Integrated Neuro-Evolution-Based Computing Paradigm to Study the COVID-19 Transposition and Severity in Romania and Pakistan

Numerical treatment of the COVID-19 transposition and severity in Romania and Pakistan has been presented in this study, i.e., ANN-GA-SQP through artificial neural network genetic algorithms (ANN-GA) and sequential quadratic programming (SQP), a design of an integrated computational intelligent paradigm, COVID-19 is widely considered to be the greatest health threat humanity has ever faced. In terms of both health and economics, COVID-19 is a huge disaster. Many academics have looked at the COVID-19 model in their research papers, although they use different traditional techniques to represent it. The use of hybrid suggested solutions to solve this issue in the present article is significant, demonstrating the study's novelty. The SIR model of COVID-19 consists of a susceptible, infectious, and recovered class of population. The activation function for the construction of functions based on fitness in mean squared error sense is developed using nonlinear equations of the COVID-19 SIR model for the best performance of ANN-GA-SQP with the combined potential of GA and SQP of a network. While detailed refining is done with efficient local search with SQP, GAs operates as a global search. In addition, a neuron analysis will be presented to verify the effectiveness and complexity of the proposed method. Adam’s numerical methodology is applied to compare the sustainability and efficacy of the presented paradigm. Analytical evaluations of mean, median, and semi-interquartile range values, as well as Theil’s inequality coefficients, root mean squared error, and mean of absolute deviation) values have been observed. The convergence and correctness of the ANN-GA-SQP approach are further validated by statistical analyses.

Artificial intelligence knacks-based computing for stochastic COVID-19 SIRC epidemic model with time delay

Time delays play an important part in modeling the fact that one cannot be communicable for a long time after becoming sick. Delay can be triggered by a variety of epidemiological situations. The most egregious causes of a delay are infection latency in the vector and infection latency in the infected host. The dynamics of susceptible, infected, recovered and cross-immune (SIRC) classed-based model having cross-immune and time-delay in the transmission for spread of COVID-19 abbreviated as (SIRC-CTC-19) are investigated in this study using an intelligent numerical computing paradigm based on the Levenberg–Marquardt Method backpropagated by neural networks (LM-BPNN). The model is mathematically governed by a system of ordinary differential equations that depicts the four nodes as susceptible, infected, recovered and cross-immune ones (SIRC) nodes with cross-immune class and time-delay in transmission components for COVID-19 dissemination (CTC-19). The reference solution of the SIRC model for the spread of COVID-19 is produced by using the explicit Runge–Kutta method for the many scenarios of this model arising from altering delay with regard to time. This reference solution permits the use of evolutionary computing to solve the SIRC-CTC-19 using train, validate and test techniques. The proposed LM-BPNN method’s accuracy has been proven by its results overlapping with explicit Runge–Kutta results Calculation of regression metrics, error analysis of histogram illustrations and learning curves on MSE effectively augment the LM-BPNN’s accuracy, convergence and reliability in solving the SIRC-CTC-19 model. [ FROM AUTHOR] Copyright of International Journal of Modern Physics B: Condensed Matter Physics;Statistical Physics;Applied Physics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Mortality of Mechanically Ventilated COVID-19 Patients in Traditional versus Expanded Intensive Care Units in New York.

Rationale: During the first wave of the coronavirus disease (COVID-19) pandemic in New York City, the number of mechanically ventilated COVID-19 patients rapidly surpassed the capacity of traditional intensive care units (ICUs), resulting in health systems utilizing other areas as expanded ICUs to provide critical care. Objectives: To evaluate the mortality of patients admitted to expanded ICUs compared with those admitted to traditional ICUs. Methods: Multicenter, retrospective, cohort study of mechanically ventilated patients with COVID-19 admitted to the ICUs at 11 Northwell Health hospitals in the greater New York City area between March 1, 2020 and April 30, 2020. Primary outcome was in-hospital mortality up to 28 days after intubation of COVID-19 patients. Results: Among 1,966 mechanically ventilated patients with COVID-19, 1,198 (61%) died within 28 days after intubation, 46 (2%) were transferred to other hospitals outside of the Northwell Health system, 722 (37%) survived in the hospital until 28 days or were discharged after recovery. The risk of mortality of mechanically ventilated patients admitted to expanded ICUs was not different from those admitted to traditional ICUs (hazard ratio [HR], 1.07; 95% confidence interval [CI], 0.95-1.20; P = 0.28), while hospital occupancy for critically ill patients itself was associated with increased risk of mortality (HR, 1.28; 95% CI, 1.12-1.45; P < 0.001). Conclusions: Although increased hospital occupancy for critically ill patients itself was associated with increased mortality, the risk of 28-day in-hospital mortality of mechanically ventilated patients with COVID-19 who were admitted to expanded ICUs was not different from those admitted to traditional ICUs.

COVID-19 backlash: Psycho-social impacts of outbreak in Pakistan

Purpose: This paper aimed to examine the psycho-social aspects of coronavirus disease 2019 (COVID-19) in Pakistan. The study was conducted in Pakistan by using an online survey technique. The rationale to opt for this method was mainly based on the country's lock-down situations, social distancing and for the care of respondents. Design/methodology/approach: A total of 1,536 individuals participated from different parts of the country. An attitudinal scale was administered consisting of statements to measure (dis)agreement of the individuals facing the current situations of COVID-19. The ethical considerations and confidentiality of the respondents were opted by describing the purpose of research on the first page of the questionnaire. Findings: The study findings showed that the cost of personal protective equipment (PPE), social isolation and loss of intimacy have favourable positive effects on the psychological problems of individuals through the mediation of fake news and misinformation during COVID-19. Furthermore, the study findings were interpreted as per the effects of current situations of epidemic, i.e. COVID-19 on the psycho-social life of individuals. Research limitations/implications: This paper is purely limited to the quantitative approach including variables, i.e. COVID-19, risk of infection, social distancing, cost of PPE, social isolation, fake news and psychological problems. Practical implications: The present research will enhance the awareness and knowledge regarding psychological problems faced by the individuals during COVID-19. It will be a significant addition to the existing body of knowledge in the field of health and well-being. It will also provide guidelines to students, research scholars, policymakers and academicians to develop policies in future to improve the health of people during epidemics such as COVID-19 and similar nature of outbreak in the future. Originality/value: This paper focused on an important gap in the research on COVID-19 in the country in the context of COVID-19, risk of infection, social distancing, cost of PPE, social isolation, fake news and psychological problems. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Effects of Occupational Stress, Self-Efficacy and Mental Health During the Pandemic on Hospital Sanitation Workers in Malaysia.

COVID-19 rapidly spread across the world, constituting a public health disaster unlike any other experienced in decades. The impact exerted on workplaces and their employees was dramatic, and an immense burden fell on healthcare provision globally. Along with "front-line" healthcare staff, sanitation workers at hospitals also had to cope with additional workloads, making them vulnerable to psychological trauma and affecting their quality of life at establishments. This study investigated how the factors of occupational stress, self-efficacy (belief in the capacity to carry out a task well) and mental health altered the WRQoL (Work-Related Quality of Life) of employees carrying out sanitation duties at hospitals in Malaysia. To this end, a survey translated into the Malay language was conducted among 449 such workers during a so-called "recovery movement control order", i.e. quarantine and control measures pertaining to an outbreak of Coronavirus disease. Research involved co-variance-based structural equation modeling, performed in IBM-AMOS-26 software, in order to discern the causal relationship of the aforementioned factors on WRQoL. Results revealed a high level of occupational stress, diminished self-efficacy and poor mental health among the employees surveyed. Such stress directly impacted the WRQoL of the second factor alongside an indirect effect on that of the third, i.e. anxiety stemming from potentially catching the virus and the experience of having to disinfect facilities for treating patients, undertake cleaning duties, and move corpses.

Maximal Product and Symmetric Difference of Complex Fuzzy Graph with Application

A complex fuzzy set (CFS) is described by a complex-valued truth membership function, which is a combination of a standard true membership function plus a phase term. In this paper, we extend the idea of a fuzzy graph (FG) to a complex fuzzy graph (CFG). The CFS complexity arises from the variety of values that its membership function can attain. In contrast to a standard fuzzy membership function, its range is expanded to the complex plane's unit circle rather than [0,1]. As a result, the CFS provides a mathematical structure for representing membership in a set in terms of complex numbers. In recent times, a mathematical technique has been a popular way to combine several features. Using the preceding mathematical technique, we introduce strong approaches that are properties of CFG. We define the order and size of CFG. We discuss the degree of vertex and the total degree of vertex of CFG. We describe basic operations, including union, join, and the complement of CFG. We show new maximal product and symmetric difference operations on CFG, along with examples and theorems that go along with them. Lastly, at the base of a complex fuzzy graph, we show the application that would be important for measuring the symmetry or asymmetry of acquaintanceship levels of social disease: COVID-19.

COVID-19 black swan and personal protective equipment (PPE) in Pakistan

Purpose>This paper aimed to examine the sources of information and use of personal protective equipment (PPE) during the COVID-19 pandemic in the province of Punjab, Pakistan. The COVID-19 pandemic affected at a large level of all social institutions including the healthcare system of the countries.Design/methodology/approach>The study was conducted in Pakistan by using an online survey technique. The rationale to opt for this method was based on the country’s lockdown situations, social distancing and the care of the respondents. A total of 847 individuals from different parts of the Punjab province participated in the study. An attitudinal scale was administered, which consisted of statements to measure (dis)agreement among the individuals on current situations of the COVID-19 pandemic. The ethical considerations and confidentiality of the respondents were opted by describing the purpose of research on the first page of the questionnaire.Findings>The study findings revealed that peer group, signs and symptoms of COVID-19 pandemic and causes and consequences of COVID-19 pandemic had favourable positive effects on the use of PPE by individuals through the mediation of fear of infection during COVID-19 pandemic. Furthermore, the study findings were interpreted as per the effects of current situations of COVID-19 on the sources of information and the use of PPE by individuals.Originality/value>This study focused on an important gap in the research on COVID-19 pandemic in the country in terms of mass media, health practitioners, peer group, fear of infection and use of PPE.

Performance of Academic Staff during COVID-19 Pandemic-Induced Work Transformations: An IPO Model for Stress Management

The COVID-19 pandemic has adversely affected all spheres of services-related business, including the higher education sector. As a pre-emptive measure, almost all traditional educational institutions have been transformed into virtual organizations. This pandemic-induced work transition has created stress among academic staff and has hampered their performance. The present study aims to examine the impact of leadership behaviors, e-training, and employment security on the stress management process, consequently improving employee performance during and after the pandemic. Based on the IPO (input–process–output) model, this study examines the effect of leadership behavior, e-training, and employment security on teaching staff’s tasks and adaptive and contextual performance, mediated by stress management. To test the conceptual model, data were collected from the teaching staff of Malaysian universities. The structural equation modeling technique was used for data analysis, while bootstrapping with the maximum likelihood estimator was used to confirm the mediational role of stress management. The study revealed that task- and relation-oriented leadership behavior, e-training, and employment security positively influence stress management and employee performance in virtual organizations. Moreover, stress management acts as a full mediator in the relationship between leadership behavior and employee performance, while partial mediation occurs between e-training, employment security, and employee performance. This study offers valuable insights into the literature by proposing leadership behavior, e-training, and employment security as input in the stress management process to attain the performance output of teaching staff. Higher education institutions should come forward to assist their teaching employees in managing their stress levels for better outcomes.

Performance Evaluation of Soft Computing Approaches for Forecasting COVID-19 Pandemic Cases.

An unexpected outbreak of deadly Covid-19 in later part of 2019 not only endangered the economies of the world but also posed threats to the cultural, social and psychological barriers of mankind. As soon as the virus emerged, scientists and researchers from all over the world started investigating the dynamics of this disease. Despite extensive investments in research, no cure has been officially found to date. This uncertain situation rises severe threats to the survival of mankind. An ultimate need of the time is to investigate the course of disease transfer and suggest a future projection of the disease transfer to be enabled to effectively tackle the always evolving situations ahead. In the present study daily new cases of COVID-19 was predicted using different forecasting techniques; Autoregressive Integrated Moving Average (ARIMA), Exponential Smoothing/Error Trend Seasonality (ETS), Artificial Neural Network Models (ANN), Gene Expression Programming (GEP), and Long Short-Term Memory (LSTM) in four countries; Pakistan, USA, India and Brazil. The dataset of new daily confirmed cases of COVID-19 from the date on which first case was registered in the respective country to 30 November 2020 is analyzed through these five forecasting models to forecast the new daily cases up to 31st January 2020. The forecasting efficiency of each model was evaluated using well known statistical parameters R 2, RMSE, and NSE. A comparative analysis of all above-mentioned models was performed. Finally, the study concluded that Long Short-Term Memory (LSTM) neural network-based forecasting model projected the future cases of COVID-19 pandemic best in all the selected four stations. The accuracy of the model ranges from coefficient of determination value of 0.85 in Brazil to 0.96 in Pakistan. NSE value for the model in India is 0. 99, 0.98 in USA and Pakistan and 0.97 in Brazil. This high-accuracy forecast of COVID-19 cases enables the projection of possible peaks in near future in the aforementioned countries and, therefore, prove to be helpful in formulating strategies to get prepared for the potential hard times ahead.

Bilateral Spontaneous Pneumothorax in a COVID-19 and HIV-Positive Patient: A Case Report.

This case report describes a 60 year-old Black-American male with a past medical history of human immunodeficiency virus (HIV) infection and hyperthyroidism, who suffered a bilateral spontaneous pneumothorax (SP) in the setting of coronavirus disease 2019 (COVID-19) pneumonia. SP is a well-established complication in HIV-positive patients and only recently has been associated with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. While HIV and COVID-19 infections have been independently linked with increased risk of SP development, it is unknown if both infections interact in a synergistic fashion to exacerbate SP risk. According to the Centers for Disease Control and Prevention (CDC), patients living with HIV have a higher risk of developing severe COVID-19 infection and the mechanism remains to be elucidated. To the best of our knowledge, this is the first report of a HIV-positive patient, who in the setting of SARS-CoV-2 infection, developed bilateral apical spontaneous pneumothorax and was later found to have a left lower lobe tension pneumothorax. This case highlights the importance of considering SP on the differential diagnosis when HIV-positive patients suddenly develop respiratory distress in the setting of SARS-CoV-2 infection.

Intubated COVID-19 predictive (ICOP) score for early mortality after intubation in patients with COVID-19.

Patients with coronavirus disease 2019 (COVID-19) can have increased risk of mortality shortly after intubation. The aim of this study is to develop a model using predictors of early mortality after intubation from COVID-19. A retrospective study of 1945 intubated patients with COVID-19 admitted to 12 Northwell hospitals in the greater New York City area was performed. Logistic regression model using backward selection was applied. This study evaluated predictors of 14-day mortality after intubation for COVID-19 patients. The predictors of mortality within 14 days after intubation included older age, history of chronic kidney disease, lower mean arterial pressure or increased dose of required vasopressors, higher urea nitrogen level, higher ferritin, higher oxygen index, and abnormal pH levels. We developed and externally validated an intubated COVID-19 predictive score (ICOP). The area under the receiver operating characteristic curve was 0.75 (95% CI 0.73-0.78) in the derivation cohort and 0.71 (95% CI 0.67-0.75) in the validation cohort; both were significantly greater than corresponding values for sequential organ failure assessment (SOFA) or CURB-65 scores. The externally validated predictive score may help clinicians estimate early mortality risk after intubation and provide guidance for deciding the most effective patient therapies.

THE IMPACT OF CORONA VIRUS DISEASE-19(COVID-19) ON POSTGRADUATE PAEDIATRIC RESIDENTS

ABSTRACT Objective: To explore the impact of corona virus disease-19 pandemic on postgraduate paediatric residents. Study Design: Mixed method study. Place and Duration of Study: Pak Emirates Military Hospital Rawalpindi, from Apr to May 2020. Methodology: Post graduate paediatric residents working in Pak Emirates Military Hospital and Combined Military Hospital Rawalpindi, Pakistan were included by purposive sampling technique. Sample size was predetermined, included all(forty total) residents of two hospitals. Participant‘s written response was obtained on an open ended self administered-questionnaire distributed in person. All enrolled participants responded. Thematic analysis of data was done. Results: The participants were predominantly female(n: 30, 75%) of age range 31-35(50%) years. The first theme category was Impact on personal life The residents reported an unprecedented physical, psychological and social stress. The second category was Family life during COVID-19 Residents had to share extra family/ financial/health responsibilities of their families. Professional duties and training was another theme category. Residents worked in new context of environment, fear of contagion, managing interpersonal / interprofessional relationships, less volume of patients/clinical experience / skills and new e-learning modalities. Challenges and suggestions to cope is another category, where residents suggested strategies and sources to improve patient care, their well being and training during pandemic. Conclusion: The residents had experienced intensive physically, emotional and social stress. Most of them behaved with resilience and extreme professional dedication. Different competencies of training are being affected. Concerned authorities must adopt new strategies to support resident‘s training and personal life.

Disc Diffusion Testing of Azithromycin Against Clinical Isolates of Typhoidal Salmonellae: A Diagnostic Conundrum.

INTRODUCTION:  Typhoid remains a major healthcare problem in low and middle-income countries. The emergence of extremely drug-resistant (XDR) typhoid strains from the Indian subcontinent has led to very limited therapeutic options. Azithromycin being the only oral option for XDR typhoid faces a threat of rapid resistance due to its overuse after the COVID-19 pandemic. OBJECTIVE:  To evaluate the reliability of azithromycin disc diffusion testing against clinical isolates of typhoidal salmonellae in comparison with E-test minimum inhibitory concentrations (MICs). STUDY DESIGN:  This is a cross-sectional validation study. Place and duration of the study: The Department of Microbiology, Pakistan Navy Ship Shifa hospital, Karachi from June 1 to December 31, 2020. METHODOLOGY:  Antimicrobial susceptibility was performed by Kirby Bauer disc diffusion method for 60 isolates including Salmonella enterica ser. Typhi and Paratyphi A using Clinical Laboratory Standard Institute (CLSI) guidelines. MICs by the E-test method were determined for Azithromycin only. RESULTS:  A significant proportion of the isolates (55%) had high azithromycin MIC in the wild-type distribution range (8-16 µg/ml). Ten (16.6%) isolates showed false resistance, i.e., zone diameter <13 mm by disc diffusion method when compared to E-test MIC results. Isolates with MICs close to breakpoint, i.e., 16 µg/ml were more likely to show discordant results. The sensitivity, specificity, negative predictive value, positive predictive value, and diagnostic accuracy of the disc diffusion method versus E-test were 100%, 83%, 100%, 9%, and 83%, respectively. CONCLUSIONS:  Disc diffusion method as recommended by CLSI is not reliable for azithromycin susceptibility testing particularly for isolates with high MICs in the susceptible range. The E-test method may be a better alternative to disc diffusion provided appropriate training is done prior to its application.

Emerging nanotechnology role in the development of innovative solutions against COVID-19 pandemic.

The COVID-19 outbreak is creating severe impressions on all facets of the global community. Despite strong measures worldwide to try and re-achieve normalcy, the ability of SARS-CoV-2 to survive sturdy ecological settings may contribute to its rapid spread. Scientists from different aspects of life are working together to develop effective treatment strategies against SARS-CoV-2. Apart from using clinical devices for patient recovery, the key focus is on developing antiviral drugs and vaccines. Given the physical size of the SARS-CoV-2 pathogen and with the vaccine delivery platform currently undergoing clinical trials, the link between nanotechnology is clear, and previous antiviral research using nanomaterials confirms this link. Nanotechnology based products can effectively suppress various pathogens, including viruses, regardless of drug resistance, biological structure, or physiology. Thus, nanotechnology is opening up new dimensions for developing new strategies for diagnosing, preventing, treating COVID-19 and other viral ailments. This article describes the application of nanotechnology against the COVID-19 virus in terms of therapeutic purposes and vaccine development through the invention of nanomaterial based substances such as sanitizers (handwashing agents and surface disinfectants), masks and gowns, amongst other personal protective equipment, diagnostic tools, and nanocarrier systems, as well as the drawbacks and challenges of nanotechnology that need to be addressed.

Pneumatosis Intestinalis in the Setting of COVID-19: A Single Center Case Series From New York.

This case series reviews four critically ill patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [coronavirus disease 2019 (COVID-19)] suffering from pneumatosis intestinalis (PI) during their hospital admission. All patients received the biological agent tocilizumab (TCZ), an interleukin (IL)-6 antagonist, as an experimental treatment for COVID-19 before developing PI. COVID-19 and TCZ have been independently linked to PI risk, yet the cause of this relationship is unknown and under speculation. PI is a rare condition, defined as the presence of gas in the intestinal wall, and although its pathogenesis is poorly understood, intestinal ischemia is one of its causative agents. Based on COVID-19's association with vasculopathic and ischemic insults, and IL-6's protective role in intestinal epithelial ischemia-reperfusion injury, an adverse synergistic association of COVID-19 and TCZ can be proposed in the setting of PI. To our knowledge, this is the first published, single center, case series of pneumatosis intestinalis in COVID-19 patients who received tocilizumab therapy.

An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19.

Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases.