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The COVID-19 pandemic resulted in a paradigm shift in the delivery of instruction for students with autism spectrum disorders (ASD), forcing educators, therapists, and behavior analysts to pivot across programming with little lead-time. This chapter first presents the transition to remote learning for one New York City-based applied behavior analytic school for students with autism. Direct instruction (DI) in the remote learning format is then recommended as an ideal teaching methodology. The chapter then presents preliminary support for the remote use of DI through quantitative data for seven of the learners in this ABA school. Later, these results are discussed with respect to key design features of DI and the applicability of these findings to students in circumstances that would normally preclude them from receiving high quality instruction. The chapter concludes with a brief tutorial to guide educators in adopting this methodology to remote settings. © 2023, IGI Global. All rights reserved.
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OBJECTIVE: Wide arrays of laboratory parameters have been proposed by many studies for prognosis in COVID-19 patients. In this study, we wanted to determine if the International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score in addition to certain clinical and laboratory parameters would help in predicting mortality. We wanted to determine if a greater severity score on chest x-ray at presentation translated to poor patient outcomes using the COVID-19 chest radiography score. MATERIAL AND METHODS: This retrospective study was conducted at SDS TRC and Rajiv Gandhi Institute of chest diseases, Bangalore from March 2021 to June 2021. This study included 202 real-time-polymerase chain reaction-positive COVID-19 patients aged above 18 years admitted to the intensive care unit of our hospital. Demographic characteristics and baseline hematological and inflammatory markers (serum C-reactive protein, lactate dehydrogenase, troponin-I, ferritin, and d-dimer) were collected. Radiological severity on a chest x-ray was assessed using the validated COVID-19 chest radiography score. The International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score was assigned to each patient within 24 hours of intensive care unit admission. Outcome studied was in-hospital mortality. RESULT(S): The overall mortality was 54.9% (111 cases). Age more than 50 years, >4 days of symptoms, peripheral oxygen saturation/ fraction of inspired oxygen ratio less than 200, elevated serum lactate dehydrogenase >398.5 IU/L, and hypoalbuminemia (<2.95 g/dL) were detected as independent predictors of mortality. A significant correlation of risk stratification with mortality (P = .057) was seen with International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score. There was no significant correlation between the COVID-19 chest radiography score and mortality. CONCLUSION(S): Age >50 years, peripheral oxygen saturation/fraction of inspired oxygen ratio <200, mean symptom duration of >4 days, elevated serum lactate dehydrogenase, and hypoalbuminemia are independent predictors of mortality in severe COVID-19 pneumonia. International Severe Acute Respiratory and Emerging Infections Consortium-Coronavirus Clinical Characterization Consortium score was different in the survivors and deceased.Copyright © Author(s).
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Coronavirus disease (COVID-19) has been declared as a pandemic by WHO with thousands of cases being reported each day. Numerous scientific articles are being published on the disease raising the need for a service which can organize, and query them in a reliable fashion. To support this cause we present AWS CORD-19 Search (ACS), a public, COVID-19 specific, neural search engine that is powered by several machine learning systems to support natural language based searches. ACS with capabilities such as document ranking, passage ranking, question answering, knowledge graph based ranking and biomedical topic classification provides a scalable solution to COVID-19 researchers and policy makers in their search and discovery for answers to high priority scientific questions. We present a quantitative evaluation and qualitative analysis of the system against other leading COVID-19 search platforms. ACS is top performing across these systems yielding quality results which we detail with relevant examples in this work. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Introduction: In the fight against COVID-19, doctors, nurses, administrative staff, police personnel and other supporting staff have been in the frontline providing emergency services. While performing their duties, they are at risk of getting infections and transmitting them to their near and dear ones. This can lead to increased psychological stress levels among them. This study was conducted to assess the level of stress among health care workers and police personnel during the COVID-19 pandemic period in Delhi. Methodology: This is a cross-sectional study among the COVID-19 warriors working in designated COVID-19 hospitals using Google forms. The relationship between various social, demographic, and administrative factors and the level of stress experienced by the study subjects was assessed using Perceptive Stress Scale (PSS-10). Results: The results describe heightened severity of perception of stress among the study cohort. We found at least 10 risk factors that showed statistically significant association with increased TPSS in the studied cohort group. Conclusion: There is an urgent need for screening, proper diagnosis, and management of psychiatric issues among FLCWs, and for expanding mental health services for reducing stress among the target population. © 2021 Indian Society for Malaria and Communicable Diseases. All rights reserved.
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Antibody test is used in seroprevalence surveys for Coronavirus Disease-2019 (COVID-19). Apart from estimating the proportion of population infected, they can help in drawing plenty of inferences about the extent, progress and course of the pandemic. They can potentially be helpful in planning and prioritising vaccine distribution by providing a broad overview into proportion of population immune to COVID-19 in a geographic area and also help in understanding the pockets of high or low seroprevalence. This review was conducted with an aim of compiling an updated and comprehensive information about the seroprevalence of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antibody in various pockets of India in the year 2020, and thus to understand the current pandemic situation in the country. A total of 35 studies were identified through all resources and detailed review was carried out based on these studies. Additionally, indicators were devised to understand and compare the results. Results were further classified into states/Union Territories (UTs), districts, Sub-district regions. The study findings show that the anti SARS-CoV-2 antibodies seroprevalence estimates vary across different regions (states/UTs, districts, sub district regions) of India and can increase or in some instances decrease over the course of time. The study concludes by asserting the need for repeated seroprevalence surveys as well as follow-up studies for current pandemic surveillance.
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Background: Patients with autoimmune rheumatic diseases (AIRD) may be at an increased risk for COVID-19 infection and poorer outcomes when compared with the general population. We undertook this study to estimate the risk of COVID-19 infection in our AIRD population and determine parameters which contribute to its occurrence. Methods: We prospectively recruited all consecutive AIRD patients on immunosuppressive therapy from 14 specialist rheumatology centers across south Indian state of Karnataka during current COVID-19 pandemic and followed them longitudinally. Results: Among 3807 participants, the majority were women (2.9:1), mean age was 43.8 (+14.3) years, rheumatoid arthritis (52.1%), and systemic lupus erythematosus (14.8%) were the most frequent diagnosis. Twenty-three (0.6%) patients contracted SARS-CoV-2 infection. Age >60 years (P = 0.01), diabetes (P = 0.009), hypertension (P = 0.001), preexisting lung disease (P = 0.0002), current prescription of either angiotensin-converting enzyme inhibitor or angiotensin receptor blockers (P = 0.01), and higher glucocorticoids dosage (P = 0.002) were identified as potential risk factors in our cohort. The past use of cyclophosphamide (P = 0.0001) or mycophenolate mofeti (P = 0.003) or biologics (P = 0.001) also had a significant association with COVID-19 infection. Hydroxychloroquine use did not influence occurrence or outcome. The presence of underlying lung disease (relative risk - 3.08, 95% confidence interval - 1.21, 8.44, P = 0.029) was the only independent risk factor associated with the risk of COVID positivity in the multivariate analysis. Incidence rate of COVID-19 infection was similar to that of the general population (P = 0.22). Conclusions: The incidence of SARS CoV-2 infection in AIRD population is comparable to the general population. Underlying lung disease was the most important risk factor apart from older age, diabetes, hypertension, and a higher glucocorticoid dosage. © 2021 Wolters Kluwer Medknow Publications. All rights reserved.