making. This paper presents the methodological approaches taken when designing the workshop, practical concerns raised, initial insights gained, and considers future steps. © SW 2023.All rights reserved

ON THE GREEN: CONSUMER PERCEPTIONS OF RETURNING TO GOLF SPECTATORSHIP AMID THE COVID-19 PANDEMIC

Throughout the COVID-19 pandemic, the sport industry has contended with stoppages of play and interrupted revenue streams. With sport beginning to "return to normal,” there is uncertainty about the safe return of spectatorship and how live-event attendees perceive safety and precautionary measures amid a serious health emergency. The purpose of this study was to assess golf consumers' perceptions of following COVID-19 preventative measures at a small-scale professional golf event in Canada, and how these perceptions may influence their future event attendance. The results from a multiple linear regression analysis indicated that perceived benefits of COVID-19 vaccination and self-efficacy of following preventative measures significantly and positively influenced golf spectator's consideration of attending an event where these measures are enforced, while the perceived barriers of mask wearing significantly and negatively influenced attendance consideration. This has several practical implications for event management practitioners planning and hosting an event amid the COVID-19 pandemic. © Copyright 2023 Cognizant, LLC.

Acute aortic thrombosis in a patient with SARS-CoV-2 coronavirus disease (COVID-19).

One of the rare and life-threatening conditions is acute aortic thrombosis. We have described a case of thrombosis of the aorta and iliac arteries in a patient against the background of viral pneumonia COVID-19, with newly diagnosed diabetes mellitus and arterial hypertension.Copyright © 2021 The authors. All right reserved.

Towards Timeline Generation with Abstract Meaning Representation

Timeline summarization (TLS) is a challenging research task that requires researchers to distill extensive and intricate temporal data into a concise and easily comprehensible representation. This paper proposes a novel approach to timeline summarization using Meaning Representations (AMRs), a graphical representation of the text where the nodes are semantic concepts and the edges denote relationships between concepts. With AMR, sentences with different wordings, but similar semantics, have similar representations. To make use of this feature for timeline summarization, a two-step sentence selection method that leverages features extracted from both AMRs and the text is proposed. First, AMRs are generated for each sentence. Sentences are then filtered out by removing those with no named-entities and keeping the ones with the highest number of named-entities. In the next step, sentences to appear in the timeline are selected based on two scores: Inverse Document Frequency (IDF) of AMR nodes combined with the score obtained by applying a keyword extraction method to the text. Our experimental results on the TLS-Covid19 test collection demonstrate the potential of the proposed approach. © 2023 ACM.

Assessing the Impact of Disruptive Events on Urban Mobility: A Case Study of Chicago Taxis during COVID-19

The rise of Transportation Network Companies (TNCs) over the last decade has significantly disrupted the taxi industry. Studies have shown that taxi ridership has plummeted, and their capacity utilization rates are lower than 50% in five major U.S. cities. Additionally, the COVID-19 pandemic has dealt a severe blow to the already struggling taxi industry. To monitor the evolution of the taxi industry and its impacts on society, our study evaluates changes in the utilization rates, fuel consumption, and emissions among Chicago taxis, using taxi data with rich information on trip profiles from pre-pandemic and pandemic times. Our findings indicate that the taxi utilization rate decreased during the pandemic. While fuel consumption and emissions per kilometer decreased thanks to the reduced traffic during the pandemic, the overall fuel consumption and emissions increased due to increased deadhead travel. The methods developed in this study can be applied to monitor and evaluate the impact of future disruptive events on urban mobility and transportation systems more effectively. By utilizing mobility data to better understand transportation systems, we can develop more efficient, sustainable, and resilient mobility solutions for smart cities. © 2023 ACM.

COVID-19 Bed Management Using a Two-Step Process Mining and Discrete-Event Simulation Approach

The sudden admission of many patients with similar needs caused by the COVID-19 (SARS-CoV-2) pandemic forced health care centers to temporarily transform units to respond to the crisis. This process greatly impacted the daily activities of the hospitals. In this paper, we propose a two-step approach based on process mining and discrete-event simulation for sizing a recovery unit dedicated to COVID-19 patients inside a hospital. A decision aid framework is proposed to help hospital managers make crucial decisions, such as hospitalization cancellation and resource sizing, taking into account all units of the hospital. Three sources of patients are considered: (i) planned admissions, (ii) emergent admissions representing day-to-day activities, and (iii) COVID-19 admissions. Hospitalization pathways have been modeled using process mining based on synthetic medico-administrative data, and a generic model of bed transfers between units is proposed as a basis to evaluate the impact of those moves using discrete-event simulation. A practical case study in collaboration with a local hospital is presented to assess the robustness of the approach. Note to Practitioners—In this paper we develop and test a new decision-aid tool dedicated to bed management, taking into account exceptional hospitalization pathways such as COVID-19 patients. The tool enables the creation of a dedicated COVID-19 intensive care unit with specific management rules that are fine-tuned by considering the characteristics of the pandemic. Health practitioners can automatically use medico-administrative data extracted from the information system of the hospital to feed the model. Two execution modes are proposed: (i) fine-tuning of the staffed beds assignment policies through a design of experiment and (ii) simulation of user-defined scenarios. A practical case study in collaboration with a local hospital is presented. The results show that our model was able to find the strategy to minimize the number of transfers and the number of cancellations while maximizing the number of COVID-19 patients taken into care was to transfer beds to the COVID-19 ICU in batches of 12 and to cancel appointed patients using ICU when the department hit a 90% occupation rate. IEEE

How do the sectoral indices react to COVID-19? Evidence from an emerging economy

The study empirically examines the impact of the COVID-19 on different sectoral indices of the National Stock Exchange (India) using the event study method and a generalised autoregressive conditional heteroskedasticity (GARCH) model. We provide evidence of positive impacts on the auto, oil and gas, healthcare, and pharma sectors. While the bank, financial services, and private bank sectors are the most adversely impacted sectors, the PSU bank, media, and reality sectors are the least impacted, and the rest are moderately impacted sectors. The overall impact of COVID-19 was negative until the implementation of nationwide lockdowns and the announcement of stimulus packages. The GARCH results exhibit more substantial evidence for the negative impact of the pandemic on the FMCG, IT, metal, oil and gas, and PSU bank sectors. We also find a more favourable impact on FMCG, pharma, and healthcare sectors in India.

Association Between COVID-19 Pandemic and Serious Mental Illness: Systematic Review within Salutogenesis Model for Public Health Management

Background: The outbreak of the COVID-19 pandemic, the constant transformation of the SARS-COV-2 virus form, exposure to substantial psychosocial stress, environmental change, and isolation have led to the inference that the overall population's mental health could be affected, resulting in an increase in cases of psychosis. Objective(s): We initiated a systematic review to determine the impact of the SARS-COV-2 virus and its long-term effects-in both symptomatic and asymptomatic cases-on people with or without psychosis. We envisioned that this would give us an insight into effective clinical intervention methods for patients with psychosis during and after the pandemic. Method(s): We selected fifteen papers that met our inclusion criteria, i.e., those that considered participants with or without psychiatric illness and exposed to SARS-COV-2 infection, for this review and were retrieved via Google, Google Scholar, MEDLINE, PubMed, and PsychINFO Database. Key Gap: There is a dearth of research in understanding how COVID-19 affects people with or without a prior personal history of psychosis. Result(s): The systematic review summary provides insight into the state of knowledge. Insights from the systematic review have also been reviewed from the salutogenesis model's perspec-tive. There is moderate evidence of new-onset psychosis during the COVID-19 pandemic in which some antipsychotics treated the psychotic symptoms of patients while treating for COVID-19. Suggestions and recommendations are made for preventive and promotive public health strategies. Conclusion(s): The Salutogenesis model and Positive Psychology Interventions (PPI) provide another preventive and promotive public health management approach.Copyright © 2023 Bentham Science Publishers.

Effectiveness and supply effects of high-coverage rent control policies

Concerns about housing affordability are widespread in cities worldwide, prompting discussions about rent control policies. This paper studies the effects of a rent control policy adopted in Catalonia in 2020 that applied to some but not all municipalities. The policy virtually covered all the rental market and forced ads and tenancy agreements to specify the applicable rent cap to ensure enforcement. To identify the causal effect of the rent control regulation on the rental market, we exploit register microdata of tenancy agreements and implement difference-in-differences regressions and event-study designs. Our results indicate that the regulation reduced average rents paid by about 4% to 6%. We do not find evidence of a reduction in the supply of rental units, as measured by the number of signed and ended agreements or the active stock of rental units. We implement several robustness tests to address identification concerns related to Covid-19. Our results suggest that rent control policies can effectively reduce rental prices without necessarily shrinking the rental market.

Simulation modeling assessment and improvement of a COVID-19 mass vaccination center operations

The development of safe and effective vaccines against COVID-19 has been a turning point in the international effort to control this disease. However, vaccine development is only the first phase of the COVID-19 vaccination process. Correct planning of mass vaccination is important for any policy to immunize the population. For this purpose, it is necessary to set up and properly manage mass vaccination centers. This paper presents a discrete event simulation model of a real COVID-19 mass vaccination center located in Sfax, Tunisia. This model was used to evaluate the management of this center through different performance measures. Three person's arrival scenarios were considered and simulated to verify the response of this real vaccination center to arrival variability. A second model was proposed and simulated to improve the performances of the vaccination center. Like the first model, this one underwent the same evaluation process through the three arrivals scenarios. The simulation results show that both models respond well to the arrival's variability. Indeed, most of the arriving persons are vaccinated on time for all the studied scenarios. In addition, both models present moderate average vaccination and waiting times. However, the average utilization rates of operators are modest and need to be improved. Furthermore, both simulation models show a high average number of persons present in the vaccination center, which goes against the respect of the social distancing condition. Comparison between the two simulation models shows that the proposed model is more efficient than the actual one. [ FROM AUTHOR] Copyright of Simulation is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Stress and resilience in the workers of three health authorities of Emilia-Romagna during the COVID-19 pandemic

Aims: The aim of the present study was to study the prevalence of depression, anxiety, stress, and post-traumatic symptoms in Health-Care Workers (HCWs) of three Health Authorities of Emilia-Romagna, Italy during the COVID pandemic. Material(s) and Method(s): An online questionnaire was spread to the staff of the University Hospital of Modena and the Local Health Agencies of Modena and Romagna, including the Depression Anxiety Stress Scale (DASS-21), the Impact of Event Scale - Revised (IES-R), and the Utrecht Work Engagement Scale - Short Version (UWES-9). The scores at DASS-21 and IES-R were used as dependent variables in multivariate logistic regression models. Result(s): A total of 5868 HCWs were reached (response rate of 22.4%), 76.1% of which were women, mostly aged between 45 and 54 years. Rates of positive scores were: 27.9% DASS-21 Depression;28.4% DASS-21 Anxiety;34.7% DASS-21 Stress;21.9% IES-R. At the multivariate logistic regression, the following were statistically significant risk factors for positive scores: female sex, young age, and working at the front line. An increase in alcohol and tobacco consumption and worsening of eating habits were also strongly associated with symptoms. At UWES-9, the three samples reported lower vigor than dedication and absorption, which are at a medium-high level. Conclusion(s): HCWs have experienced high levels of emotional distress related to the COVID-19 pandemic. Significant improvements are needed not only in terms of organization and distribution of resources, but also in provision of dedicated psycho-social interventions.Copyright © 2023