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COVID-19 pandemic has paused many ongoing research projects and unified researchers' attention to focus on COVID-19 related issues. Our project traces 712,294 scientists' publications related to COVID-19 for two years, from January 2020 to December 2021, in order to detect the dynamic evolution patterns of COVID-19 collaboration network over time. By studying the collaboration network of COVID-19 scientists, we observe how a new scientific community has been built in preparation for a sudden shock. The number of newcomers grows incrementally, and the connectivity of the collaboration network shifts from loose to tight promptly. Even though every scientist has an equal opportunity to start a study, collaboration disparity still exists. Following the scale-free distribution, only a few top authors are highly connected with other authors. These top authors are more likely to attract newcomers and work with each other. As the collaboration network evolves, the increase rate in the probability of attracting newcomers for authors with higher degree increases, whereas the increase rates in the probability of forming new links among authors with higher degree decreases. This highlights the interesting trend that COVID pandemic alters the research collaboration trends that star scientists are starting to collaborate more with newcomers, but less with existing collaborators, which, in certain way, reduces the collaboration disparity. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The management of Covid-19 affected patients is a very difficult task. The current healthcare system of India is not able to cope with the enormous flow of patients and is in a dire need for improvement. This implementation paper provides a system which will manage all the affected patients right from the time they are Covid-19 positive till the time they are treated and discharged. This paper includes all the technical details of a fully implemented healthcare management system which is a significant improvement in the current system. The proposed system is a cross platform multi user web app which can be used by multiple stakeholders to carry out smooth management of the patients. It consists of a lot of key features like dynamic location-wise patient status, an accurate tracking system of ambulances, a statistical trend analysis of patients and categorical report generation of patients. This system aims to help the medical Front-liners in efficient management of Covid-19 patients, and it is a common site for all the different health workers like field workers and medical officers to work togetherand fight against this deadly disease affecting our country. © 2022 IEEE.
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Background: Clinical outcome and parenchymal lung abnormalities (PLA) data from hospitalized patients with COVID 19 pneumonia are limited. Objective(s): (1) Understand and compare the patterns of PLA on high resolution computed tomographic (HRCT) at admission, 4-8 weeks post-admission in all patients and 10-12 weeks post-admission in a subgroup of patients (2) follow up their general health status on phone 6 months post admissionMethods: Prospective, observational study of consecutive adult patients hospitalized with RT-PCR confirmed COVID-19 pneumonia in a tertiary centre, India. Clinical data and HRCT image patterns and distribution of PLA at admission, 4-8 weeks in all patients and at 10-12 weeks in a subgroup of patients were analysed using a novel, composite radiological score (CRS). Surviving patients were followed up telephonically 6 months later. Finding(s): Of 179 patients, HRCT features were ground glass opacity (144, 80.4%), consolidation (23, 12.8%) and reticulation (7, 4%) at admission. 74% demonstrated resolving PLA with 14% showing complete resolution at 4-8 weeks. Fine reticulations were seen in 12% at 8 weeks and 20% in a subgroup of 44 patients who had persisting symptoms at 10-12 weeks. CRS correlated well with clinical severity and recovery (p=0.003). At 6 months, 144 responded to the phone follow up, reported no functional impairment and had returned to their pre-COVID health status. Conclusion(s): PLA resolved in 88% at 8 weeks and all the 144 patients who were followed up at 6 months reported return to pre-COVID 19 health status. This is quite reassuring amidst concerns of 'long COVID'.
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Task scheduling scenarios require the system designers to have complete information about the resources and their capabilities, along with the tasks and their application-specific requirements. An effective task-to-resource mapping strategy will maximize resource utilization under constraints, while minimizing the task waiting time, which will in-turn maximize the task execution efficiency. In this work, a two-level reinforcement learning algorithm for task scheduling is proposed. The algorithm utilizes a deep-intensive learning stage to generate a deployable strategy for task-to-resource mapping. This mapping is re-evaluated at specific execution breakpoints, and the strategy is re-evaluated based on the incremental learning from these breakpoints. In order to perform incremental learning, real-time parametric checking is done on the resources and the tasks;and a new strategy is devised during execution. The mean task waiting time is reduced by 20% when compared with standard algorithms like Dynamic and Integrated Resource Scheduling, Improved Differential Evolution, and Q-learning-based Improved Differential Evolution;while the resource utilization is improved by more than 15%. The algorithm is evaluated on datasets from different domains like Coronavirus disease (COVID-19) datasets of public domain, National Aeronautics and Space Administration (NASA) datasets and others. The proposed method performs consistently on all the datasets. © 2023 IETE.
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Introduction: The impact of the COVID-19 pandemic on substance use in children and adolescents is not well understood. Although lockdowns have largely ended, there is concern regarding longer time effects on development. Presentations to emergency department (ED) settings may provide an indicator of substance use associated with a relatively high level of acuity. The aim of the current study is to describe trends in pediatric (0-17yo) presentations associated with substance use diagnoses to emergency services at an academic center in a Southwestern state since onset of the COVID-19 pandemic and how these compare to rates prior to onset of COVID pandemic. Method(s): Retrospective chart review of electronic medical record data from July 2019-March 2022. Data included all visits by pediatric subjects (0-17yo) associated with a substance-use related diagnosis to acute care settings within the University of New Mexico Health Sciences Center system. Data is summarized within 3-month quarters (Jan- Mar, April-June, July-Sept, Oct-Dec) to allow comparison of numbers presenting during similar periods of year. March 2020 was when broad lockdowns were started in New Mexico. Variables included total number of visits, sex (M, F), race, ethnicity (Hispanic/Non-Hispanic), age range (0-9, 10-14, 15- 17yo), insurance (private, Medicaid, other government, selfpay/ other), whether seen by mental health provider, ED length of stay (LOS) (1 hour or less, 2-5 hours, 6 hours or more), and substance-related diagnosis. Variables are compared between each quarter using a generalized linear model. Result(s): There were 938 visits total during this time (467 male, 467 females, 4 missing). 598 were Hispanic, 274 non- Hispanic White, 147 Native American, 45 Black, 8 Asian, 4 NH/PI, and 146 declined or unknown. The vast majority of visits were in adolescents 15-17yrs old. The most common diagnosis was cannabis-related disorder at 306 encounters, followed by alcohol n=303. The trajectory of visits from July 2019-March 2022 showed a decline from 98 visits in July-Sept 2019 to 51 visits in April-June 2020, followed by increase to 102 visits in Jan-Mar 2022. Comparisons of equivalent quarters for each year were as follows: Q1 (2020 n=71;2021 n=71, 2022 n=102). Q2 (2020 n=51;2021 n=81). Q3 (2019 n=98;2020 n=75;2021 n=107, 2019-2021). Q4 (2019 n=90;2020 n=57;2021 n=111). There were fewer female visits prior to onset of COVID-19 (n=40 in females vs n=58 in males in 2019 Q3) and decreased further early in the pandemic (N=29 vs 46 in males in 2020 Q3), but then rose more rapidly than males (n=59 female, n=48 male, 2021 Q3). The proportion of visits with LOS 5 hours in Q3 initially decreased from 27.8% of visits(n=25) in 2019 to 19.3% (n=11) in 2020, then increased significantly to 35.1% in 2021 (n=39). There was not a significant effect of other variables. Conclusion(s): The COVID-19 pandemic resulted in a rapid decrease in ED substance-abuse pediatric presentations, which rebounded to levels greater than pre-COVID. Females increased more than males. Visits with longer LOS increased during later pandemic. Future work includes understanding how mental health comorbidities and other socioeconomic stressors may relate to these findings.
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COVID-19 pandemic has paused many ongoing research projects and unified researchers' attention to focus on COVID-19 related issues. Our project traces 712,294 scientists' publications related to COVID-19 for two years, from January 2020 to December 2021, in order to detect the dynamic evolution patterns of COVID-19 collaboration network over time. By studying the collaboration network of COVID-19 scientists, we observe how a new scientific community has been built in preparation for a sudden shock. The number of newcomers grows incrementally, and the connectivity of the collaboration network shifts from loose to tight promptly. Even though every scientist has an equal opportunity to start a study, collaboration disparity still exists. Following the scale-free distribution, only a few top authors are highly connected with other authors. These top authors are more likely to attract newcomers and work with each other. As the collaboration network evolves, the increase rate in the probability of attracting newcomers for authors with higher degree increases, whereas the increase rates in the probability of forming new links among authors with higher degree decreases. This highlights the interesting trend that COVID pandemic alters the research collaboration trends that star scientists are starting to collaborate more with newcomers, but less with existing collaborators, which, in certain way, reduces the collaboration disparity. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 presents severely in persons with immunocompromised states such as diabetes mellitus. Steroids are used in the management of COVID-19. The use of steroids in immunocompromised persons increases the chances of opportunistic infections. Mucormycosis infects immunocompromised individuals. The aim of this systemic review was to study the clinico-epidemiological features of mucormycosis in patients of COVID-19. PubMed, Medline, Embase, and Google Scholar were searched for 'mucormycosis', 'COVID-19', and 'SARS-Cov 2'. A total of 30 studies were included in this study, which included 22 case reports and 8 original articles. The median age of patients was 54.80 years;79.56% (74/93) were diabetic. Steroid administration history was present in 74.19% (69/93) of patients. Rhino-orbital mucormycosis constituted 46.98% (39/83) of the cases, rhino-orbital-cerebral type in 37.35% (31/83) cases, pulmonary mucormycosis in 10.84% (9/83) cases, 1 case of gastric mucormycosis, 1 case of cutaneous mucormycosis, 1 case of palatal mucormycosis, and 1 case of disseminated mucormycosis. The median duration of presentation of mucormycosis was 14 days after hospital admission. The total number of deaths was reported in 32.26% (30/93) of the cases. The most common species found was Rhizopus, and amphotericin B was the most common antifungal administered. The COVID-19 pandemic is creating a massive pool of susceptible patients having poorly controlled diabetes mellitus and receiving steroids for COVID-19 management, thus creating an unholy alliance with mucormycosis. Mucormycosis started as a new epidemic in India, which is an otherwise rare opportunistic fungal infection. © 2022 Medical Journal of Dr. D.Y. Patil Vidyapeeth ;Published by Wolters Kluwer - Medknow.
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The global outbreak of SARS-CoV-2, COVID-19 a novel strain of coronaviruses, emerged from Wuhan city of China in December 2019 and was later announced as global pandemic by World Health Organization on March 11, 2020. The infection spread globally and infected over 190 million people with a mortality rate of around 2%. Combating the disease is difficult as no specific therapeutics and vaccines are yet available against the novel coronavirus. Hence, early detection and containment of infected individuals are the best possible approaches to reduce the spread of the infection. The chapter summarized the major diagnostic tools used for detection of COVID-19 along with their advantages and disadvantages. Additionally, the potential therapeutic approaches are also discussed with their current developmental status. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Purpose: The COVID-19 pandemic and technological advancements have enabled employees to telework. Referring to this emerging phenomenon, the authors aim to examine how employees' levels of trust in management mediated by psychological well-being impact their performance as they telework. Deploying the theoretical lens of person-environment misfit, the authors also explore the role of technostress in the trust-wellbeing-performance relationship. Design/methodology/approach: The data was collected from 511 full-time service sector employees across Indian organizations through a structured survey questionnaire. The proposed moderation-mediation model for this study was tested using structural equation modeling and bootstrapping method. Findings: Structural equation modeling results indicate that trust in management significantly impacts employee performance while teleworking. While psychological well-being was observed as a significant mediator, technostress played the moderator role in the trust-performance relationship. The moderated-mediation effect of psychological well-being in the trust-performance relationship was stronger when technostress was low and weaker when technostress was high. Research limitations/implications: The authors extend the person-environment misfit theory in the context of telework, highlighting the role of technostress that may impact the trust-wellbeing- performance relationship in such work settings. Practical implications: The study informs leaders and managers on balancing delicate aspects such as employee trust and well-being that significantly impact performance as they telework. The authors also highlight the critical role of managers in respecting employees' personal and professional boundaries to alleviate technostress. Originality/value: The authors make a novel theoretical contribution to the emerging literature on teleworking by examining the trust-psychological wellbeing-performance link and the role of technostress in this relationship. © 2022, Emerald Publishing Limited.
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The COVID-19 pandemic has caused unprecedented turmoil necessitating nations to impose lockdowns. Thus, organizations forced employees to work from home (WFH) by leveraging information technology. We explored the impact of WFH on employees during the lockdown. We conducted in-depth interviews of 24 employees across manufacturing and technology-enabled sectors in India and analyzed the data using Gioia’s methodology. Four dimensions emerged from the impact of WFH on employees: role improvisation, stress, isolation, and self-initiated creativity. While some themes were common between the two industrial sectors, other themes varied. For instance, service sector employees reported current work-related stress, whereas manufacturing sector employees reported future-related stress. Interestingly, we discovered sparks of creativity among employees during this period either towards nurturing themselves (technology-enabled sector) or towards solving long-pending organizational issues (manufacturing sector). Most importantly, these creativity sparks were self-initiated. The study is novel as it explores the impact of large-scale WFH enforced during crisis.
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Purpose : Older adults with combined hearing and vision loss (dual sensory loss/DSL) are a highly vulnerable population during the COVID-19 pandemic. Although around 1.1 million older Canadians live with DSL, data are scarce on how COVID-19 affected their access to healthcare during the pandemic. Therefore, the present study explored the impact of COVID-19 on healthcare access for older Canadians with DSL. Methods : We distributed an online survey for healthcare workers who provided services to older adults with DSL during the pandemic. Survey data were collected from 228 Canadian healthcare workers between August and November 2021. Content analysis was used to analyze open-ended qualitative data, whereas descriptive statistics were used for quantitative survey data using SPSS. Results : Almost all healthcare workers felt that COVID-19 has negatively affected their care delivery to older adults with DSL, especially due to physical distancing and use of Personal Protective Equipment. Moreover, those using telehealth with their older clients reported that COVID-19 related shift to telehealth appointments restricted access to healthcare for their clients. Most respondents (91%) felt that older adults with DSL found it difficult to follow pandemic-related physical distancing guidelines in a clinical or health system setting. While 69% of them believed that the health system was not adapted to match the needs of older adults living DSL, 71 % felt healthcare professionals are not adequately trained to meet the needs of this population in pandemic situations such as COVID-19. Conclusions : We concluded that the pandemic has negatively impacted healthcare services to older adults with DSL. The pandemic accentuated the need for equitable care for older adults with DSL, considering the unique challenges experienced by them and their healthcare providers. Our study findings underscored the need for training of healthcare professionals on the communication and accessibility needs of older adults living with DSL.
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Introduction: COVID-19 pandemic has severe consequences for the whole world. Each age group has been affected. Both the pediatric and geriatric populations have been worst affected by COVID-19. Even pregnant females were affected much and especially the neonates of pregnant women with COVID-19. The vulnerability increases in neonates of mothers with COVID-19. There is less literature and guidelines available which discussed the outcomes of neonates of mothers who had COVID-19 during gestation. Aims and Objectives: To find out the effect on the fetus of mothers, who were infected with COVID-19 during gestation. Method(s): This is a retrospective study which considered 120 pregnant women, comprising 60 pregnant females with COVID-19 (study group) and another 60 pregnant females without COVID-19 (control group). The baseline characteristics were obtained from the hospital in both groups and the outcomes were evaluated and analyzed. Result(s): The study found that there are significant differences between the two groups in gestational age at the time of delivery, premature delivery occurred and neonatal death (p<0.05). Conclusion(s): The study has concluded that the presence of COVID-19 in pregnant females caused placental infection affecting the fetus significantly, as evidenced by premature birth and neonatal deaths among the COVID-19 group. Copyright © 2022, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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Due to the Coronavirus (COVID-19) cases growing rapidly, the effective screening of infected patients is becoming a necessity. One such way is through chest radiography. With the high stakes of false negatives being potential cause of innumerable more cases, expert opinions on x-rays are high in demand. In this scenario, Deep Learning and Machine Learning techniques offer fast and effective ways of detecting abnormalities in chest x-rays and can help in identifying patients affected by COVID-19. In this paper, we did comparative analysis of various Machine Learning and Deep Learning techniques on chest x-rays based on accuracy, precision, recall, f1 score, and Matthews correlation coefficient. It was observed that improved results were obtained using Deep Learning. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Introduction: Early and correct identification of the betacoronavirus is important for effective isolation treatment and case management. Real-time polymerase chain reaction (PCR) are consider as a gold standard for the diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2);however, for that, there are a requirement of skilled workforce and elaborate infrastructure. A rapid point of care test known as Truenat Beta CoV and Truenat SARS COV assay were recommended by the Government of India. The aim of the study was to find out the performance of Truenat assay in comparison to four RT-PCR assay kits. Materials and Methods: The cross sectional study was conducted in a COVID-19 testing laboratory in Central India. Forty known Truenat positive sample with different viral load were analyze in selected rtPCR kits from 4 different manufacturers. Results: Of the total of ten very low viral load samples, BGI kit was able to detect six samples, followed by TruePCR six samples, TaqPath five samples and NIV kit were able to detect three samples. Similarly, in the case of low viral load sample, BGI and TaqPath kit were able to detect all the 10 samples followed by NIV kit five samples and TruePCR nine samples respectably. In the case of medium and high viral load samples, all four reverse transcription-PCR (RT-PCR) kits were shown a 100% detection rate. Conclusions: Based on our findings, we believe truenat RT-PCR is a more reliable technique for the detection of SARC-CoV-2. Hence, it should be installed in the healthcare setup for better control of the pandemic.
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Introduction Around 1.1 million older Canadians live with combined hearing and vision impairment (dual sensory loss/DSL). Evidence highlights that they are at a high risk of cognitive impairment, functional decline, social isolation, falls, depression, and mortality. Compared to their non-DSL peers, older adults with DSL experience various challenges in accessing healthcare, which were exacerbated during the COVID-19 pandemic. This study aimed to explore the continuum of geriatric care for older adults with DSL by integrating their perspectives, those of caregivers who accompany them on healthcare visits, and their healthcare providers in Canada during the pandemic. Method We conducted a qualitative study with 32 older Canadians with DSL and their caregivers, and an online survey with 228 healthcare providers across the country. Qualitative interviews were audio-recorded using Zoom and transcribed verbatim, while the survey data were collected using Lime Survey. Thematic analysis was used to analyse qualitative data, whereas descriptive statistics were used for quantitative survey data. Results The findings highlighted the gaps in the continuum of care for this population. The reported gaps were lack of training on DSL among healthcare providers, lack of time and comfort to go beyond one’s specialty, lack or limited support to overcome communication challenges while providing care to older adults with DSL, difficulty in using technologies for virtual/telehealth, presence of comorbidities such as cognitive impairment, and restrictions in caregiver accompaniment during the pandemic. Conclusion Our findings indicate that the continuum of care for this group is negatively affected due to the pandemic, in a disproportionate manner, and structural barriers are experienced by older adults with DSL and their caregivers for access to care. To ensure effective care, healthcare professionals need training on DSL-specific accessibility and communication. A collaborative, cross-disciplinary geriatric care approach with the active involvement of essential care partners is an utmost need.
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While most studies have been reporting the psychological issues being faced by the public due to the global spread of coronavirus and sudden restrictions and changes accompanying it, the present study attempted to explore dynamic human experiences during the COVID-19 pandemic and resultant lockdown, so as to understand the psycho-social factors that acted as adaptive resources or as buffers to maintain a stable mental state amidst this crisis. In-depth telephonic interviews with 30 participants were conducted to explore their experiences in dealing with the COVID-19 pandemic and the lockdown. Thematic analysis performed to identify the positive and protective factors that helped people adapt in a healthy way revealed that although the initial response of the participants to the pandemic was "optimistic bias" followed by downplaying the seriousness of the issue, later they demonstrated increased realization and acceptance to the seriousness of the situation. Upon realizing the situation, their positive psychological resources acted as a buffer against the ill effects of the pandemic, and they used both cognitive and behavioral coping. The study clearly demonstrates that crisis in life is not just a source of stress, anxiety, and uncertainty but also an opportunity to test one's psychological resources to learn and grow.
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Pandemic caused owing to widespread of corona-virus has changed our lives upside down. Covering the face area particularly nose and mouth is the prime need of the hour. Any negligence of not wearing the mask or incorrectly wearing the mask can be hazardous. This necessitates the need of understanding the real importance of wearing the mask appropriately in order to avoid the spread of Covid 19. Knowing the present population of the country, manual monitoring of the individuals is quite difficult. So, this research puts forward the use of deep learning techniques for automatic facemask detection using techniques such as capsule network, ResNet50, Mobile-Net architecture, and Convolution Neural Network. The techniques are validated on the merged dataset taken from MaskedFace-Net dataset and Kaggle (publicly available) based on the performance measures namely accuracy, precision, recall and F1-score. Amongst all, the results showed that capsule neural network achieved superlative performance with the accuracy of around 99% in comparison to other aforesaid deep learning techniques. © 2022, Springer Nature Switzerland AG.
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Background: COVID 19 causes a spectrum of disease. Majority affected are asymptomatic or have febrile mild upper respiratory symptoms. Pulmonary involvement leads to moderate and severe disease. The clinical symptoms range from mild cough and breathlessness to florid ARDS. Early inflammatory pulmonary phase is characterised by alveolitis and acinar shadows (consolidation and organising pneumonia). Methods: This is a prospective observational cohort study of 193 consecutive adult patients who were admitted with RT-PCR confirmed COVID-19 pneumonia to a tertiary hospital in Delhi NCR from March to December 2020, and subsequently presented for clinical follow-up. Demographic, clinical, laboratory parameters, radiological parameters and treatment details were recorded at the time of admission;HRCT Thorax was done at admission (CT1) and at 4-8 week follow up (CT2) in this group of 193 patients. A subset of patients with more severe disease had a follow up CT (CT3) which was done approximately 3 months after CT1. Treatment and Outcome: The treatment given to the patients, depending on the severity of their disease, as per national guidelines was recorded during admission and included the following - Level of oxygen support, steroid, HCQs, Ivermectin, Doxycycline, Remdesivir, Tocilizumab, plasma, LMWH. Oxygen support by the following modes - Nasal prongs, face mask, HFNC (High flow nasal canula), noninvasive ventilation (BiPAP) and ventilatory support was recorded. The outcome of patients was recorded - Those who recovered and those who did not survive. The correlation between clinical variables with clinical severity as well as with extent of lung disease was made.
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As the Medical Council of India (MCI) implemented a new undergraduate curriculum from this academic session onward, the aim was to replace knowledge-centric traditional educational model to a more holistic community-based curriculum based on the domains such as knowledge, skills with emphasis on attitude, communication, and ethics. This implementation requires major reforms in the form of faculty development and resource generation for successful implementation of new course. However, COVID-19 pandemic possesses serious challenges to the implementation of curriculum and its success. This review discusses the possible challenges for the implementation of the new MCI curriculum in face of the coronavirus pandemic and possible strategies to counter it. © 2021 Medical Journal of Dr. D.Y. Patil Vidyapeeth ;Published by Wolters Kluwer - Medknow