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Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), the virus strain that causes coronavirus disease 2019 (COVID-19), was first identified in Wuhan, China in December 2019. It spread to several countries across continents and infected more than one million people within three months. While there is no consensus on the treatment of the disease yet, understanding the virus and its transmission is a cardinal priority. SARS-CoV-2 can be transmitted through bodily fluid. Upon inoculation, the surface enzyme angiotensin-converting enzyme 2 (ACE2) acts as a receptor protein for viral entry. The mean incubation period is 5.1 days, and infected individuals can exhibit a variety of symptoms from fever, cough, dyspnea, and respiratory failure to even multiorgan failure. Given the current situation, it is of paramount importance to understand the virus as thoroughly as possible. In this review, we discuss the background, epidemiology, possible pathophysiology, clinical presentation, and diagnostic studies related to SARS-CoV-2 infection. We also elaborate on the current research and evidence on treatment options and vaccine development based on the literature.

This study describes SARS-CoV-2 PCR test positivity among health care workers before, during, and after implementation of a policy requiring universal masking of all health care workers and patients in a large health care system in Massachusetts.

Introduction Differentiated service delivery (DSD) models aim to improve the access of human immunodeficiency virus treatment on clients and reduce requirements for facility visits by extending dispensing intervals. With the advent of the COVID-19 pandemic, minimising client contact with healthcare facilities and other clients, while maintaining treatment continuity and avoiding loss to care, has become more urgent, resulting in efforts to increase DSD uptake. We assessed the extent to which DSD coverage and antiretroviral treatment (ART) dispensing intervals have changed during the COVID-19 pandemic in Zambia. Methods We used client data from Zambia's electronic medical record system (SmartCare) for 737 health facilities, representing about three-fourths of all ART clients nationally. We compared the numbers and proportional distributions of clients enrolled in DSD models in the 6 months before and 6 months after the first case of COVID-19 was diagnosed in Zambia in March 2020. Segmented linear regression was used to determine whether the outbreak of COVID-19 in Zambia further accelerated the increase in DSD scale-up. Results and discussion Between September 2019 and August 2020, 181,317 clients aged 15 or older (81,520 and 99,797 from 1 September 2019 to 1 March 2020 and from 1 March to 31 August 2020, respectively) enrolled in DSD models in Zambia. Overall participation in all DSD models increased over the study period, but uptake varied by model. The rate of acceleration increased in the second period for home ART delivery (152%), ≤ 2-month fast-track (143%) and 3-month MMD (139%). There was a significant reduction in the enrolment rates for 4- to 6-month fast-track (-28%) and "other" models (-19%). Conclusions Participation in DSD models for stable ART clients in Zambia increased after the advent of COVID-19, but dispensing intervals diminished. Eliminating obstacles to longer dispensing intervals, including those related to supply chain management, should be prioritized to achieve the expected benefits of DSD models and minimize COVID-19 risk.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes. ACE2 and TMPRSS2 have received recent attention as entry factors for SARS-CoV-2. Here the authors analyze nasal airway transcriptome data from 695 children determining ACE2 and TMPRSS2 expression is induced by viral and type2 inflammation, respectively, and both exhibit eQTLs that vary across world populations.

No abstract available. Article truncated after 150 words. Sleep is more important now than ever. Getting enough sleep and maintaining a regular schedule for optimal circadian rhythm health is a challenge for most of us even in the best of times, but the schedule changes and added stress from the COVID-19 pandemic has likely impacted your sleep schedule over the past few weeks. Sleep does more than just make us feel better the next day. It allows us to pay close attention, remember new information, and multi-task. Regularity of sleep and wake also maintains the health and optimal function of the circadian timing system (our internal biological clock). Insufficient sleep and irregular sleep-wake schedules can impair our health, weaken our immune system, increase inflammation, and even lead to increased vulnerability to viral illnesses. Given how important regular, sufficient, sleep is for our safety, health, and quality of life, the following tips may help to optimize circadian and sleep …

Predictive algorithms are replacing the art of human judgement in rapidly growing areas of social life. By offering pattern recognition as forecast, predictive algorithms mechanically project the past onto the future, embracing a peculiar notion of time where the future is different in no radical way from the past and present, and a peculiar world where human agency is absent. Yet, prediction is about agency, we predict the future to change it. At the individual level, the psychological literature has concluded that in the realm of predictions, human judgement is inferior to algorithmic methods. At the sociological level, however, human judgement is often preferred over algorthms. We show how human and algorithmic predictions work in three social contexts—consumer credit, college admissions and criminal justice—and why people have good reasons to rely on human judgement. We argue that mechanical and overly successful local predictions can result in self-fulfilling prophecies and, eventually, global polarization and chaos. Finally, we look at algorithmic prediction as a form of societal and political governance and discuss how it is currently being constructed as a wide net of control by market processes in the USA and by government fiat in China. 1. Introduction 2. The statistical versus clinical prediction debate 3. Three main technological developments enabling algorithmic predictions 4. Pattern recognition versus prediction 5. Why one should be skeptical 6. Credit 7. The science of scoring 8. Agency 9. College admission 10. Crime 11. The world of algorithmic government 12. Conclusion Footnotes References

Wearable sensing technologies are having a worldwide impact on the creation of novel business opportunities and application services that are benefiting the common citizen. By using these technologies, people have transformed the way they live, interact with each other and their surroundings, their daily routines, and how they monitor their health conditions. We review recent advances in the area of wearable sensing technologies, focusing on aspects such as sensor technologies, communication infrastructures, service infrastructures, security, and privacy. We also review the use of consumer wearables during the coronavirus disease 19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and we discuss open challenges that must be addressed to further improve the efficacy of wearable sensing systems in the future.

We report severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine effectiveness against infection (VE-I) and death (VE-D) by vaccine type in 780,225 veterans in the Veterans Health Administration, covering 2.7% of the US population. From February to October 2021, VE-I declined for all vaccine types, and the decline was greatest for the Janssen vaccine, resulting in a VE-I of 13.1%. Although breakthrough infection increased risk of death, vaccination remained protective against death in persons who became infected during the Delta variant surge. From July to October 2021, VE-D for age <65 years was 73.0% for Janssen, 81.5% for Moderna, and 84.3% for Pfizer-BioNTech; VE-D for age ≥65 years was 52.2% for Janssen, 75.5% for Moderna, and 70.1% for Pfizer-BioNTech. Findings support continued efforts to increase vaccination, booster campaigns, and multiple additional layers of protection against infection.