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This paper provides a comprehensive summary of evidence to explore and position the role of serology testing in the context of coronavirus disease 19 (COVID-19) immunization and policy response in the Asia-Pacific (APAC) region. The document builds on a review of academic literature and existing policies followed by a process of discussion, validation, and feedback by a group of six experts. Six countries and territories—Australia, Hong Kong, India, Indonesia, Thailand, and Taiwan—were sampled to highlight the differing contexts and scenarios in the region. The review includes an overview of (1) the impact of the COVID-19 pandemic, including the emergence of Variants of Concern (VOCs), especially Omicron, (2) the introduction of immunization, (3) the available testing options and potential use of serology testing, (4) the landscape of guidelines and recommendations for their use, and (5) the barriers and challenges to implementing serology testing as a tool to support COVID-19 immunization. Based on the findings, the co-authors propose a set of recommendations to resolve knowledge gaps, to include the use of serology testing as part of the policy response, and to ensure adequate means of implementation. This paper's target audience includes members of the academic community, medical societies, health providers and practitioners, and decision-makers. [ABSTRACT FROM AUTHOR]

Many scholars have understood conspiracy theories as sense-making mechanisms. Among them, a particular strand further inspected them in parallel with religion and magic. This comparison bears the risk of framing conspiracy theories as irrational interpretations and anachronisms with respect to contemporary ways of explaining reality. This contribution takes off from the reflections of those who have highlighted this risk. It tries to confront the possibility of using the concept of enchantment without implying a normative judgment on the irrationality of conspiracy theories. This paper carries out this effort by closely inspecting Max Weber's texts. I argue that Weber's notion of enchantment and disenchantment allows for a punctual use of both, devoid of normative implications. After setting out this non-normative notion of enchantment, this paper examines the characteristics of the enchanted worldview and its usefulness in reading conspiracy theories. Finally, this paper supports this effort using the identified characteristics to systematise a reading of conspiracy-based accounts of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This document discusses the challenges faced in mathematical modeling and controlling COVID-19 epidemics. It highlights the global impact of the pandemic on the economy and health, as well as the uneven effects on different age groups. The availability of vaccines led to mass vaccination campaigns, prompting researchers to implement new strategies and innovative approaches. The document also mentions various journals that have published special issues on COVID-19, covering topics such as forecasting, vaccination strategies, and control measures. The special issue presented in this document consists of eleven papers that analyze clinical characteristics, variant spread, economic recovery, mortality rates, non-pharmaceutical interventions, and coordinated actions. The papers propose mathematical models and control strategies to minimize disease spread and prioritize vaccination. The document emphasizes the multidisciplinary nature of the research, involving fields such as applied mathematics, data science, engineering, biology, and economics. Overall, this special issue provides valuable insights into the mathematical modeling and control of COVID-19 epidemics. [Extracted from the article]

The COVID-19 epidemic has required countries to implement different containment strategies to limit its spread, like strict or weakened national lockdown rules and the application of age-stratified vaccine prioritization strategies. These interventions have in turn modified the age-dependent patterns of social contacts. In our recent paper, starting from the available age-structured real data at the national level, we identified, for the Italian case, specific virulence parameters for a two-age-structured COVID-19 epidemic compartmental model (under 60, and 60 years and over) in six different diseases transmission scenarios under concurrently adopted feedback interventions. An interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19 disease has been accordingly provided. In this paper, which can be viewed as a sequel to the previous one, we mainly apply the same general methodology therein (involving the same dynamic model) to new data covering the three subsequent additional scenarios: (i) a mitigated coordinated intermittent regional action in conjunction with the II vaccination phase; (ii) a super-attenuated coordinated intermittent regional action in conjunction with the II vaccination phase; and (iii) a last step towards normality in conjunction with the start of the III vaccination phase. As a new contribution, we show how meaningful updated information can be drawn out, once the identification of virulence parameters, characterizing the two age groups within the latest three different phases, is successfully carried out. Nevertheless, differently from our previous paper, the global optimization procedure is carried out here with the number of susceptible individuals in each scenario being left free to change, to account for reinfection and immunity due to vaccination. Not only do the slightly different estimates we obtain for the previous scenarios not impact any of the previous considerations (and thus illustrate the robustness of the procedure), but also, and mainly, the new results provide a meaningful picture of the evolution of social behaviors, along with the goodness of strategic interventions. [ABSTRACT FROM AUTHOR]

The development of antimicrobial polymeric materials has evolved into one of the more promising methods for preventing the growth of microbes and mitigating the spread of infectious diseases in several applications including the health and food packaging sectors. The outbreak of global pandemics, and particularly the recent COVID-19 pandemic, further strengthen the importance of developing such solutions. This review paper presents a fundamental understanding of how antimicrobial polymers are developed, describes the possible surface modification approaches to render polymers with antimicrobial properties, highlights the potential mechanism of action against a range of microorganisms (bacterial, viral, and fungal), and details some of the international standard protocols and procedures to evaluate the antimicrobial properties of modified materials (such as plastics and textiles). In addition, this review paper discusses the toxicity of antimicrobial additives when used in healthcare and food packaging applications. [ABSTRACT FROM AUTHOR]

As the proliferation of new variations of COVID-19 (Coronavirus Disease 2019) continues to increase, it is evident that the COVID-19 pandemic is not over. Indeed, we are living in a world of interrelating and overlapping pandemics—a syndemic. A syndemic accelerates the polarization of access to health care, financial support, and education opportunities in marginalized communities, and the polarization breeds social injustice, violence, and ignorance. What, then, is the Gospel the Church proclaims for those who have experienced the pandemic and are now facing a syndemic? As part of a liturgical response, this paper proposes preaching as a praxis of the ecclesiological Gospel. The ecclesiological Gospel is a term I suggest to highlight the contextual, sacramental, and communal aspects of the Gospel. Highlighting God's holistic work for salvation represented in baptism and the eucharist, the ecclesiological Gospel yearns to form a church that baptizes people in diversity, that severs evil interconnections, and that welcomes people to the table of hospitality that forms a new covenantal relationship. This paper examines the concept of a syndemic and its significance for preaching in marginalized communities. It contrasts a holistic Gospel perspective with a narrow view, proposes preaching as praxis of the ecclesiological Gospel, and illustrates its application within a particular context in responding to syndemic conditions. I hope this work offers a chance to reorient the meaning of the Gospel and the identity of the Church for people living in fear, grief, and hopelessness, while encouraging them with the unwavering hope revealed in Christ's suffering, death, and resurrection. [ABSTRACT FROM AUTHOR]

Background/Objectives: Patients with acute coronary syndrome (ACS) represent a vulnerable population. We aimed to investigate serum lipid levels of patients with ACS upon admission and during one year of the COVID-19 pandemic in a rural county hospital, and compared these findings with the data of patients with ACS in 2015 and 2017. The secondary aim of this paper was the comparison of the LDL-C values calculated with the Friedewald and Martin–Hopkins methods. Methods: A retrospective analysis of lipid-lowering data of patients treated with ACS in 2015, 2017 and in a COVID-19 year (1 April 2020–31 March 2021) was performed; the patient's numbers were 454, 513 and 531, respectively. Results: In the COVID-19 period one year after the index event, only 42% of the patients had lipid values available, while these ratios were 54% and 73% in 2017 and in 2015, respectively. Using the Friedewald formula, in the COVID-19 era the median of LDL cholesterol (LDL-F) was 1.64 (1.09–2.30) mmol/L at six months and 1.60 (1.19–2.27) mmol/L at one year, respectively. These values were 1.92 (1.33–2.27) mmol/L and 1.73 (1.36–2.43) mmol/L using the Martin–Hopkins method (LDL-MH). The LDL-F yielded significantly lower values (15% lower at six months, p = 0.044; and 8% lower at one year, p = 0.014). The LDL-F reached the previous target of 1.8 mmol/L during the COVID-19 pandemic 36% at one year vs. 48% in 2017, and 37% in 2015. The recent target LDL-C level of 1.4 mmol/L was achieved in 22% of cases in the COVID-19 pandemic, 16% in 2015 and 19% in 2017. Conclusions: A significantly lower proportion of patients with ACS had available lipid tests during the COVID-19 pandemic. Besides the lower number of available samples, the proportion of achieved 1.4 mmol/L LDL-C target lipids was stable. More rigorous outpatient care in the follow-up period may help to improve the quality of lipid lowering treatments and subsequent secondary cardiovascular prevention. If direct LDL-C determination is not available, we prefer the LDL calculation with the Martin–Hopkins method. [ABSTRACT FROM AUTHOR]

In this paper, we construct an infectious disease model with a testing compartment and analyze the existence and stability of its endemic states. We obtain the basic reproduction number, R 0 , and demonstrate the existence of one endemic equilibrium without testing and one endemic equilibrium with testing and prove their local and global stabilities based on the value of the basic reproduction number, R 0 . We then apply our model to the US COVID-19 pandemic and find that, for a large parameter set, including those relevant to the SARS-CoV-2 virus, our analytic and numerical results suggest that the trajectories will be trapped to the testing-free state when the testing number is small enough. This indicates that the pandemic may end with a testing-free endemic state through a novel and surprising mechanism called stochastic trapping. [ABSTRACT FROM AUTHOR]

Accurately predicting the pairing order of bases in RNA molecules is essential for anticipating RNA secondary structures. Consequently, this task holds significant importance in unveiling previously unknown biological processes. The urgent need to comprehend RNA structures has been accentuated by the unprecedented impact of the widespread COVID-19 pandemic. This paper presents a framework, Knotify_V2.0, which makes use of syntactic pattern recognition techniques in order to predict RNA structures, with a specific emphasis on tackling the demanding task of predicting H-type pseudoknots that encompass bulges and hairpins. By leveraging the expressive capabilities of a Context-Free Grammar (CFG), the suggested framework integrates the inherent benefits of CFG and makes use of minimum free energy and maximum base pairing criteria. This integration enables the effective management of this inherently ambiguous task. The main contribution of Knotify_V2.0 compared to earlier versions lies in its capacity to identify additional motifs like bulges and hairpins within the internal loops of the pseudoknot. Notably, the proposed methodology, Knotify_V2.0, demonstrates superior accuracy in predicting core stems compared to state-of-the-art frameworks. Knotify_V2.0 exhibited exceptional performance by accurately identifying both core base pairing that form the ground truth pseudoknot in 70% of the examined sequences. Furthermore, Knotify_V2.0 narrowed the performance gap with Knotty, which had demonstrated better performance than Knotify and even surpassed it in Recall and F1-score metrics. Knotify_V2.0 achieved a higher count of true positives (tp) and a significantly lower count of false negatives (fn) compared to Knotify, highlighting improvements in Prediction and Recall metrics, respectively. Consequently, Knotify_V2.0 achieved a higher F1-score than any other platform. The source code and comprehensive implementation details of Knotify_V2.0 are publicly available on GitHub. [ABSTRACT FROM AUTHOR]

In the development of an inactivated virus vaccine, the isolation of a single virus strain plays a key role in determining potency. The conventional methods of quantification of virus number are mainly based on virus titers, which are subjective and time-consuming, especially in the early stage of virus isolation, in which the titer difference is weak. Previous reports have shown a high correlation between the spike protein and the potency of COVID-19 vaccines. In this paper, we report a novel, fast, and convenient method of screening an Omicron virus strain by quantifying the spike protein content, where the isolated strain shows high affinity to Omicron-specific antibodies and a high titer, and it can induce high levels of neutralization antibodies. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has placed enormous pressure on healthcare systems. In the first line of the "war" against the virus, hospitals tried to maintain their general operations, while supplementing their services with COVID-19 patient care. To tackle the new difficulties, hospitals had to develop strategic response plans, and were in need of finding the most effective management structure for their institution. The focus of this paper is the aforementioned management structures. After overviewing the international literature, we identified three different approaches and we named them the Horizontal, Vertical, and Intermedier Approach. The separation is based on the following features: decision making, information distribution, command forwarding, intra-hospital communication channels, hierarchy, and control. After summarizing the international experiences, we introduce a Hungarian centrum hospital's approach, as the institution was assigned to fulfil COVID-19 centrum hospital duties in the middle of the first wave. The North-Buda Szent János Central hospital was in need of restructuring their management structure, and the leadership decided to transform it into a hierarchical, vertical structure, operating with centralized decision making and personal control. This control–command system idea came from the hospital's Internist Head Coordinator Physician, who is the first author of our article, and had serious military medicine experiences (in Afghanistan). [ABSTRACT FROM AUTHOR]

By integrating energy-efficient AIoT-based biosensor networks, healthcare systems can now predict COVID-19 outbreaks with unprecedented accuracy and speed, revolutionizing early detection and intervention strategies. Therefore, this paper explores the rapid growth of electronic technology in today's environment, driven by the proliferation of advanced devices capable of monitoring and controlling various healthcare systems. However, these devices' limited resources necessitate optimizing their utilization. To tackle this concern, we propose an enhanced Artificial Intelligence of Things (AIoT) system that utilizes the networking capabilities of IoT biosensors to forecast potential COVID-19 outbreaks. The system aims to efficiently collect data from deployed sensor nodes, enabling accurate predictions of possible disease outbreaks. By collecting and pre-processing diverse parameters from IoT nodes, such as body temperature (measured non-invasively using the open-source thermal camera TermoDeep), population density, age (captured via smartwatches), and blood glucose (collected via the CGM system), we enable the AI system to make accurate predictions. The model's efficacy was evaluated through performance metrics like the confusion matrix, F1 score, precision, and recall, demonstrating the optimal potential of the IoT-based wireless sensor network for predicting COVID-19 outbreaks in healthcare systems. [ABSTRACT FROM AUTHOR]

Definition: The history of women archaeologists in Portugal and their contribution to the development of the discipline is yet to be studied. However, in recent years, some articles published in Portugal have contributed to the construction of this history. Some of these are from the year 2020, and although the coronavirus pandemic has affected the progress of these investigations, especially regarding fieldwork. Generally, these are quantitative studies based on the number of publications by women archaeologists and their references and interviews in newspapers. These articles, which require significant time for database analysis, have not yet explained the existing gaps. It is not the scope of this paper to pursue this quantitative scope; instead, it intends to conduct a qualitative analysis of the contribution of women archaeologists to the development of prehistoric studies in Northern Portugal. To achieve this goal, we are focusing on analysing the doctoral theses developed by women concerning pre- and proto-historic archaeology in Northern Portugal. With this evaluation, we intend to contribute to the history of Portuguese women's archaeology and, at the same time, highlight their methodological and conceptual achievements. [ABSTRACT FROM AUTHOR]

Air conditioning systems can play a positive or negative role in the spread of COVID-19 infection. The importance of sufficient outdoor air changes in buildings was highlighted by the World Health Organization, therefore these should be guaranteed by mechanical ventilation systems or adequate air conditioning systems. The proposed case study concerns the optimal number of outdoor air changes to limit COVID-19 contagion for a school building in Central Italy. The Wells–Riley model is used to assess the risk of airborne infection, while energy consumption is calculated by a dynamic energy simulation software. The scope of the paper offers an innovative method to define the optimal ventilation strategy for the building's HVAC system design to reduce the risk of infection with limited increases in energy consumption and greenhouse gas emissions. Results show that the desirable approach is the one in which the same low value of contagion risk is set in all rooms. This new approach results in significant energy savings, compared to the most common ones (setting the same high outdoor air rates for all rooms) to counteract the risk of infection. Finally, the zero-emission building target is verified by introducing a suitable photovoltaic system to offset pollutant emissions. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic disrupted public health and economies worldwide. In this paper, we investigate an optimal control problem to simultaneously minimize the epidemic size and control costs associated with intervention strategies based on official data. Considering people with undetected infections, we establish a control system of COVID-19 with time-varying parameters. To estimate these parameters, a parameter identification scheme is adopted and a mixed algorithm is constructed. Moreover, we present an optimal control problem with two objectives that involve the newly increased number of infected individuals and the control costs. A numerical scheme is conducted, simulating the epidemic data pertaining to Shanghai during the period of 2022, caused by the Omicron variant. Coefficient combinations of the objectives are obtained, and the optimal control measures for different infection peaks are indicated. The numerical results suggest that the identification variables obtained by using the constructed mixed algorithm to solve the parameter identification problem are feasible. Optimal control measures for different epidemic peaks can serve as references for decision-makers. [ABSTRACT FROM AUTHOR]

The International Conference on Sports Concussion, held every four years since 2001, has been instrumental in forming the international consensus on sports-related concussions. However, due to the unprecedented global pandemic of COVID-19, not only the Tokyo Olympics 2020, but also the initially scheduled sixth conference was postponed multiple times. Finally, the 6th International Conference on Sports Concussion took place in Amsterdam at the end of October 2022. In July 2023, the Amsterdam Declaration, reflecting the outcomes of this sixth conference, was released. This paper provides an overview of the conference, in which significant updates were revealed and introduced, including revisions to the definition of sports-related concussions, as well as the latest version of the Sports Concussion Assessment Tool (SCAT), known as SCAT6, the Office Assessment Tool (SCOAT), and the updated staged return-to-play protocol. [ABSTRACT FROM AUTHOR]

In this paper, an SEAI epidemic model with asymptomatic infection is studied under the background of mass transmission of COVID-19. First, we use the next-generation matrix method to obtain the basic reproductive number R 0 and calculate the equilibrium point. Secondly, when R 0 < 1 , the local asymptotic stability of the disease-free equilibrium is proved by Hurwitz criterion, and the global asymptotic stability of the disease-free equilibrium is proved by constructing the Lyapunov function. When R 0 > 1 , the system has a unique endemic equilibrium point and is locally asymptotically stable, and it is also proved that the system is uniformly persistent. Then, the application of optimal control theory is carried out, and the expression of the optimal control solution is obtained. Finally, in order to verify the correctness of the theory, the stability of the equilibrium point is numerically simulated and the sensitivity of the parameters of R 0 is analyzed. We also simulated the comparison of the number of asymptomatic infected people and symptomatic infected people before and after adopting the optimal control strategy. This shows that the infection of asymptomatic people cannot be underestimated in the spread of COVID-19 virus, and an isolation strategy should be adopted to control the spread speed of the disease. [ABSTRACT FROM AUTHOR]

Due to immunosuppression, transplant recipients are at higher risk of infections with SARS-CoV-2 and worse clinical outcomes than immunocompetent hosts. Furthermore, lung transplant patients represent a special group among solid organ recipients, since pneumonia is the main manifestation of COVID-19. However, data on the course of disease and the changes in morbidity and mortality during the course of the pandemic are limited. In our pulmonary rehabilitation clinic, we treat patients shortly after lung transplant as well as long-term transplant patients. Over the last almost 4 years of pandemic, we witnessed several COVID-19 infections in lung transplant patients in our clinic as well as patients who acquired an infection beforehand. In this paper, we aim at retrospectively describing a series of recent COVID-19 cases in our clinic, looking at the clinical course of disease and outcomes in lung transplant patients. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has resulted in millions of fatalities worldwide. The case of pediatric cancer patients stands out since, despite being considered a population at risk, few studies have been carried out concerning symptom detection or the description of the mechanisms capable of modifying the course of the COVID-19 disease, such as the interaction and response between the virus and the treatment given to cancer patients. By synthesizing existing studies, this paper aims to expose the treatment challenges for pediatric patients with COVID-19 in an oncology context. Additionally, this updated review includes studies that utilized the antiviral agents Remdesivir and PaxlovidTM in pediatric cancer patients. There is no specific treatment designed exclusively for pediatric cancer patients dealing with COVID-19, and it is advisable to avoid self-medication to prevent potential side effects. Managing COVID-19 in pediatric cancer patients is indeed a substantial challenge. New strategies, such as chemotherapy application rooms, have been implemented for children with cancer who were positive for COVID-19 but asymptomatic since the risk of disease progression is greater than the risk of complications from SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Several research papers have attempted to describe the dynamics of COVID-19 based on systems of differential equations. These systems have taken into account quarantined or isolated cases, vaccinations, control measures, and demographic parameters, presenting propositions regarding theoretical results that often investigate the asymptotic behavior of the system. In this paper, we discuss issues that concern the theoretical results proposed in the paper "An Extended SEIR Model with Vaccination for Forecasting the COVID-19 Pandemic in Saudi Arabia Using an Ensemble Kalman Filter". We propose detailed explanations regarding the resolution of these issues. Additionally, this paper focuses on extending the local stability analysis of the disease-free equilibrium, as presented in the aforementioned paper, while emphasizing the derivation of theorems that validate the global stability of both epidemic equilibria. Emphasis is placed on the basic reproduction number R 0 , which determines the asymptotic behavior of the system. This index represents the expected number of secondary infections that are generated from an already infected case in a population where almost all individuals are susceptible. The derived propositions can inform health authorities about the long-term behavior of the phenomenon, potentially leading to more precise and efficient public measures. Finally, it is worth noting that the examined paper still presents an interesting epidemiological scheme, and the utilization of the Kalman filtering approach remains one of the state-of-the-art methods for modeling epidemic phenomena. [ABSTRACT FROM AUTHOR]

The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and the world economy. The pervasive presence of illness, uncertainty, and fear has markedly diminished overall life satisfaction. Consequently, sentiment analysis has gained substantial traction among scholars seeking to unravel the emotional and attitudinal dimensions of this crisis. This research endeavors to provide a bibliometric perspective, shedding light on the principal contributors to this emerging field. It seeks to spotlight the academic institutions associated with this research domain, along with identifying the most influential publications in terms of both paper volume and h-index metrics. To this end, we have meticulously curated a dataset comprising 646 papers sourced from the ISI Web of Science database, all centering on the theme of sentiment analysis during the COVID-19 pandemic. Our findings underscore a burgeoning interest exhibited by the academic community in this particular domain, evident in an astonishing annual growth rate of 153.49%. Furthermore, our analysis elucidates key keywords and collaborative networks within the authorship, offering valuable insights into the global proliferation of this thematic pursuit. In addition to this, our analysis encompasses an n-gram investigation across keywords, abstracts, titles, and keyword plus, complemented by an examination of the most frequently cited works. The results gleaned from these endeavors offer crucial perspectives, contribute to the identification of pertinent issues, and provide guidance for informed decision-making. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected nearly all strata of life, including scientific activities. Implementation of nationwide lockdowns, closures of universities, and other measures significantly limiting social mobility precluded field and laboratory research from being pursued at a pre-pandemic pace. On the other hand, working from home could translate into higher productivity of researchers in terms of publication output, ultimately affecting the journals' metrics. This effect has been well evidenced in the biomedical field, but whether it also occurred in aquatic sciences has not been explored. Therefore, this study aimed to analyze and compare various metrics of journals classified in the Scopus evaluations in 2019 (encompassing 2016–2019, the pre-pandemic period) and 2022 (covering 2019–2022, the pandemic period) within three subjects: aquatic science, oceanography, and water science and technology. In general, the number of journals classified into the considered categories increased in 2022 by 12%, and the majority (78%) experienced an increase in the CiteScore metric. The total published articles and received citations also significantly increased in 2022 by 17.5% and 63.5%, respectively, and were even higher in the case of open access journals—69% and 145%, respectively. The overall share of cited articles in the considered period was higher by 5% than in the 2019 Scopus evaluation and by 7% in the case of open access periodicals. However, source normalized impact per paper (SNIP) and the SCImago journal rank (SJR) values decreased by 7% and 8%, respectively. The highest share of citations was generated by Water Research, Water, and the Journal of Hydrology, and the highest number of articles was published by Water, Frontiers in Marine Science, and Desalination and Water Treatment. Only five of the COVID-19-related papers published in journals with the highest CiteScore and total number of citations received more than 200 citations, but their contribution to citations received by the journals was not high. In summary, the present study's findings indicate the high potential of the field dedicated to water sciences to adapt in a period challenged by an infectious disease pandemic. However, they do not exclude the adverse effect that this period could have on the activities of individual scientists and research teams. [ABSTRACT FROM AUTHOR]

With the renewed focus on indoor air quality (IAQ) due to "Sick building syndrome" and the recent COVID-19 pandemic, the availability of innovative components and innovative guidance for maintenance and systemic safety design will play an important role, with HVAC systems as protagonists. UV-C irradiation has been investigated for a long time, and some system solutions are known. The aim of this work is to provide an overview of the latest outcomes related to the innovative components of HVAC systems using UV-C irradiation and investigate the current state of the art. A procedure based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was adopted, and the Scopus database was used to query the relevant literature. A total of 66 publications qualified for inclusion in the survey: 29 articles report experimental investigations, 24 articles are related to numerical or theoretical analysis, and both approaches were used in 13 articles. Many papers deal with upper-room UVGI, AHUs, and ducts. A few papers analyse mobile devices. The evaluation of the dose, as in the case of the definition of irradiance, is reported in a small number of articles. This lack of information makes the scenario imprecise and non-quantitative. [ABSTRACT FROM AUTHOR]

This paper charts the journey from classroom-based training delivery to hybrid and virtual learning opportunities used to overcome the challenges imposed by public health restrictions introduced in response to the COVID-19 pandemic. The public health measures introduced in March 2020 had a significant effect on the ability of the Children First Information and Advice Service (CFIAS), in Tusla, Ireland's Child and Family Agency, to deliver services. One of the key tools used by the CFIAS to support understanding of responsibilities, and best practice, in child safeguarding by professionals, and within organisations, has been the provision of direct training and information sessions. The introduction of public health restrictions necessitated a complete rethink by the CFIAS on how child safeguarding training and information are delivered. The paper presents an outline of the background and context of child safeguarding in Ireland, followed by a description of some of the challenges experienced by the CFIAS in response to the pandemic public health restrictions. It includes discussion on strategies and solutions considered to overcome these challenges. There is further discussion on the tools and methods eventually used, followed by a reflection on lessons learned by the CFIAS in areas including training delivery and methodology, eLearning, and information provision. The paper provides an analysis of limited qualitative and quantitative data, as well as a reflection on the lived experience of the CFIAS team members responding to the challenges posed during this time period, rather than a preplanned research study on pedagogical approaches in adult learning. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the journal Brain Sciences titled "Neurological and Psychiatric Disorders in the COVID-19 Era." The issue aims to expand knowledge about the impact of COVID-19 on neurological and psychiatric disorders and how the outbreak has affected their management. The issue includes six original scientific papers. One study found an association between pulmonary embolism in COVID-19 patients and neurological complications such as stroke and seizures. Another study reviewed the possible mechanisms of SARS-CoV-2 damage in the body, including neurological disorders. A systematic review identified risk factors for depressive symptoms during COVID-19-related restrictions. Another study evaluated long-term neuropsychiatric sequelae in COVID-19 survivors and found that a significant portion still experienced symptoms. A review focused on the impact of COVID-19 on neurology training, and the final paper examined emotional distress in COVID-19 patients admitted to a rehabilitation unit. The special issue aims to provide new insights for future research initiatives. [Extracted from the article]

Chronic rhinosinusitis (CRS) is a highly prevalent disease and up to 83% of CRS patients suffer from olfactory dysfunction (OD). Because OD is specifically seen in those CRS patients that present with a type 2 eosinophilic inflammation, it is believed that type 2 inflammatory mediators at the level of the olfactory epithelium are involved in the development of this olfactory loss. However, due to the difficulties in obtaining tissue from the olfactory epithelium, little is known about the true mechanisms of inflammatory OD. Thanks to the COVID-19 pandemic, interest in olfaction has been growing rapidly and several studies have been focusing on disease mechanisms of OD in inflammatory conditions. In this paper, we summarize the most recent data exploring the pathophysiological mechanisms underlying OD in CRS. We also review what is known about the potential capacity of olfactory recovery of the currently available treatments in those patients. [ABSTRACT FROM AUTHOR]

Losing a child is a traumatic event, disrupting life's natural cycle, profoundly affecting the family system, and causing enduring grief. Perinatal death, including ectopic pregnancies, miscarriages, stillbirths, and neonatal deaths, exacerbates this distress. Additionally, the COVID-19 pandemic has challenged healthcare systems and supporting services available to individuals in need. Thus, this research explores experiences of parents facing perinatal loss in 2020–2021, further focusing on the pandemic's impact. Using a mixed-methods design with self-reports and qualitative interviews, this paper presents results from the quantitative protocol, involving an update and follow-up of a previous study. It compares measurements across scales: COVID-19: The Impact of Event Scale-Revised; The Prolonged Grief-13; The Parental Assessment of Paternal/Maternal Affectivity; The Dyadic Adjustment Scale (short version); The Daily Spiritual Experiences Scale; and The Inventory of Complicated Spiritual Grief. In the baseline measurement, 45 parents participated (37 mothers and 8 fathers), with 20 (13 mothers and 7 fathers) contributing to the follow-up and 9 engaging in interviews. Baseline results showed higher scores for mothers compared to fathers, with effect sizes ranging from small to medium (ranging from −0.02 to 0.29), though statistical significance was limited due to the small sample size. Multiple regression analysis for distress measures at baseline identified two significant predictors: maternal/paternal affectivity and gestational week. Additionally, positive support from healthcare professionals emerged as a mitigating factor, particularly in relation to Avoidance. A significant reduction in stress measures and parental affectivity was observed at the 6-month follow-up. Qualitative analysis revealed three themes: Shifts in Self-Perception and Post-Loss Growth; Conflicted Relationship with One's Body; and Negative Impact of COVID-19 vs. Unexpectedly Positive Aspects. In conclusion, the findings emphasize the significance of psychological and psychosocial interventions based on meaning-making processes, along with the importance of spiritual care and empowerment for those navigating perinatal loss. [ABSTRACT FROM AUTHOR]

The evolutionary dynamics of viruses, particularly exemplified by SARS-CoV-2 during the ongoing COVID-19 pandemic, underscore the intricate interplay between genetics, host adaptation, and viral spread. This paper delves into the genetic evolution of SARS-CoV-2, emphasizing the implications of viral variants on global health. Initially emerging from the Wuhan-Hu-1 lineage, SARS-CoV-2 rapidly diversified into numerous variants, each characterized by distinct mutations in the spike protein and other genomic regions. Notable variants such as B.1.1.7 (α), B.1.351 (β), P.1 (γ), B.1.617.2 (δ), and the Omicron variant have garnered significant attention due to their heightened transmissibility and immune evasion capabilities. In particular, the Omicron variant has presented a myriad of subvariants, raising concerns about its potential impact on public health. Despite the emergence of numerous variants, the vast majority have exhibited limited expansion capabilities and have not posed significant threats akin to early pandemic strains. Continued genomic surveillance is imperative to identify emerging variants of concern promptly. While genetic adaptation is intrinsic to viral evolution, effective public health responses must be grounded in empirical evidence to navigate the evolving landscape of the pandemic with resilience and precision. [ABSTRACT FROM AUTHOR]

The optimal placement of healthcare facilities, including the placement of diagnostic test centers, plays a pivotal role in ensuring efficient and equitable access to healthcare services. However, the emergence of unique complexities in the context of a pandemic, exemplified by the COVID-19 crisis, has necessitated the development of customized solutions. This paper introduces a bi-objective integer linear programming model designed to achieve two key objectives: minimizing average travel time for individuals visiting testing centers and maximizing an equitable workload distribution among testing centers. This problem is NP-hard and we propose a customized local search algorithm based on the Voronoi diagram. Additionally, we employ an ϵ -constraint approach, which leverages the Gurobi solver. We rigorously examine the effectiveness of the model and the algorithms through numerical experiments and demonstrate their capability to identify Pareto-optimal solutions. We show that while the Gurobi performs efficiently in small-size instances, our proposed algorithm outperforms it in large-size instances of the problem. [ABSTRACT FROM AUTHOR]

The purpose of this research is to examine whether Buddhist ethics can improve the health and well-being of Buddhist practitioners during pandemics like COVID-19. It is hypothesized that diseases are part of suffering, and Buddhist teachings aim to eliminate the suffering of all beings. Buddhism also offers ethical codes of conduct for its practitioners to improve their health and well-being. So, the Buddha's teaching or Buddhist ethics, when practiced seriously, should be able to improve one's health, physically and mentally, enhancing the well-being of all Buddhist practitioners during the spread of all pandemics including COVID-19. The present study found that Buddhist ethical practices like the chanting of Buddhist suttas and the development of mindfulness, concentration/meditation, and insight (vipassanā) can improve both physical and mental health, which are important for dealing with any pandemic, tremendously. If the cores of Buddhist ethics (morality, meditation, and wisdom) are perfectly practiced, not only will one live with good physical and mental health but one also will be able to eliminate all the mental defilements that are the root causes of all illnesses and thus enter nibbāna, the state of mind that is beyond all sources of suffering including pandemics/epidemics. More specifically, this paper highlights a set of Buddhist practices, called four bhāvanās (types of development), that can be used to improve health and well-being during any pandemic. [ABSTRACT FROM AUTHOR]

The social media app TikTok was launched in the US in 2017 with a very specific purpose: sharing 15-s clips of singing and dancing to popular songs. Seven years and several billion downloads later, it is now the go-to app for Gen Z Internet users and much better known for its ultra-personalized algorithm, AI-driven filters, and network of thriving subcultures. Among them, a growing community of magical and spiritual practitioners, frequently collectivized as Witchtok, who use the app not only share their craft and create community but consider the technology itself a powerful partner with which to conduct readings, channel deities, connect to a collective conscious, and transcend the communicative boundaries between the human and spirit realms—a practice that can be understood as algorithmic divination. In analyzing contemporary witchcraft on TikTok and contextualizing it within the larger history of technospirituality, this paper aims to explore algorithmic divination as an increasingly popular and powerful practice of technomancy open to practitioners of diverse creed and belief. [ABSTRACT FROM AUTHOR]

During the winter of 2019, the global outbreak of COVID-19 prompted extensive research on urban air pollution under lockdown measures. However, these studies predominantly focused on winter conditions, thereby limiting investigations into changes in urban air pollutants during other seasons that were also subject to lockdown restrictions. Shanghai, China, has undergone two COVID-19 lockdown periods in two seasons: winter 2019 and spring 2022. The seasonal variations and human activities were represented by meteorological factors and nighttime light brightness in this paper, respectively. The reduction in human-related emissions during the two lockdown periods was estimated based on the targets outlined in China's Air Pollution Prevention and Control Action Plan. The results showed significant reductions in NO2 and PM particles during the two lockdown periods, both accompanied by a notable increase in O3 concentration. In comparison to the winter lockdown, there was an approximate 40% decrease in the NO2 and PM2.5 concentrations in the spring, while the O3 concentration exhibited an increase of 48.81%. Furthermore, due to shifting wind patterns during the two lockdowns from winter to spring, the high-pollution core areas shifted 20–25 km southeastward in the spring. The PM particles and NO2 concentrations exhibited a considerable impact from human activities, whereas the O3 concentration was affected mostly by seasonal change and interactions among air pollutants. Compared to the corresponding non-lockdown condition, the concentration of CO decreased during the winter lockdown; however, it increased during the spring lockdown. The different change in CO concentration during the two lockdown periods was found to have a lower effect on the O3 concentration than that caused by changes in meteorological factors and nitrogen oxide (NO, NO2) concentrations. In summary, the impact of COVID-19 lockdown periods on urban air pollutants was more pronounced in spring compared to winter, and the interactions among air pollutants also underwent alterations. [ABSTRACT FROM AUTHOR]

The process of SARS-CoV-2 infection, responsible for the COVID-19 pandemic, is carried out through different steps, with the interaction between ACE2 and Spike protein (S) being crucial. Besides of that, the acidic environment of endosomes seems to play a relevant role in the virus uptake into cells and its intracellular replication. Patients affected by two rare genetic tubulopathies, Gitelman's and Bartter's Syndromes, and a rare genetic metabolic disease, Fabry Disease, have shown intrinsic protection from SARS-CoV-2 infection and COVID-19 on account of specific intrinsic features that interfere with the virus uptake into cells and its intracellular replication, which will be reported and discussed in this paper, providing interesting insights for present and future research. [ABSTRACT FROM AUTHOR]

Due to the global population increase and the recovery of agricultural demand after the COVID-19 pandemic, the importance of agricultural automation and autonomous agricultural vehicles is growing. Fallen person detection is critical to preventing fatal accidents during autonomous agricultural vehicle operations. However, there is a challenge due to the relatively limited dataset for fallen persons in off-road environments compared to on-road pedestrian datasets. To enhance the generalization performance of fallen person detection off-road using object detection technology, data augmentation is necessary. This paper proposes a data augmentation technique called Automated Region of Interest Copy-Paste (ARCP) to address the issue of data scarcity. The technique involves copying real fallen person objects obtained from public source datasets and then pasting the objects onto a background off-road dataset. Segmentation annotations for these objects are generated using YOLOv8x-seg and Grounded-Segment-Anything, respectively. The proposed algorithm is then applied to automatically produce augmented data based on the generated segmentation annotations. The technique encompasses segmentation annotation generation, Intersection over Union-based segment setting, and Region of Interest configuration. When the ARCP technique is applied, significant improvements in detection accuracy are observed for two state-of-the-art object detectors: anchor-based YOLOv7x and anchor-free YOLOv8x, showing an increase of 17.8% (from 77.8% to 95.6%) and 12.4% (from 83.8% to 96.2%), respectively. This suggests high applicability for addressing the challenges of limited datasets in off-road environments and is expected to have a significant impact on the advancement of object detection technology in the agricultural industry. [ABSTRACT FROM AUTHOR]

Heritage tourism in Egypt, differentiated by its distinctive ancient wonders and cultural prosperity, has faced numerous challenges through its history, with political unrest, economic fluctuations, and, most recently, the global COVID-19 pandemic. This research paper investigates the dynamic interplay between planned and adopted resilience within the hotel sector in Egyptian heritage sites and their consequential effects on both social and economic sustainability. A quantitative research method was employed to empirically explore these dynamics. A structured questionnaire was distributed to 550 top and middle managers in hotels located in heritage sites, capturing insights into their perspectives on planned and adopted resilience. The collected data underwent rigorous analysis utilizing "partial least squares structural equation modeling" (PLS-SEM), providing a robust foundation for drawing meaningful conclusions. Findings from the research underscore the necessity of aligning planned and adopted resilience to generate sustainable social and economic performance. The synthesis of planned and adopted resilience was revealed to be pivotal in generating sustainable social and economic performance for hotels. This synthesis catalyzes the hotels' ability to mitigate uncertainties, adjust to changing environment, and ensure long-term viability. This research might contribute to the current literature by suggesting industry-specific awareness for the reciprocal relationship between planned and adopted resilience in the hotel businesses and their combined influence on both sides of sustainability (social and economic). The findings provide actionable recommendations for hotel management, policymakers, and industry stakeholders to enhance resilience, foster social cohesion, and ensure the economic sustainability of heritage tourism in an everchanging environment. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, microbiological controls neglected the spread of viruses through the air. Techniques to identify this threat required additional research to enable control measures to be introduced to protect against the spread of disease through this route. Due to the very high level of risk occurring during research on the COVID-19 and SARS-CoV-2 viruses, it seems necessary to use analogous microorganisms that will allow, through an experiment, to validate or challenge a method that stops the spread of infectious microorganisms, without unnecessary risk to research staff. The presented work was carried out to assess the possibility of using airborne microorganisms that are safe for humans for this type of research. The work presents the selection process of bacteria and viruses (bacteriophages) that have the greatest potential for use in experimental studies on airborne-droplet transmission indoors, especially in hospital facilities. In the study, it was assumed that determining the survival rates of groups of organisms would allow them to be used as a proxy for studying more dangerous bacteria and viruses. Survival studies of selected microorganisms were carried out, and the paper selected microorganisms with the highest survival rate in a given environment. [ABSTRACT FROM AUTHOR]

This paper examines the relationships between the consumption of 'bad' or 'good' digital economic news and attitudes toward immigrant and ethnic minorities during the crisis that developed during the COVID-19 pandemic. The study considered attitudes toward two minority groups in Israel: immigrant citizens from English-speaking countries, and Israeli Palestinian citizens, an ethnic minority. The data were collected through an online survey of 866 respondents, who were members of the majority population group. The study found that, during the global crisis, exposure to bad digital news was associated with more positive attitudes toward both disadvantaged and non-disadvantaged minority groups. Moreover, in times of global crisis, people focused mostly on local rather than global digital news. In contrast to the idea of Intergroup Threat Theory, the study revealed that feelings of economic threat during the global crisis engendered higher cohesion between different population groups, and more positive attitudes toward minorities. In times of crisis, bad news for the economy brings good news for social solidarity—people tend to rally around the flag; this phenomenon even occurs between groups engaged in years-long, protracted conflict. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic affected many aspects of human life including consumer behavior. The main aim of this paper was to identify basic patterns of changes in consumer attitudes towards agri-food products under the influence of the 2020 pandemic and to better understand to what extent and what kind of food market problems appeared for the inhabitants of the Danube microregion. For this purpose, an explorative study was elaborated. Assuming that the experience of COVID-19 affected consumer attitudes and sense of food security, a hybrid survey was conducted in the Danube microregion (Croatia, Serbia and Romania) during 2022. Data collected from a total of 903 respondents were statistically analyzed in SPSS. Descriptive statistics, PCA, ANOVA and t-Test were employed. The main results have shown that although the surveyed population of the Danube microregion during the pandemic in 2020 was generally not afraid of food shortages, food was in most part available for their families and their shopping habits have not changed to a large degree, the experience of the pandemic has raised the level of awareness about some issues related to food and specifically the prices of food products. Also, three different patterns of attitude and behavior towards food and agriculture, which emerged as a result of the experience of the pandemic in 2020, were identified. These patterns also proved to be different for different segments of the population. The findings suggest the need for stronger support for the development of locally affordable food systems with the use of ICT as a coping mechanism in crises. [ABSTRACT FROM AUTHOR]

Background: COVID-19 caused a pandemic, due to its ease of transmission and high number of infections. The evolution of the pandemic and its consequences for the mortality and morbidity of populations, especially the elderly, generated several scientific studies and many research projects. Among them, we have the Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO) research project. For such a project with many data records, it is necessary to provide a smooth graphical analysis to extract value from it. Methods: In this paper, we present the development of a full-stack Web application for the PREMO project, consisting of a dashboard providing statistical analysis, data visualization, data import, and data export. The main aspects of the application are described, as well as the diverse types of graphical representations and the possibility to use filters to extract relevant information for clinical practice. Results: The application, accessible through a browser, provides an interactive visualization of data from patients admitted to the intensive care unit (ICU), throughout the six waves of COVID-19 in two hospitals in Lisbon, Portugal. The analysis can be isolated per wave or can be seen in an aggregated view, allowing clinicians to create many views of the data and to study the behavior and consequences of different waves. For instance, the experimental results show clearly the effect of vaccination as well as the changes on the most relevant clinical parameters on each wave. Conclusions: The dashboard allows clinicians to analyze many variables of each of the six waves as well as aggregated data for all the waves. The application allows the user to extract information and scientific knowledge about COVID-19's evolution, yielding insights for this pandemic and for future pandemics. [ABSTRACT FROM AUTHOR]

COVID-19 is a contagious disease that poses a serious risk to public health worldwide. To reduce its spread, people need to adopt preventive behaviours such as wearing masks, maintaining physical distance, and isolating themselves if they are infected. However, the effectiveness of these measures may depend on various factors that differ across countries. This paper investigates how some factors, namely outsiders' effect, life expectancy, population density, smoker percentage, and temperature, influence the transmission and death rate of COVID-19 in ninety-five top-affected countries. We collect and analyse the data of COVID-19 cases and deaths using statistical tests. We also use fuzzy logic to model the chances of COVID-19 based on the results of the statistical tests. Unlike the conventional uniform weighting of the rule base in fuzzy logic, we propose a novel method to calculate the weights of the rule base according to the significance of the factors. This study aims to provide a comprehensive and comparative analysis of the factors of COVID-19 transmission and death rates among different countries. [ABSTRACT FROM AUTHOR]

Background: Personal emotions and affects have been identified and studied in the context of pandemics, as well as coping strategies centered on emotional regulation or the balance between positive and negative emotions. Objectives: The objectives of this paper are to identify an emotion and affect structure in our sample and analyze the relationship of these dimensions with resilient coping in the context of the COVID-19 pandemic. Method: This study employed a cross-sectional design that involved a non-probabilistic sample with 598 participants over the age of 18, with 51.1% being female, and an average age of 40.73 years. First, the emotional structure was identified through principal component analysis (PCA). Secondly, a linear regression analysis was performed to investigate emotional dimensions as predictors of coping. Results: A valid and reliable emotional structure with four dimensions was identified. The regression model revealed that coping is positively associated with the active and positive dimension and negatively correlated with the negative and moral dimensions. Conclusions: Emotional dimensions are predictors of coping, with moral and negative dimensions having a negative effect, while active and positive dimensions have a positive effect. When designing interventions for coping strategies, multiple dimensions of emotions and affective states in people who are in vulnerable situations must be considered. [ABSTRACT FROM AUTHOR]

The impact of the global COVID-19 pandemic has been devastating in many countries, increasing household energy poverty. Lockdown measures have brought the EU economies into recession phases and forced people to stay confined to their homes, aggravating these issues. From the second half of 2021, when the worst seemed behind us, a new threat has appeared threatening economic recovery: the inflationary process in energy prices. This paper aims to verify the effects on energy poverty in European countries following the economic crisis generated by COVID-19 and the current inflationary scenario due to the increase in energy commodity prices through dynamic factor models, estimating the time it will take for energy poverty to return to levels before the shocks that occurred over the past two years. The outcomes show that the overall rise in energy prices (in particular gas) that unexpectedly affected European countries modifies the forecast scenarios, delaying, at best, the first improvements, initially expected as early as 2021, until after 2022. [ABSTRACT FROM AUTHOR]

COVID-19 analysis from medical imaging is an important task that has been intensively studied in the last years due to the spread of the COVID-19 pandemic. In fact, medical imaging has often been used as a complementary or main tool to recognize the infected persons. On the other hand, medical imaging has the ability to provide more details about COVID-19 infection, including its severity and spread, which makes it possible to evaluate the infection and follow-up the patient's state. CT scans are the most informative tool for COVID-19 infection, where the evaluation of COVID-19 infection is usually performed through infection segmentation. However, segmentation is a tedious task that requires much effort and time from expert radiologists. To deal with this limitation, an efficient framework for estimating COVID-19 infection as a regression task is proposed. The goal of the Per-COVID-19 challenge is to test the efficiency of modern deep learning methods on COVID-19 infection percentage estimation (CIPE) from CT scans. Participants had to develop an efficient deep learning approach that can learn from noisy data. In addition, participants had to cope with many challenges, including those related to COVID-19 infection complexity and crossdataset scenarios. This paper provides an overview of the COVID-19 infection percentage estimation challenge (Per-COVID-19) held at MIA-COVID-2022. Details of the competition data, challenges, and evaluation metrics are presented. The best performing approaches and their results are described and discussed. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease-19 (COVID-19). This virus has caused a global pandemic, marked by several mutations leading to multiple waves of infection. This paper proposes a comprehensive and integrative mathematical approach to the third wave of COVID-19 (Omicron) in the Kingdom of Saudi Arabia (KSA) for the period between 16 December 2022 and 8 February 2023. It may help to implement a better response in the next waves. For this purpose, in this article, we generate a new mathematical transmission model for coronavirus, particularly during the third wave in the KSA caused by the Omicron variant, factoring in the impact of vaccination. We developed this model using a fractal-fractional derivative approach. It categorizes the total population into six segments: susceptible, vaccinated, exposed, asymptomatic infected, symptomatic infected, and recovered individuals. The conventional least-squares method is used for estimating the model parameters. The Perov fixed point theorem is utilized to demonstrate the solution's uniqueness and existence. Moreover, we investigate the Ulam–Hyers stability of this fractal–fractional model. Our numerical approach involves a two-step Newton polynomial approximation. We present simulation results that vary according to the fractional orders (γ) and fractal dimensions (θ), providing detailed analysis and discussion. Our graphical analysis shows that the fractal-fractional derivative model offers more biologically realistic results than traditional integer-order and other fractional models. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) was a global pandemic with high mortality and morbidity that led to an increased health burden all over the world. Although the virus mostly affects the pulmonary tract, cardiovascular implications are often observed among COVID-19 patients and are predictive of poor outcomes. Increased values of myocardial biomarkers such as troponin I or NT-proBNP were proven to be risk factors for respiratory failure. Although the risk of acute coronary syndromes (ACSs) was greater in the acute phase of COVID-19, there were lower rates of hospitalization for ACSs, due to patients' hesitation in presenting at the hospital. Hospitalized ACSs patients with COVID-19 infection had a prolonged symptom-to-first-medical-contact time, and longer door-to-balloon time. The mechanisms of myocardial injury in COVID-19 patients are still not entirely clear; however, the most frequently implicated factors include the downregulation of ACE2 receptors, endothelial dysfunction, pro-coagulant status, and increased levels of pro-inflammatory cytokines. The aim of this paper is to evaluate the long-term outcomes and prognosis of COVID-19 survivors that presented an acute myocardial infarction, by reviewing existing data. The importance of the association between this infectious disease and myocardial infarction arises from the increased mortality of patients with SARS-CoV-2 infection and AMI (10–76%, compared with 4.6% for NSTEMI patients and 7% for STEMI patients without COVID-19). The literature review showed an increased risk of cardiovascular events in COVID-19 survivors compared with the general population, even after the acute phase of the disease, with poorer long-term outcomes. [ABSTRACT FROM AUTHOR]

The COVID-19 lockdown has had serious consequences, including rethinking higher education. The study aims to enhance the knowledge base of online education and academic integrity through a case study of the Ludovika University of Public Service (LUPS), Budapest, Hungary. The research aimed to assess the teachers' experience with distance learning and examinations, including the change in workload, digital competencies, Moodle, Turnitin, and other software used during and after the lockdown. This paper summarizes the university-level policy changes induced during the lockdown, covering the introduction of emergency distance teaching and online examinations in academic integrity at the university. Two years after the first lockdown, the researchers made a survey (n = 145) about the continuation of the introduced solutions. The results show that a remarkable reordering started while the technical and technological backgrounds were available for the changes. The teachers could feel a significant increase in workload with distance education and have low trust in maintaining the standards of academic integrity. However, the research shows moderate and low levels of digital competencies in the majority of teachers, which clearly defines the most crucial task leading to success. Maintaining the monitoring system with objective indicators of the development and the opinions of the interested parties is essential for successful strategies in the field. [ABSTRACT FROM AUTHOR]

In this paper, we tackle the problem of forecasting future pandemics by training models with a COVID-19 time series. We tested this approach by producing one model and using it to forecast a non-trained time series; however, we limited this paper to the eight states with the highest population density in Mexico. We propose a generalized pandemic forecasting framework that transforms the time series into a dataset via three different transformations using random forest and backward transformations. Additionally, we tested the impact of the horizon and dataset window sizes for the training phase. A Wilcoxon test showed that the best transformation technique statistically outperformed the other two transformations with 100% certainty. The best transformation included the accumulated efforts of the other two plus a normalization that helped rescale the non-trained time series, improving the sMAPE from the value of 25.48 attained for the second-best transformation to 13.53. The figures in the experimentation section show promising results regarding the possibility of forecasting the early stages of future pandemics with trained data from the COVID-19 time series. [ABSTRACT FROM AUTHOR]

Although the severity of the COVID-19 pandemic has appears to have subsided in most parts of the world, nevertheless, in addition to six million deaths, it has yielded unprecedented challenges in the economy, energy, education, urban services, and healthcare sectors. Meanwhile, based on some reports, smart solutions and technologies have had significant success in achieving pandemic-resilient cities. This paper reviews smart city initiatives and contributions to the prevention and treatment of coronavirus disease, as well as reducing its destructive impact, leading towards pandemic-resilient economic and health systems. Furthermore, the situational awareness contributions are reviewed in pandemic-resilient governance. The main contribution of this study is to describe the construction of social capital in smart cities as a facilitator in creating a pandemic-resilient society in crisis through two analyses. Moreover, this research describes smart cities' energy as interconnection of energy hubs (EHs) that leads to a high level of resiliency in dealing with the main challenges of the electricity industry during the pandemic. Energy-hub-based smart cities can contribute to designing pandemic-resilient energy infrastructure, which can significantly affect resilience in economic and health infrastructure. In brief, this paper describes a smart city as a pandemic-resilient city in the economic, energy, and health infrastructural, social, and governmental areas. [ABSTRACT FROM AUTHOR]

This paper highlights curriculum and policy reforms and innovations in a Higher Education (HE) institution in response to undergraduate student perspectives about the phenomenon of the COVID-19 restrictions imposed by the New Zealand government (2020–2022). The advent of the coronavirus pandemic precipitated unexpected and unprecedented changes in HE learning and in the pedagogy required for undergraduate students. Consequently, HE institutions have had to be agile, resulting in 'emergency' adaptations to curriculum practice and policy implementation. This paper discusses triggers for change, reactions to restrictions, strategic measures, and the emergence of a 'new normal' from an undergraduate student perspective. Local and global concerns about student participation in undergraduate study (in Sport and Recreation), sport, and physical activity during restricted periods prompted the researchers to investigate the challenges these young people faced. Student voice was collected through semi-structured interviews and focus groups, collected post lockdown periods. Research findings, elicited from lecturers using a collaborative auto-ethnographical method, along with interpretative analysis (hermeneutic phenomenology) of students' perspectives about the four pillars of lifestyle, active lives, learning, and livelihood provide insights about the impact of unexpected curriculum and policy change for HE students in New Zealand. This research provides real-time data to inform recommendations on policy and practice in HE institutions, to enhance student wellbeing in times of crises, like the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Polypharmacy, the use of multiple and potentially inappropriate medications, is an increasing problem among older adults. The global polypharmacy prevalence is 34.6% in patients with COVID-19, and polypharmacy in COVID-19 increases with age. The present paper proposes that polypharmacy in older adults with COVID-19 and other comorbid conditions is linked to the medication outcome reporting bias of randomized controlled trials. Outcome reporting bias can occur when treatment efficacy is reported as relative risk reductions, which overestimates medication benefits and exaggerates disease/illness risk reductions compared to unreported absolute risk reductions. The comorbidities common in patients with COVID-19 include high blood pressure, cardiovascular disease, dementia or cerebrovascular disease, and diabetes. Accordingly, the present paper reassesses the relative and absolute risk reductions in clinical trials from a small convenience sample of antihypertension, statin, anticoagulant, and antihyperglycemic medications. Examples demonstrate a wide gap between reported relative risk reductions and unreported absolute risk reductions in medication clinical trials. This paper concludes that medication clinical trial outcome reporting bias is an important upstream factor that contributes to biased medication benefits and poor clinical decision making, leading to polypharmacy in older adults with COVID-19 and other comorbid conditions. Public health campaigns are urgently needed to educate the public about the link between polypharmacy and medication outcome reporting bias. [ABSTRACT FROM AUTHOR]