Public Health Events' Assessment Per Annex-2 Decision- Instrument of the Ihr (2005) and Communication with the World Health Organization's Ihr State Parties in the Who European-Region

Intro: Guided by the annex-2 decision instrument of the International Health Regulations (IHR) 2005, public health events are assessed and notified to WHO by the IHR State Parties. Similarly, using the secure Event Information Site (EIS), the WHO shares information with the IHR State Parties through their National Focal Points (NFPs). This summarizes information about such events associated with the WHO European Region (EURO). Method(s): From the EIS, a list of events that may constitute a public health emergency of international concern shared by the WHO with the NFPs was extracted. This descriptive analysis includes data from 2007-2022 within the European Region or travel-associated while events occurred elsewhere. Finding(s): Of all the events (from six WHO Regions), 15% were associated with the European Region. The annual proportion varied such as 8% in 2007 and 22% in 2022. Events' classification by hazards and syndromes showed infectious (89%) and acute respiratory syndromes (42%) as the most common causes. Per annex-2 of the IHR (2005), about 88% and 66% of events qualified for unusual/unexpected or serious public health impact respectively and 60% simultaneously qualified both the criteria. About 61% of events qualified for unusual/unexpected and having risk of international spread concurrently. Similarly, 55% events had risk of international spread and serious public health impact, simultaneously. About 16% had risk of interference with international travel/trade. The recent EIS communications (2019-2022) were related to monkeypox, COVID-19, hepatitis of unknown aetiology, human influenza caused by a new subtype and polio. Conclusion(s): The events' assessment shared with the NFPs through the secure EIS platform is promptly accessible to all the IHR State Parties. Over the past fifteen years, such communications can improve situational awareness of events and facilitate information exchange for IHR State-Parties. Moreover, this encourages handling hazards at their source and strengthen readiness and response.Copyright © 2023

Zero-and-One Integer-Valued AR(1) Time Series with Power Series Innovations and Probability Generating Function Estimation Approach

Zero-and-one inflated count time series have only recently become the subject of more extensive interest and research. One of the possible approaches is represented by first-order, non-negative, integer-valued autoregressive processes with zero-and-one inflated innovations, abbr. ZOINAR(1) processes, introduced recently, around the year 2020 to the present. This manuscript presents a generalization of ZOINAR processes, given by introducing the zero-and-one inflated power series (ZOIPS) distributions. Thus, the obtained process, named the ZOIPS-INAR(1) process, has been investigated in terms of its basic stochastic properties (e.g., moments, correlation structure and distributional properties). To estimate the parameters of the ZOIPS-INAR(1) model, in addition to the conditional least-squares (CLS) method, a recent estimation technique based on probability-generating functions (PGFs) is discussed. The asymptotic properties of the obtained estimators are also examined, as well as their Monte Carlo simulation study. Finally, as an application of the ZOIPS-INAR(1) model, a dynamic analysis of the number of deaths from the disease COVID-19 in Serbia is considered.

Curcumin as a natural systemic disease modulator

In the prevention and treatment of various diseases, a variety of preparations based on medicinal plants are now generally acknowledged and well-documented. The main advantages of traditional medicine in underdeveloped nations are safety and affordability. As diferuloylmethane, curcumin is a naturally occurring polyphenol that is mostly produced in the rhizomes of plant roots. Curcumin has a long history of usage in conventional medicine, although its therapeutic effects and health advantages are still little understood. The therapeutic benefits of curcumin include the treatment of malignancies, neurodegenerative, ocular, and COVID diseases as well as inflammatory and digestive disorders, rheumatic and skin issues, and tumors. Apoptosis-related genes, cytokines, enzymes, and other targets have all been found in certain studies to be modulated by curcumin. Furthermore, little is known about the biological mechanisms that underlie these activities. We will examine some of the known molecular targets and biological processes of curcumin in this chapter. The processes through which curcumin functions in neuroprotection and/or mental health disorders will be covered in this chapter. We will also talk about curcumin's protective role in how bone may impact neurological function. © 2023 Nova Science Publishers, Inc.

Immunoserologic and hemotherapy considerations in patients undergoing hematopoietic progenitor cell transplantation

With increasing evidence of the success of hematopoietic progenitor cell (HPC) transplantation in the cure of many benign and malignant diseases, such interventions have been performed at increasing rates for the past several years. Due to myelosuppression caused by the conditioning and graft-versus-host disease (GVHD) prophylaxis regimens, blood component transfusions are almost inevitably needed. During transplantation, patient's hematopoietic lineages reconstitute to the HPC donor's progenitor cell types. Therefore, specific immunoserologic and hemotherapeutic aspects need to be considered for the selection of blood components during different phases of transplantation for successful outcomes. Those considerations include but are not limited to ABO and human leucocyte antigen (HLA) compatibility of the transfused blood components with either or both the patient and the HPC donor according to the particular phase of transplantation, and the special blood component processing to reduce the risk of transfusion associated graft-versus-host disease (TA-GVHD), cytomegalovirus (CMV) transmission in CMV seronegative patients and immune mediated platelets refractoriness. Complications may still arise, particularly in major, minor, or bidirectional ABO mismatched transplantations and/or due to the HLA mismatch and alloimmunization. Here we discuss the indications, immunoserologic considerations and the special component processing of red blood cells (RBCs), platelets, granulocytes, and plasma transfusions, based upon the current evidence and describe the prevention and management of salient, pertinent complications.Copyright © 2022 The authors.

Quantitative proteomics analysis of COVID-19 patients: Fetuin-A and tetranectin as potential modulators of innate immune responses.

Treatment of severe cases of coronavirus disease 2019 (COVID-19) is extremely important to minimize death and end-organ damage. Here we performed a proteomic analysis of plasma samples from mild, moderate and severe COVID-19 patients. Analysis revealed differentially expressed proteins and different therapeutic potential targets related to innate immune responses such as fetuin-A, tetranectin (TN) and paraoxonase-1 (PON1). Furthermore, protein changes in plasma showed dysregulation of complement and coagulation cascades in COVID-19 patients compared to healthy controls. In conclusion, our proteomics data suggested fetuin-A and TN as potential targets that might be used for diagnosis as well as signatures for a better understanding of the pathogenesis of COVID-19 disease.

Does bank affiliation affect firm capital structure? Evidence from a financial crisis

PurposeThis study aims to assess the determinants of corporate debt with a particular focus on bank-affiliated and non-bank-affiliated firms during the global financial crisis.Design/methodology/approachThe authors analyse the data of 395 listed manufacturing firms from Pakistan with 2,370 firm-year observations. The sample is divided into subsamples, namely bank-affiliated, non-bank-affiliated and stand-alone firms. Fixed and panel effect regression models are applied to determine the during, pre-crisis and post-crisis effects on corporate capital structure.FindingsThe robust results of the study reveal that non-bank-affiliated firms have different leverage determinant behaviours with a greater reliance on size, tangibility and profitability. However, bank-affiliated firms seemed to show greater immunity from a crisis compared to other firms. Simultaneously, the stand-alone firms remained at a disadvantage subject to internal financial ties of group-affiliated firms and form a base of market imperfection.Practical implicationsThis study's findings imply that financial managers should contain better ties with financial institutions to enhance financial immunity in worse time of financial crisis or COVID-19 global calamity. On the regulation front, these findings call for critical policy regulations to govern the internal ties with financial institutions to create a level playing field for the corporate sector.Originality/valueTo the best of the authors' knowledge, this study is the first to investigate determinants of corporate debt with a particular focus on bank-affiliated and non-bank-affiliated firms. This work is also novel to explore corporate debt of bank-affiliated and non-bank-affiliated firms during the financial crisis.

Differences in Diabetes Control in Telemedicine vs. In-Person Only Visits in Ambulatory Care Setting

Importance: The COVID-19 pandemic has led to increased utilization of telemedicine. Patients with diabetes are a vulnerable population that require regular treatment and monitoring. Little is known about the impact visit modality on diabetes outcomes in an ambulatory setting. Objective: Compare proportions of patients with diabetes with uncontrolled diabetes among those with telemedicine versus in-person only ambulatory visits and examine differences by age, race, gender, ethnicity, and insurance. Design: A retrospective cohort study. Setting : The largest academic healthcare system in the state of Georgia with ambulatory clinics in urban, suburban and rural settings. Participants : Adults with diabetes scheduled for an ambulatory primary or specialty clinic visit between May 2020 and May 2021 were included. Patients were compared among three visit groups: those with all in-person visits, those with one telemedicine visit, and those with 2+ telemedicine visits. Demographics including age, race, ethnicity, gender, insurance status, and comorbidities were extracted from the electronic medical record. Main Outcomes and Measures: The primary clinical outcome was uncontrolled diabetes, defined as HbAlc >= 9.0%. Chi-square test was used to determine crude differences in uncontrolled diabetes between visit groups. Multivariable logistic regression was used to assess differences in uncontrolled diabetes between visit groups following risk adjustment. Results: A total of 18,148 ambulatory clinic visits for patients with diabetes were scheduled during the study period, and 11.6% had uncontrolled diabetes. There was no difference in proportion of patients with uncontrolled diabetes between all in-person visits (834 (11.6%)), one telemedicine visit (558 (11.8%)), or 2+ telemedicine visits (709 (11.4%)) (p = 0.80). Patients with 2+ telemedicine visits had significantly lower odds of uncontrolled diabetes compared to all in-person visits after adjusting for age, gender, race, ethnicity, insurance status, and comorbidities (OR: 0.88;95% CI: 0.79 - 0.99, p = 0.03). Conclusions and Relevance: Telemedicine visits were associated with a lower odds of uncontrolled diabetes. Further work is warranted to explore the relationship between telemedicine visits, equitable access to care, and diabetes outcomes. Copyright © 2023 Annals of Family Medicine, Inc.

Implementing and managing nurse led reviews of patient outcomes at 3 and 6 months following mechanical thrombectomy for acute ischaemic stroke

Introduction: 90% of patients undergoing mechanical thrombectomy (MT) require collection of a 90-day outcome (Sacks et al, 2018). This paper presents the development and operation of a Stroke clinical nurse specialist (CNS) led, telephone thrombectomy outcome clinic at a Comprehensive stroke centre (CSC). The clinic was funded and included within the CNS role. The CNS completed formal mRS training. Service managers created a template for the clinic e.g., appointment duration, frequency, and volume. The CNS curated appointments at 90days & 6 months +/- 14 days. Clinics operated weekly (10-20 patients/month) in structured 15-minute appointments. Multiple 'Did not attend's' (DNA) outcome data was obtained via GP and next of kin. Method(s): Outcome completion and DNA rates were compared from 2019- 2021 from hospital systems. A survey for stroke consultants captured perceived benefits and challenges. Result(s): Outcome completion for 2019 was 97.6% (n=164), 2020 86.9% (n=145) and 2021 99% (n=101). 2020 data was temporarily impacted by stroke CNS staffing change and the coronavirus pandemic. DNA rates reduced between 2019 - 2021 for 3 month (18% to 17%) and 6-month reviews (19% to 11%). 100% of stroke consultants agreed outcome data is vital for the service (6/6). Perceived benefits were quality assurance, standardisation, governance, and clinical continuity. Practical challenges included room availability, following up DNA's and the use of interpreters. Conclusion(s): CSC's can achieve >90% of MT case outcomes with mRS trained CNS led clinics. They provide standardised, reliable, and vital patient outcomes for improving MT services.

Analysing the model of online learning in mathematics and science using a two-step least squares method

This study analyses the model of online learning. Specifically, the model examines the effects of student education expenditures on student perceptions on online learning of mathematics and science subjects. We expect that student education expenditures are higher upon the introduction of a new method of learning which is online learning during the Covid-19 pandemic. Even though many incentives have been implemented, unobserved factors such as availability of transportation to commute and distances to acquire reliable internet connection might affect student's expenses and performance. Hence, in this study, we employ the two-step least squares method to address potential endogeneity bias in the baseline model. The findings show some evidence of bias with statistically significant results of the endogeneity test and strong instrument results of the overidentifying restriction test. Male students in particular significantly tend to have high education expenses and less likely to prefer online learning compared to face-to-face learning of mathematics and science. It suggests for the government and policymakers to intervene strategically by allocating digital endowment such as network externalities at appropriate platforms to reduce students' expenses on education. It also perhaps may help to reduce students gender inequality in education. © 2023 Author(s).

An INAR(1) Time Series Model via a Modified Discrete Burr–Hatke with Medical Applications

This paper introduces a flexible discrete transmuted record type discrete Burr–Hatke (TRT-DBH) model that seems suitable for handling over-dispersion and equi-dispersion in count data analysis. Further to the elegant properties of the TRT-DBH, we propose, in the time series context, a first-order integer-valued autoregressive process with TRT-DBH distributed innovations [TRBH-INAR(1)]. The moment properties and inferential procedures of this new INAR(1) process are studied. Some Monte Carlo simulation experiments are executed to assess the consistency of the parameters of the TRBH-INAR(1) model. To further motivate its purpose, the TRBH-INAR(1) is applied to analyze the series of the COVID-19 deaths in Netherlands and the series of infected cases due to the Tularaemia disease in Bavaria. The proposed TRBH-INAR(1) model yields superior fitting criteria than other established competitive INAR(1) models in the literature. Further diagnostics related to the residual analysis and forecasting based on the TRBH-INAR(1) model are also discussed. Based on modified Sieve bootstrap predictors, we provide integer forecasts of future death of COVID-19 and infected of Tularemia.

Assessing Foundation Students' Acceptance in Using Video Conferencing Technologies (VCTs) as Online Learning Platforms during the Pandemic

The COVID-19 pandemic has significantly affected Higher Education Institutions (HEIs) in Malaysian education system. Due to this, the HEIs have implemented online learning to be replaced with physical classrooms to ensure that all students able to reach their learning potentials. As such, video conferencing technologies (VCTs) have been employed nationwide for effective learning activities. Previous research have shown that teaching and learning using VCTs are beneficial for online learning, however, not many studies focused on the student's acceptance of VCTs during unforeseen situations. This study intends to overcome this research gap by investigating the factors influencing the foundation students' acceptance of VCTs during the outbreak. Therefore, the facilitating conditions and computer self-efficacy factors are integrated into the Technology Acceptance Model (TAM) for analysis. For this purpose, the PLS-SEM was used to analyze the data collected from 231 participants of selected higher education institutions in Malaysia. The finding revealed that ‘attitude towards use' and ‘intention to use' VCTS have a positive relationship with the actual use of VCTs. Furthermore, the result indicated that facilitating condition has significantly impacted the ‘perceived ease of use' of the VCTs. However, ‘computer self-efficacy' has no significant impact on the ‘perceived usefulness' of the VCTs. It is also learned that using VCTs is acceptable for remote and online learning mode, particularly amid the current COVID-19 pandemic. The outcomes of this study are able to improve the existing knowledge on the student's acceptance of VCTs and provide useful insights into the curriculum designated for the HEIs. Hence, it can be concluded that our findings validated the model used in this study and offered valuable guidelines in developing online learning approaches that promote learning through varied platforms. © 2023,International Journal of Emerging Technologies in Learning. All Rights Reserved.

Monoclonal Antibody Use for Coronavirus Disease 2019 in Pediatric Patients: A Multicenter Retrospective Study.

Monoclonal antibodies for COVID-19 are authorized in high-risk patients aged ≥12 years, but evidence in pediatric patients is limited. In our cohort of 142 patients treated at seven pediatric hospitals between 12/1/20 and 7/31/21, 9% developed adverse events, 6% were admitted for COVID-19 within 30 days, and none received ventilatory support or died.

Contactless Surveillance for Preventing Wind-Borne Disease using Deep Learning Approach

Covid-19 has been marked as a pandemic worldwide caused by the SARS-CoV-2 virus. Different studies are being conducted with a view to preventing and lessening the infections caused by covid-19. In future, many other wind-borne diseases may also appear and even emerge as "pandemic”. To prevent this, various measures should be an integral part of our daily life such as wearing face masks. It is tough to manually ensure individuals safety. The goal of this paper is to automate the process of contactless surveillance so that substantial prevention can be ensured against all kinds of wind-borne diseases. For automating the process, real time analysis and object detection is a must for which deep learning is the most efficient approach. In this paper, a deep learning model is used to check if a person takes any preventive measures. In our experimental analysis, we considered real time face mask detection as a preventive measure. We proposed a new face mask detection dataset. The accuracy of detecting a face mask along with the identity of a person achieved accuracy of 99.5%. The proposed model decreases time consumption as no human intervention is needed to check an individual person. This model helps to decrease infection risk by using a contactless automation system. © 2022,International Journal of Advanced Computer Science and Applications. All Rights Reserved.

ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination

The emergence of the COVID-19 pandemic and the first global infodemic have changed our lives in many different ways. We relied on social media to get the latest information about COVID-19 pandemic and at the same time to disseminate information. The content in social media consisted not only health related advise, plans, and informative news from policymakers, but also contains conspiracies and rumors. It became important to identify such information as soon as they are posted to make an actionable decision (e.g., debunking rumors, or taking certain measures for traveling). To address this challenge, we developed and publicly released the first largest manually annotated Arabic tweet dataset, ArCovidVac, for the COVID-19 vaccination campaign, covering many countries in the Arab region. The dataset is enriched with different layers of annotation, including, (i) Informativeness (more vs. less important tweets);(ii) fine-grained tweet content types (e.g., advice, rumors, restriction, authenticate news/information);and (iii) stance towards vaccination (pro-vaccination, neutral, anti-vaccination). Further, we performed in-depth analysis of the data, exploring the popularity of different vaccines, trending hashtags, topics and presence of offensiveness in the tweets. We studied the data for individual types of tweets and temporal changes in stance towards vaccine. We benchmarked the ArCovidVac dataset using transformer models for informativeness, content types, and stance detection. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

Dual_Pachi: Attention-based dual path framework with intermediate second order-pooling for Covid-19 detection from chest X-ray images.

Numerous machine learning and image processing algorithms, most recently deep learning, allow the recognition and classification of COVID-19 disease in medical images. However, feature extraction, or the semantic gap between low-level visual information collected by imaging modalities and high-level semantics, is the fundamental shortcoming of these techniques. On the other hand, several techniques focused on the first-order feature extraction of the chest X-Ray thus making the employed models less accurate and robust. This study presents Dual_Pachi: Attention Based Dual Path Framework with Intermediate Second Order-Pooling for more accurate and robust Chest X-ray feature extraction for Covid-19 detection. Dual_Pachi consists of 4 main building Blocks; Block one converts the received chest X-Ray image to CIE LAB coordinates (L & AB channels which are separated at the first three layers of a modified Inception V3 Architecture.). Block two further exploit the global features extracted from block one via a global second-order pooling while block three focuses on the low-level visual information and the high-level semantics of Chest X-ray image features using a multi-head self-attention and an MLP Layer without sacrificing performance. Finally, the fourth block is the classification block where classification is done using fully connected layers and SoftMax activation. Dual_Pachi is designed and trained in an end-to-end manner. According to the results, Dual_Pachi outperforms traditional deep learning models and other state-of-the-art approaches described in the literature with an accuracy of 0.96656 (Data_A) and 0.97867 (Data_B) for the Dual_Pachi approach and an accuracy of 0.95987 (Data_A) and 0.968 (Data_B) for the Dual_Pachi without attention block model. A Grad-CAM-based visualization is also built to highlight where the applied attention mechanism is concentrated.

Statistical modelling of COVID-19 and drug data via an INAR(1) process with a recent thinning operator and cosine Poisson innovations.

In this paper, we propose the first-order stationary integer-valued autoregressive process with the cosine Poisson innovation, based on the negative binomial thinning operator. It can be equi-dispersed, under-dispersed and over-dispersed. Therefore, it is flexible for modelling integer-valued time series. Some statistical properties of the process are derived. The parameters of the process are estimated by two methods of estimation and the performances of the estimators are evaluated via some simulation studies. Finally, we demonstrate the usefulness of the proposed model by modelling and analyzing some practical count time series data on the daily deaths of COVID-19 and the drug calls data.

Assessment of Left Ventricular Function by Global Longitudinal Strain in Patients Recovered from Covid-19

Background: Patients with COVID-19 infection may have an additional marker of outcomes with left ventricular (LV) strain evaluation by transthoracic echocardiography (TTE). Objective: This study aimed to use two-dimensional (2D) speckle-tracking echocardiography to evaluate left ventricular (LV) global longitudinal strain (GLS) in order to identify subclinical cardiac impairment among recovered cases from Covid-19 infection. Patients and methods: A case-control study in the isolation Hospital, Zagazig University in the duration from October 2021 to March 2022. We included 110 patients that were categorized in 2 groups according to clinical, radiological, laboratory and echocardiographic parameters: Group I: included patients recovered from Covid-19 (Study group). Group II: Non-Covid patients (Control group). This group included healthy subjects who have not encountered Covid-19 infection. Results: When comparing both groups, significant differences were found regarding echocardiographic data using speckle tracking. LVGLS was significantly decreased in cases compared to controls (19.18 ± 2.76 vs 21.58 ± 1.35, P<0.001), AP2GLS (18.90 ± 2.47 vs 21.58 ± 1.35, P<0.001), AP3GLS (20.28 ± 2.98 vs 21.94 ± 3.13, P = 0.005). A statistically difference existed between the two groups with respect to GLS, with all controls having a GLS value greater than −18 and 27.35% of cases had decreased GLS < −18%. Conclusion: As a primary method, it's nearly as secure as the more traditional median sternotomy for mitral valve repair. Excellent cosmetic outcomes can be achieved without the need for additional groin incisions and the risks associated with them. © 2022, Ain Shams University Faculty of Medicine. All rights reserved.