Games in the Time of COVID-19: Promoting Mechanism Design for Pandemic Response

Most governments employ a set of quasi-standard measures to fight COVID-19, including wearing masks, social distancing, virus testing, contact tracing, and vaccination. However, combining these measures into an efficient holistic pandemic response instrument is even more involved than anticipated. We argue that some non-trivial factors behind the varying effectiveness of these measures are selfish decision making and the differing national implementations of the response mechanism. In this article, through simple games, we show the effect of individual incentives on the decisions made with respect to mask wearing, social distancing, and vaccination, and how these may result in sub-optimal outcomes. We also demonstrate the responsibility of national authorities in designing these games properly regarding data transparency, the chosen policies, and their influence on the preferred outcome. We promote a mechanism design approach: It is in the best interest of every government to carefully balance social good and response costs when implementing their respective pandemic response mechanism;moreover, there is no one-size-fits-all solution when designing an effective solution. © 2022 held by the owner/author(s). Publication rights licensed to ACM.

European Sentiment in time of crises. The point of view of young university students

The latest emergencies – economic, refugee, and the pandemic of Covid-19 – has impacted in European collective identity construction, especially in Southern Europe. This article investigates if the pandemic crisis has activated in young Italian and Spanish university students nationalistic or/and European responses. The analysis, based on an online survey, uses the partial least squares structural equation modelling (PLS-SEM) statistical method to perform an exploratory analysis of the explanatory theoretical model of European sentiment. The results show that young people attribute several meanings to Europe during the pandemic, which are based mainly on making informed decisions and recognizing a common space of interaction as an opportunity of peace, security and democracy. The findings highlight the role of EU communicative actions in increasing trust in national and European institutions.

Redesigning Knowledge Management Through Corporate Sustainability Strategy in the Post-Pandemic Era

This study investigates the role of Knowledge Management (KM) in integrating corporate sustainability practices in the post-pandemic context. It also examines the current literature on KM and sustainable development and develops a sustainable conceptual model. Based on a survey of contemporary literature and KM and corporate sustainability approach, this study proposes a conceptual framework with KM and corporate sustainability strategy as fundamental constructs to attain organisational excellence (OE) in the post-pandemic era. The research adds conceptual and situational elements such as the interaction between KM and sustainability strategy, creative approaches for developing a structural framework, and the right direction for boosting efficiency. The research is one of the first to present a comprehensive framework for achieving OE in the post-pandemic era. Furthermore, by focussing on COVID-19 and the post-pandemic environment, this research provides a new perspective on KM and corporate sustainability literature. © 2023 World Scientific Publishing Co.

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

Due to the rapid propagation characteristic of the Coronavirus (COV-ID-19) disease, manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection. Despite, new automated diagnostic methods have been brought on board, particularly methods based on artificial intelligence using different medical data such as X-ray imaging. Thoracic imaging, for example, produces several image types that can be processed and analyzed by machine and deep learning methods. X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines. Through this paper, we propose a novel Convolutional Neural Network (CNN) model (COV2Net) that can detect COVID-19 virus by analyzing the X-ray images of suspected patients. This model is trained on a dataset containing thousands of X-ray images collected from different sources. The model was tested and evaluated on an independent dataset. In order to approve the performance of the proposed model, three CNN models namely MobileNet, Residential Energy Services Network (Res-Net), and Visual Geometry Group 16 (VGG-16) have been implemented using transfer learning technique. This experiment consists of a multi-label classification task based on X-ray images for normal patients, patients infected by COVID-19 virus and other patients infected with pneumonia. This proposed model is empowered with Gradient-weighted Class Activation Mapping (Grad-CAM) and Grad-Cam++ techniques for a visual explanation and methodology debugging goal. The finding results show that the proposed model COV2Net outperforms the state-of-the-art methods. © 2023 CRL Publishing. All rights reserved.

The lived experiences of special education administrators sensemaking during the COVID-19 pandemic

This qualitative narrative study design examined the lived experiences of the challenges special education administrators faced in implementing federal and state guidance during the COVID-19 pandemic. The participants were comprised of special education administrators from a suburban county in New York state. Half of the participants were from a Title I school district. In the spring of 2020, the COVID-19 pandemic caused schools across the country to close their doors, forcing schools to shift to online learning platforms. This left to sudden shifts in the delivery of instruction, leadership, and support, and created logistical challenges for administrators serving students with disabilities. Through qualitative analysis of in-depth interviews and reflective journaling, coding was conducted to discover themes to better understand special education administrators' experiences. The findings from this study supported Karl Weick's sensemaking framework that portrayed the need for an increase in communication, collaboration, and support for staff and student mental health needs. Understanding the lived experiences of special education administrators during this time will help decision making, should another unprecedented challenge occur. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Three-Way Group Decision Making Based on Evidential Reasoning with Probabilistic Linguistic Term Assessments

In consideration of the different importance degrees that may be assigned to all possible linguistic terms, this paper investigates a novel three-way group decision-making method based on the probabilistic linguistic term set (PLTS) information systems. We first construct PLTS information systems based on multiple attributes. Considering the reliabilities of the experts, we determine the weights of the experts by the similarities of the information provided by the expert with regard to other experts. Subsequently, using the evidential reasoning (ER) method, we aggregate the information provided by all experts and obtain the conditional probability of each object. The introduction of the ER rules and the weights of experts successfully solve the problem of conflict between the evaluation information. Then an approach is presented to calculate loss functions and thresholds, which reduces the subjectivity of the decision-making process. Next, the decision result of each object is deduced based on the minimum-loss principle. Finally, a case study about the selection of mask foundries during the COVID-19 is used to demonstrate the effectiveness of our proposed method. And the superiority of our proposed method are proved by comparative analysis. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

A large-scale group decision making method based on spatial information aggregation and empathetic relationships of experts

Large-scale group decision making (LSGDM) involving a large number of experts has attracted more and more scholars' attention. Many LSGDM methods assumed that experts were independent to make evaluations, but the development of social media promotes the communication among experts, which makes experts no longer independent. In addition, existing LSGDM methods mainly adopted aggregation strategies such as the weighted average operator and arithmetic average operator to integrate the opinion of experts in a cluster, which makes the aggregation results cannot reflect the real opinion of the expert group. To address these issues, considering the empathetic network of experts, this study proposes an LSGDM method based on a new aggregation method for expert space information. Firstly, we determine objective weights of experts according to the objective empathetic relationships among experts. Then, the Steiner-Weber point problem is used as a prototype to establish an aggregation method called the spatial optimal aggregation (SOA) method to fuse the spatial information of experts. The model is solved by the genetic algorithm. Finally, an illustrative example about the selection of the most urgent risk in the transportation of COVID-19 vaccines is presented to show the validity and practicability of the proposed model. © 2023 Elsevier Inc.

Decision-making, medical resource allocation and the elderly in the context of COVID-19: An anthropology of and for bioethics

In the context of the COVID-19 pandemic, decision-making practices related to the allocation of medical resources and the treatment of the elderly inform us about the ethics present in the health care setting and at the societal level. The comparison between decision-making in the daily context and the particularity of a pandemic ethics highlights the transition between a non-pandemic ethics and a "pandethics”. The public health ethics approach, particularly utilitarian, has been brought forward in a prominent way in the ethical debates and dilemmas surrounding resource allocation and prioritization. By raising the oppositions and issues associated with age rationing discourses and choices, the question of the treatment of the elderly in the context of COVID-19, and the ageism experienced in this context, emerges. At the same time, difficult ethical decisions and choices are intertwined with the caregiver's duty to care, and therefore the possibility of moral injury. Conflict emerges between ethical decision-making practices and the caregiver's personal or professional values, as the balance between various duties is upset. Alternative approaches and ethics are thus put forward in light of the situations experienced, particularly in the context of long-term care. The thesis developed here aims to support the added value of anthropology to decision-making processes and its more formal integration into well-known approaches in bioethics. Using an anthropological perspective, I conclude by exploring avenues of reflection associated with the ethics of discussion, vulnerability, feminism, or care as other ways of approaching decision-making in the context of a pandemic, at a time when ethical and social reflection is essential. © 2022 University of Montreal. All rights reserved.

Prise de décision, répartition des ressources médicales et personnes âgées en contexte de COVID-19: une anthropologie de et pour la bioéthique

In the context of the COVID-19 pandemic, decision-making practices related to the allocation of medical resources and the treatment of the elderly inform us about the ethics present in the health care setting and at the societal level. The comparison between decision-making in the daily context and the particularity of a pandemic ethics highlights the transition between a non-pandemic ethics and a "pandethics”. The public health ethics approach, particularly utilitarian, has been brought forward in a prominent way in the ethical debates and dilemmas surrounding resource allocation and prioritization. By raising the oppositions and issues associated with age rationing discourses and choices, the question of the treatment of the elderly in the context of COVID-19, and the ageism experienced in this context, emerges. At the same time, difficult ethical decisions and choices are intertwined with the caregiver's duty to care, and therefore the possibility of moral injury. Conflict emerges between ethical decision-making practices and the caregiver's personal or professional values, as the balance between various duties is upset. Alternative approaches and ethics are thus put forward in light of the situations experienced, particularly in the context of long-term care. The thesis developed here aims to support the added value of anthropology to decision-making processes and its more formal integration into well-known approaches in bioethics. Using an anthropological perspective, I conclude by exploring avenues of reflection associated with the ethics of discussion, vulnerability, feminism, or care as other ways of approaching decision-making in the context of a pandemic, at a time when ethical and social reflection is essential. © 2022 University of Montreal. All rights reserved.

The Design and Utilisation of PanSim, a Portable Pandemic Simulator

The COVID-19 pandemic has presented a clear and present need for urgent decision making. Set in an environment of uncertain and unreliable data, and a diverse range of possible interventions, there is an obvious need for integrating HPC into workflows that include model calibration, and the exploration of the decision space. In this paper, we present the design of PanSim, a portable, performant, and productive agent-based simulator, which has been extensively used to model and forecast the pandemic in Hungary. We show its performance and scalability on CPUs and GPUs, then we discuss the workflows PanSim integrates into. We describe the heterogeneous, resource-constrained HPC environment available to us, and formulate a scheduling optimisation problem, as well as heuristics to solve them, to either minimise the execution time of a given number of simulations or to maximise the number of simulations executed in a given time frame. © 2022 IEEE.

Solving the parental CATCH-22: Special masters during times of crisis

The COVID-19 pandemic created a unique catch-22 for families with ongoing parenting cases. By materially changing the circumstances of everyday life while simultaneously closing the courts, the virus placed parents in impossible situations. Sometimes, parents had to decide whether to adhere to parenting schedules and perhaps expose their children to illness or death, or to disobey court orders and potentially expose themselves to possible serious legal penalties. In other parenting cases, the virus allowed opportunistic parents to wrongfully withhold their children while the courts were closed. In either situation, parents often did not qualify for emergency hearings and, even if they did, an unmanageable backlog in court proceedings realistically prevented their cases from being heard. The same pattern was observed in the wake of Hurricane Katrina, and it will logically take place any time a disaster causes legal problems and closes the courts. This article presents national data to reveal the extent to which courts closed during the pandemic and proposes a solution to these catch-22 problems: a system in which states activate special masters to act as mobile or virtual neutral third-party decision-makers. By employing such a system, states would not be exercising any authority that they do not already commonly use, and they would uphold their obligations to families even in difficult times. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Justice-centered education amid the COVID-19 pandemic

The COVID-19 pandemic has brought new saliency to educational efforts to ensure every person is able to make effective personal decisions and participate in civic affairs. However, social and political systems often constrain individual opportunities to enact personal decision-making. These sociopolitical contexts necessitate an increased emphasis on justice-centered education that equips students to recognize and respond to inequities in local and global contexts. In this article, we present three case studies of areas relevant to K-12 education to which the pandemic has drawn critical attention: how scientific knowledge changes, how decisions are made about science-based issues, and how the impacts of such decisions cascade in the environment. Collectively, these cases highlight the importance of justice-centered pedagogies for learning about complex socioscientific issues such as the COVID-19 pandemic and how transboundary justice-centered education could support the meaningful convergence of environmental education, science education, and social studies education. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

How Did We Let This Happen?

Deotto examines whether the illusion of choice begins with actually an illusion or a more nuanced understanding of fate. He details his experience of attending a birthday party where another guest was a magician. They discussed free-choice involving a card trick. He uses the example of the COVID-19 pandemic, specifically in his native Italy, as an illustration of how warnings of disaster are often ignored, a mirror of some sentiments about the climate crisis.

Türkiye'de Büyükşehirlerin Sağlık Turizmi Potansiyellerinin CRITIC ve WASPAS Yöntemleri ile Karşılaştırılması

Ekonomik ve sosyal kalkınma çabalarında gelirlerin çeşitlendirilmesi önemli bir unsurdur. Bu çeşitlilikte önemli bir konumda olan sağlık turizmi, özellikle COVID-19 pandemisinin ardından, daha fazla tartışılmaya başlanmıştır. Bu sebeple ülkelerin alternatif turizm hizmetlerinde çeşitlilik geliştirmeleri de bu doğrultuda zorunluluk haline gelmiştir. Bu kapsamda, Türkiye'de büyükşehirlerin sağlık turizmi potansiyellerini karşılaştırmaya odaklanan bu çalışmada karşılaştırma kriterleri belirlenmiş ve bu kriterlerin ağırlıklandırılması çok kriterli karar verme yöntemlerinden CRITIC ile yapılmıştır. Elde edilen bu ağırlıklar ve kriter değerleri kullanılarak, 30 büyükşehir WASPAS yöntemi ile sıralanmıştır. Sıralama sonuçlarına göre Ístanbul, Antalya, Ankara, Ízmir ve Adana ilk beş sırada yer almıştır. Son sıralarda ise Hatay, Mersin, Mardin, Sakarya ve Şanlıurfa yer almıştır. Bu sonuçlara göre sağlık turizmi alanında bölgesel ve ulusal ölçekte rekabetçiliğe katkı sağlayacağı değerlendirilen stratejik önerilere de yer verilmiştir.Alternate : Diversification of incomes is an important element in economic and social development efforts. Health tourism, which has an important place in this diversity, has started to be discussed more, especially after the COVID-19 pandemic. Therefore, it has become a necessity for countries to develop diversity in alternative tourism services. In this context, in this study, which focuses on comparing the health tourism potentials of metropolitan cities in Turkey, comparison criteria were determined, and the weighting of these criteria was made with CRITIC, one of the multi-criteria decision-making methods. Thirty metropolitan cities were ranked by WASPAS method using these weights and criterion values. According to the ranking results, Istanbul, Antalya, Ankara, Izmir and Adana took the first five places. Hatay, Mersin, Mardin, Sakarya and Şanlıurfa took the last place. According to these results, strategic suggestions that are considered to contribute to regional and national competitiveness in the field of medical health tourism are also included.

Pandemic and insurance purchase: How do people respond to unprecedented risk and uncertainty?

We investigate how people insure themselves against an upsurge of risk and uncertainty during a pandemic. Using high-frequency, city-level insurance purchases data from the largest online insurance platform in China, we employ difference-in-differences strategies to quantify changes in insurance purchases before and after the COVID-19 outbreak relative to a corresponding period in 2019. We show that the pandemic induces a substantial increase in daily number of insurance purchase, with evident impact on both health and life insurance. We demonstrate that the increase mainly originates from an expanded number of consumers;and is not driven by compositional shifts. Particularly, we show that the observed increase is better explained by pandemic risk exposure than other mechanisms such as negative emotions and insurance awareness. Nevertheless, there is a notable discrepancy between changes in insurance purchases and COVID-19 risk exposure, which is driven by individuals' lack of information on pandemic. We find that the more direct and high-quality information people have, the more likely their decisions are to accord with the objective risk exposure. These findings reveal the key driving forces of the risk management responses under an unprecedented pandemic, and point to the importance and necessity of public information disclosure. © 2023 Elsevier Inc.

Making Space for Garbage Cans: How emergent groups organize social media spaces to orchestrate widescale helping in a crisis

During the Covid-19 pandemic, citizens self-organized at an unprecedented scale to support vulnerable people in neighbourhoods, towns and cities. Drawing on an in-depth study of an online volunteering group that emerged at the beginning of the pandemic and helped thousands of people in a city in the United Kingdom, we unpack how citizens co-construct social media spaces to orchestrate helping activity during a crisis. Conceptualizing a novel synthesis of classical garbage can theory and virtual space, we reveal how emergent groups use ‘spatial partitioning' and ‘spatial mapping' to create a multi-layered spatial architecture that distributes decision-making and invites impromptu choice occasions: spontaneous matchmaking, proximal chance connects and speculative attraction. Our insights extend the study of emergent organizing and decision-making in crises. Furthermore, we advance a new line of theorizing which exploits garbage can theory, beyond its existing application in classical decision sciences, to posit a spatial view of organizing that paves the way for its novel applications in organization studies.

The Role of Urban–Rural Connections in Building Food System Resilience

This paper investigates food system resilience—conceptualized through the four dimensions of agency, buffering, connectivity, and diversification—from the perspective of rural–urban relations. We consider three cases that capture distinct actor and policy foci in the wider literature on urban–rural interactions. These are secondary cities and their development potential as central nodes in urban–rural food systems, the role of digital infrastructure in shaping food systems resilience, and finally, street food vendors as a particularly vulnerable yet crucial group of actors linking rural food supply with urban demand. We review existing literature within these themes, with a particular focus on the impact of the COVID-19 pandemic on the food systems in middle- and low-income countries. This allows us to examine the relationship between rural–urban connectivity and food system resilience and to identify possible trade-offs. We formulate recommendations for research and policy around the notions of new localities (i.e., considering the interconnectedness of rural and urban food systems across administrative boundaries), smart development (i.e., context-specific approaches building on local strengths), and network governance (i.e., inclusive decision making engaging with diverse stakeholders across multiple scales). © 2023 by the authors.

Effects of Green Human Resource Management on Innovation Performance through Green Innovation: Evidence from Northern Cyprus on Small Island Universities

The education sector has been severely affected by the global pandemic of COVID-19, and the need for improvement in its aftermath became a challenge for scholars and practitioners alike. The current research focuses on the role of Green Human Resource Management (GHRM) initiatives as an independent variable that is innovation-centric, and improved innovation performance of education sector employees as the dependent variable. GHRM in the current context is described as focusing on environmental aspects within the processes and functions of work in a comprehensive manner that incorporates both resource/waste management and areas of development, as well as green behavior among members. Moreover, the mediating effect of green innovation on the aforementioned relationship and enhancing the role of environmental leadership are examined through a quantitative approach using purposive and convenience sampling techniques. Data from several universities across Northern Cyprus have been gathered with regard to the design, aims, and context of this study. With a total of 187 teachers and administrators from three different universities and using PLS-SEM for analysis, the results show that human resource departments in universities can play a major role in determining the extent of innovation performance within the organization. Green innovation as a mediator can improve the workplace environment, which can be significantly enhanced through an adequate leadership that supports such initiatives (i.e., environmental leadership). The current results can be beneficial for scholars (organizational psychology, innovation, and sustainable HRM), as well as decision-makers in the universities in Northern Cyprus as a small island.

A Multi-Criteria Decision Approach using Divergence Measures for Selection of the Best COVID-19 Vaccine

COVID-19 is a worldwide health threat that has resulted in a significant number of deaths and complicated healthcare management issues. To prevent the COVID-19 pandemic, there is a need to choose a safe and most effective vaccine. Several Multi-criteria Decision-Making (MADM) techniques and approaches have been selected to choose the optimal probable options. The purpose of this article is to deliver divergence measures for fuzzy sets. To validate these measures, some of the properties were also proved. The Multi-criteria Decision-Making method is employed to rank and hence select the best vaccine out of available alternatives. The proposed research allows the ranking of different vaccines based on specified criteria in a fuzzy environment to aid in the selection process. The results suggest that the proposed model provides a realistic way to select the best vaccine from the vaccines available. A case study on the selection of the best COVID-19 vaccine and its experimental results using fuzzy sets are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Asymmetric Differential Privacy

Differential privacy (DP) is attracting considerable research attention as a privacy definition when publishing statistics of a dataset. This study focused on addressing the limitation that DP inevitably causes two-sided errors. For example, consider a threshold query that asks whether a counting is above a given threshold or not. An answer through the DP mechanism can cause error. This phenomenon is not desirable for sensitive analysis such as the counting of COVID-19-infected individuals (in a dataset) visiting a specific location;misinformation can result in incorrect decision-making which can increase the epidemic. To the best of our knowledge, the problem is yet to be solved. We proposed a variation of DP, namely asymmetric DP (ADP) to solve the problem. ADP can provide reasonable privacy protection and achieve one-sided errors. Finally, experiments were conducted to evaluate the utility of the proposed mechanism for the epidemic analysis using a real-world dataset. The results of study revealed the feasibility of proposed mechanisms. © 2022 IEEE.