Sudden lockdown repeals, social mobility, and COVID-19: Evidence from a judicial natural experiment

The imposition and lifting of COVID-19 lockdown orders were among the most heatedly debated policies during the pandemic. Credible empirical evaluations of the effects of reopening policies are difficult because policymakers often explicitly linked sustained reductions in COVID-19 cases to the lifting of lockdown orders. This hardwired policy endogeneity creates challenges in isolating the causal effects of lifting of lockdown orders on social mobility and public health. To overcome simultaneity bias, we exploit a natural experiment generated by the Wisconsin Supreme Court when it abolished Wisconsin's "Safer at Home” order on separation-of-powers grounds. We capitalize on this sudden, dramatic, and largely unanticipated termination of a statewide lockdown order to estimate its effect—relative to a more gradual scaling back of restrictions—on social mobility and COVID-19 case growth. First, using anonymized smartphone data from SafeGraph and a synthetic control design, we find that termination of COVID-related restrictions had small and short-lived negative impacts on social distancing. Then, using data on case and mortality rates, we find no evidence that the Wisconsin Supreme Court decision impacted COVID-19 growth up to a month following the repeal. These findings suggest that in the absence of carrying new information, sudden lockdown repeals may generate smaller behavioral responses than policymakers anticipate. © 2023 The Authors. Journal of Empirical Legal Studies published by Cornell Law School and Wiley Periodicals LLC.

A Learning Analytics Approach Using Social Network Analysis and Binary Classifiers on Virtual Resource Interactions for Learner Performance Prediction

The COVID-19 pandemic induced a digital transformation of education and inspired both instructors and learners to adopt and leverage technology for learning. This led to online learning becoming an important component of the new normal, with home-based virtual learning an essential aspect for learners on various levels. This, in turn, has caused learners of varying levels to interact more frequently with virtual resources to supplement their learning. Even though virtual learning environments provide basic resources to help monitor the learners’ online behaviour, there is room for more insights to be derived concerning individual learner performance. In this study, we propose a framework for visualising learners’ online behaviour and use the data obtained to predict whether the learners would clear a course. We explored a variety of binary classifiers from which we achieved an overall accuracy of 80%–85%, thereby indicating the effectiveness of our approach and that learners’ online behaviour had a significant effect on their academic performance. Further analysis showed that common patterns of behaviour among learners and/or anomalies in online behaviour could cause incorrect interpretations of a learner’s performance, which gave us a better understanding of how our approach could be modified in the future. © 2022,International Review of Research in Open and Distance Learning. All Rights Reserved.

A Learning Analytics Approach Using Social Network Analysis and Binary Classifiers on Virtual Resource Interactions for Learner Performance Prediction

The COVID-19 pandemic induced a digital transformation of education and inspired both instructors and learners to adopt and leverage technology for learning. This led to online learning becoming an important component of the new normal, with home-based virtual learning an essential aspect for learners on various levels. This, in turn, has caused learners of varying levels to interact more frequently with virtual resources to supplement their learning. Even though virtual learning environments provide basic resources to help monitor the learners' online behaviour, there is room for more insights to be derived concerning individual learner performance. In this study, we propose a framework for visualising learners' online behaviour and use the data obtained to predict whether the learners would clear a course. We explored a variety of binary classifiers from which we achieved an overall accuracy of 80%-85%, thereby indicating the effectiveness of our approach and that learners' online behaviour had a significant effect on their academic performance. Further analysis showed that common patterns of behaviour among learners and/or anomalies in online behaviour could cause incorrect interpretations of a learner's performance, which gave us a better understanding of how our approach could be modified in the future.

Are short course corticosteroids as effective as longer course in determining days of oxygen requirement and hospital stay in patients with moderate COVID-19 disease?

Background: In past 2 years, COVID-19 pandemic has affected the health care system adversely. World statistics showed a huge rise in the incidence of this highly infectious disease. Abnormal and unregulated immune response was found to be the key deciding factor for the outcome of this disease. A lot of studies showed a promising role of corticosteroids as immunosuppressant agents. They reduce morbidity and mortality in patients with moderate-to-severe COVID-19 disease. However, steroid therapy comes with a huge concern in form of their adverse effects, especially on prolonged use. Optimum duration of steroid therapy is not standardized. Aim and Objectives: The present study was carried out to determine days of oxygen requirement and duration of hospital stay in patients receiving short course steroid vis-à-vis long course steroid therapy. Materials and Methods: A retrospective observational study was conducted in tertiary care teaching hospital after prior permission of the Institutional Ethics Committee. All patients diagnosed as having moderate COVID-19 illness with age group of 18–80 years with minimum 03 days of 6 mg dexamethasone or other equivalent steroid administration were included in the study. Patients who were living with HIV/AIDS, cancer, hepatic and renal illness, ischemic and other valvular diseases, and chronic pulmonary diseases affecting oxygenation status were excluded from the study. A total of 203 study participants were enrolled during study period (68 in short course while 135 in long course steroid group). Data were enrolled in predesigned structured and validated case record form. Results: Short course steroid therapy was found more frequent in <60 years of age. Mean and SD of days of oxygen administration were (4.36 vs. 8.88) and (2.15 vs. 3.43) in short course and long course steroid therapy, respectively. Oxygen requirement for ≥7 days was in (10, 7.41%) patients and (45, 66.18%) patients in short course steroid group and long course steroid group, respectively. Mean and standard deviation of duration of hospital stay were (6.64, 2.87) and (11.9, 4.03) in short course and long course steroid group, respectively. Hospital stay for more than 9 days was (20, 14.81%) and (47, 69.12%) in short course and long course steroid group, respectively. Conclusion: A positive association was found between duration of hospital stay and long course steroid therapy and was statistically significant. Similarly, a positive association between days of oxygen requirement and long course steroid therapy was found and again it was statistically significant. The study findings indicated that short course steroid therapy was found to be more effective in treatment outcome of COVID-19 illness as far as the duration of hospital stay and oxygen administration parameters are concerned.

Systematic Review on Various Techniques of Android Malware Detection

Smartphone has become the 4th basic necessity of human being after Food, Cloths and Home. It has become an integral part of the life that most of the business and office work can be operated by mobile phone and the demand for online classes demand for all class of students have become a compulsion without any alternate due to the COVID-19 pandemic. Android is considered as the most prevailing and used operating system for the mobile phone on this planet and for the same reason it is the most targeted mobile operating system by the hackers. Android malware has been increasing every quarter and every year. An android malware is installed and executed on the smartphones quietly without any indication and user’s acceptance, that possess threats to the consumer’s personal and/or classified information stored. To address these threats, varieties of techniques have been proposed by the researchers like Static, Dynamic and Hybrid. In this paper a systematic review has been carried out on the relevant studies from 2017 to 2020. Assessment of the malware detection capabilities of various techniques used by different researchers has been carried out with comparison of the performance of different machine learning models for the detection of android malwares by assessing the results of empirical evidences such as datasets, features, tools, etc. However the android malware detection still faces several challenges and the possible solution with some novel approach or technique to improve the detection capabilities is discussed in the discussion and conclusion. © 2022, Springer Nature Switzerland AG.

Diagnostic dilemma in a patient with COVID vaccine-related thrombosis

Case Report While the COVID-19 pandemic killing millions world-wide, definitive therapy is not yet available. However, vaccines were shown to effectively reduce COVID-19 related mortality. Side effects of COVID vaccination include thrombosis. Most of the vaccine-related thrombosis took place after the Oxford-AstraZeneca and Johnson & Johnson vaccines. Our case, however, developed thrombosis after receiving the Moderna mRNA vaccine. A 62 y/o female with hypertension and paroxysmal atrial fibrillation had retroperitoneal hematoma thought to be due to an aneurysm posterior to the pancreatic head and underwent embolization. Following this, she developed bilateral pulmonary embolism (PE) secondary to iliac vein thrombosis which was thought to be a direct result of compression from the hematoma. She was started on anticoagulation (rivaroxaban) at that time and monitored closely for possible bleeding. Unfortunately, she stopped rivaroxaban after one month due to financial reasons. A year later, the patient presented to the hospital with chest tightness for 3 days, one week after she took her 2nd dose of Moderna vaccine. 2 days later, she started having left-sided chest tightness and dizziness. She has no family history of clotting disorder, recent surgery, and has no known malignancy. On admission, she was hemodynamically stable with normal oxygen saturation in room air. Blood work showed normal platelet count and coagulation panel. CT angiogram of the chest showed PE in the right middle lobe segmental branch without right ventricular strain. She did not have troponin elevation or EKG changes. Apixaban was initiated through a financial assistance program on discharge. Although vaccine-related thrombosis remains at the top of the differential diagnosis for our patient, a history of prior thromboembolic event a year earlier and lack of adherence to anticoagulation may have enhanced this lady's resurgence of thrombosis. Having a high degree of suspicion following COVID vaccination is always important to make an early diagnosis and prevent serious consequences of thromboembolism. It is possible that the immune-modulatory effects of the mRNA vaccines can enhance the recurrence of thrombosis in persons with previous history of the condition.

Aortic thrombosis leading to acute limb ischemia in the setting of COVID-19 pneumonia versus recently resolved pancreatitis

Case Report Hypercoagulability in the setting of COVID 19 infection is well known, but data about arterial thrombosis in this context is limited. There have also been rare instances of aortic thrombosis in the setting of acute pancreatitis. We present the case of a 64-year-old female who was admitted for acute hypoxic respiratory failure due to COVID pneumonia. A few days earlier, the patient was admitted for a bout of acute pancreatitis that was medically managed but left the hospital against medical advice. During this admission, she was found to be covid positive but was asymptomatic. Chest imaging showed bilateral interstitial opacities. The patient was readmitted due to worsening hypoxia and received dexamethasone, antibiotics and prophylactic heparin on admission. The patient didn't receive remdesivir due to acute kidney injury. Oxygen requirements increased over the next 2 days. On hospital day 3 , the patient developed right lower limb pain not relieved with analgesics with symptoms suggestive for acute limb ischemia. CT angiography of the abdominal aorta and lower extremities revealed significant clot burden in infrarenal aorta and acute occlusion of bilateral popliteal arteries and right profunda femoral artery likely due to aortic clot emboli. Vascular surgery was consulted and proceeded with thrombectomy in the infrarenal aorta, bilateral common iliac arteries and bilateral lower extremity arteries with compartment fasciotomy of the lower extremities. Unfortunately, the patient developed severe septic shock and passed away a few hours after the surgery. Although rare, there have been a few other case reports where aortic thrombosis was caused by COVID 19 or acute pancreatitis. In our patient, both pancreatitis and COVID 19 likely have played a role in aortic thromboembolism leading to critical limb ischemia. Once diagnosed, arterial occlusion is a medical emergency and needs urgent attention and immediate intervention! Physicians should be aware of the possibility of arterial occlusion in the context of Covid 19, especially if acute pancreatitis preceded Covid 19 infection.

Digital monitoring of paediatric patients with chronic recurrent multifocal osteomyelitis at a national orthopaedic centre

Introduction: Chronic recurrent multifocal osteomyelitis (CRMO) is a paediatric inflammatory bone condition requiring close monitoring by a multi-disciplinary team throughout childhood. Many UK patients are seen at the Royal National Orthopaedic Hospital, Stanmore for more than a decade of specialist management. Prior to the recent COVID crisis, we recognised need for more frequent monitoring without the inconvenience of cross-country travel and so piloted an online system of monitoring CRMO. Method: An online assessment form was created using the GDPR-compliant Qualtrics system after consultation with CRMO paediatricians and a specialist nurse. 3 medical students telephoned parents of 31 patients to pilot the assessment form. Responses indicating issues were then referred to the CNS for follow-up. Results: Response data confirmed need for close monitoring with 26% of respondents being seen quarterly, 29% reporting pain greater than 6/ 10, 29% having side-effects and 30% finding current treatment ineffective. 74% of respondents found online assessment extremely/very useful and 58% preferred it to face-to-face appointments. Conclusions: A digital CRMO monitoring tool can successfully identify patients with both new and ongoing issues. In the COVID and post- COVID era, digital tools can closely monitor patients with chronic conditions like CRMO whilst improving quality of life by reducing need for face-to-face appointments.

Political violence, risk aversion, and non-localized disease spread: evidence from the U.S. Capitol riot

On January 6, 2021, the U.S. Capitol was sieged by rioters protesting certification of Joseph R. Biden's election as the 46th president of the United States. The Director of the Centers for Disease Control and Prevention (CDC) quickly predicted that the Riot would be a COVID-19 "surge event". This study is the first to estimate the impact of the Capitol Riot on risk-averting behavior and community-level spread of the novel coronavirus. First, using anonymized smartphone data from SafeGraph, Inc. and an event-study approach, we document that on January 6th there was a substantial increase in non-resident smartphone pings in the census block groups including the Ellipse, the National Mall, and the U.S. Capitol Building, consistent with a large protest that day. Next, using data from the same source and a synthetic control approach, we find that the Capitol Riot increased stay-at-home behavior among District of Columbia residents, indicative of risk averting behaviors in response to violence and health risks. Finally, turning to COVID-19 case data, we find no evidence that the Capitol Riot substantially increased community spread of COVID-19 in the District of Columbia in the month-long period following the event. This may be due to increases in social distancing and a "virtual lockdown" of the Capitol prior to the inauguration of the new president. However, exploiting variation in non-resident smartphone inflows into the January 6 Capitol protest, we find that counties with the highest protester inflows experienced a significant increase in the rate of daily cumulative COVID-19 case growth in the month following the protest. We conclude that the Capitol Riot may have contributed to non-localized COVID-19 spread.

Public Policy Implications of the COVID-19 Pandemic

A shelter-in-place order (SIPO) is one of the most restrictive non-pharmaceutical interventions designed to curb the spread of COVID-19. On March 19, 2020, California Governor Gavin Newsom issued the first statewide SIPO in the United States. The order closed non-essential businesses and required residents to shelter in place for all but essential activities such as grocery shopping, retrieving prescriptions from a pharmacy, or caring for relatives. This study is the first in the economics literature to estimate the effect of a statewide SIPO on public health. Using daily state-level coronavirus data and a synthetic control research design, we find that California's statewide SIPO reduced COVID-19 cases by 160.9 to 194.7 per 100,000 population by April 20, one month following the order. We further find that California's SIPO led to as many as 1,566 fewer COVID-19 deaths during this period. Back-of-the-envelope calculations suggest that there were about 649 to 703 job losses per life saved, and about 14 to16 job losses per case averted during this post-treatment period. (C) 2020 by the Association for Public Policy Analysis and Management

When do shelter-in-place orders fight COVID-19 best? Policy heterogeneity across states and adoption time

Shelter in place orders (SIPOs) require residents to remain home for all but essential activities such as purchasing food or medicine, caring for others, exercise, or traveling for employment deemed essential. Between March 19 and April 20, 2020, 40 states and the District of Columbia adopted SIPOs. This study explores the impact of SIPOs on health, with particular attention to heterogeneity in their impacts. First, using daily state-level social distancing data from SafeGraph and a difference-in-differences approach, we document that adoption of a SIPO was associated with a 5 to 10 percent increase in the rate at which state residents remained in their homes full-time. Then, using daily state-level coronavirus case data collected by the Centers for Disease Control and Prevention, we find that approximately three weeks following the adoption of a SIPO, cumulative COVID-19 cases fell by 44 percent. Event-study analyses confirm common COVID-19 case trends in the week prior to SIPO adoption and show that SIPO-induced case reductions grew larger over time. However, this average effect masks important heterogeneity across states - early adopters and high population density states appear to reap larger benefits from their SIPOs. Finally, we find that statewide SIPOs were associated with a reduction in coronavirus-related deaths, but estimated mortality effects were imprecisely estimated.