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As a reference laboratory for measles and rubella surveillance in Lombardy, we evaluated the association between SARS-CoV-2 infection and measles-like syndromes, providing preliminary evidence for undetected early circulation of SARS-CoV-2. Overall, 435 samples from 156 cases were investigated. RNA from oropharyngeal swabs (N = 148) and urine (N = 141) was screened with four hemi-nested PCRs and molecular evidence for SARS-CoV-2 infection was found in 13 subjects. Two of the positive patients were from the pandemic period (2/12, 16.7%, March 2020-March 2021) and 11 were from the pre-pandemic period (11/44, 25%, August 2019-February 2020). Sera (N = 146) were tested for anti-SARS-CoV-2 IgG, IgM, and IgA antibodies. Five of the RNA-positive individuals also had detectable anti-SARS-CoV-2 antibodies. No strong evidence of infection was found in samples collected between August 2018 and July 2019 from 100 patients. The earliest sample with evidence of SARS-CoV-2 RNA was from September 12, 2019, and the positive patient was also positive for anti-SARS-CoV-2 antibodies (IgG and IgM). Mutations typical of B.1 strains previously reported to have emerged in January 2020 (C3037T, C14408T, and A23403G), were identified in samples collected as early as October 2019 in Lombardy. One of these mutations (C14408T) was also identified among sequences downloaded from public databases that were obtained by others from samples collected in Brazil in November 2019. We conclude that a SARS-CoV-2 progenitor capable of producing a measles-like syndrome may have emerged in late June-late July 2019 and that viruses with mutations characterizing B.1 strain may have been spreading globally before the first Wuhan outbreak. Our findings should be complemented by high-throughput sequencing to obtain additional sequence information. We highlight the importance of retrospective surveillance studies in understanding the early dynamics of COVID-19 spread and we encourage other groups to perform retrospective investigations to seek confirmatory proofs of early SARS-CoV-2 circulation.

EndALL-Virus by Suriya Sundaram In the midst of the real-life coronavirus ordeal, you are in a world where a virus has put humanity on the brink of extinction. The virus has taken everything you love from you. You have nothing left to lose. You are humanity's last hope... will you make the right decisions to save man-kind?

The COVID-19 pandemic demonstrated the potential for healthcare systems to lack capacity to meet demand for critical care in times of crisis. Recent research suggests a rise in the utilization of intensive care unit (ICU) resources and the potential misallocation of resources to patients without clinical need or hope of benefit. Several authorities have published resource allocation policies to guide healthcare systems, commonly relying on measures of illness severity to determine the priority by which ICU resources would be allocated. This raises concerns about the properties of and the potential for allocation criteria to exacerbate racial disparities in clinical outcomes. Policymakers intend that such policies would maximize the number of lives saved by prioritizing provision of critical care services to patients most likely to benefit. This dissertation examines the interrater reliability of the University of California’s Scarce Resource Allocation Policy (SRAP) in determining the allocation priority of a cohort of consecutively admitted ICU patients at the University of California, Los Angeles (UCLA) Health System. Use of the SRAP had relatively poor reliability in determining allocation priority as laid out within the policy itself. A microsimulation model examined the likely impact of allocation decisions and likelihood of allocation of resources under four defined scenarios of resource constraint, for the outcome of ICU mortality. Mortality differed significantly across tested constraint levels compared to the case of no constraint (i.e., current capacity). Mortality was greater in subgroups with lower priority for constrained ICU resources. A mediation analysis examined if observed differences in mortality risk among racial groups are related to the use of SOFA scores or the selected comorbid conditions. Results suggest that these policy criteria do not mediate the effect of race on mortality. Understanding the projected outcomes related to use of these policies and the policy criteria that drive observed differences among patient groups can better inform policymakers in shaping protocols to maximize lives saved and avoid worsening healthcare disparities.

In the last few months, the COVID-19 pandemic has spread all across the world and is still dominating the headlines at this time. Notwithstanding global and regional differences, the basic elements of how we live have radically changed due to government prevention policies, the fear of contracting the virus and the actual spread of the disease. In this context, at CLEARING HOUSE, we realised that it was not possible to carry on our work and research as if nothing was happening. This is why we decided to adapt our work plan and during April we launched a new line of reflection and research with the objective to look at how the COVID-19 pandemic was changing both, our professional perspective and citizens’ attitude on green spaces and urban forests. In this blog, we bring together different stories looking at the issue from various angles (tag: COVID-19), and at the same time we present the findings of a survey. This post provides a general overview of the responses; in the next blog posts we will also provide details about specific groups of respondents; and at the same time we are working on a more elaborate analysis that will be published in the form of a scientific paper. Read more: http://clearinghouseproject.eu/2020/07/23/green-spaces-urban-forests-during-the-covid-19-pandemic/

When discussing students’ educational experience on campus, including race and racism, previous studies usually discuss domestic and international students separately and use different theoretical frameworks. Previous literature examining international students focused on the individual characteristics of students and how those associated with their personal adjustment to their campus environment (e.g., Andrade, 2006; Khawaja & Stallman, 2011; Ward & Masgoret, 2009). Little attention has been given to critical frameworks that address the international student population, considering not only on students’ race and ethnicity as major factors, but also engages international students’ direct racial experiences within specific institutional types. This study explores Asian international graduate students’ experiences of campus racial climate and resistance strategies in a Minority-serving Institution (MSI) in the U.S. This study uncovers how racialization experiences are shaped by students' own ethnic backgrounds, the history of the U.S.’s racial stratification system, and national and global contexts. My research also raises timely concerns of anti-Asian racism in the U.S. due to America’s shifting political climate and the serious consequences of the COVID-19 pandemic on higher education. Despite facing microaggressions and other forms of oppressions on and off-campus, Asian international graduate students engage in resistance strategies to adjust to and combat microaggressions, institutional invisibility, and academic injustices. This research is guided by a qualitative research methodology utilizing a single case study to focus on an individual’s lived experiences. The aim of this research also includes ameliorating oppressive attitudes to Asian international students.

SARS-CoV-2 entry into host cells is orchestrated by the spike (S) glycoprotein that contains an immunodominant receptor-binding domain (RBD) targeted by the largest fraction of neutralizing antibodies (Abs) in COVID-19 patient plasma. Little is known about neutralizing Abs binding to epitopes outside the RBD and their contribution to protection. Here, we describe 41 human monoclonal Abs (mAbs) derived from memory B cells, which recognize the SARS-CoV-2 S N-terminal domain (NTD) and show that a subset of them neutralize SARS-CoV-2 ultrapotently. We define an antigenic map of the SARS-CoV-2 NTD and identify a supersite recognized by all known NTD-specific neutralizing mAbs. These mAbs inhibit cell-to-cell fusion, activate effector functions, and protect Syrian hamsters from SARS-CoV-2 challenge. SARS-CoV-2 variants, including the 501Y.V2 and B.1.1.7 lineages, harbor frequent mutations localized in the NTD supersite suggesting ongoing selective pressure and the importance of NTD-specific neutralizing mAbs to protective immunity. ispartof: location:United States status: Published online ispartof: bioRxiv

Files to reproduce the results of the preprint: "Estimated transmission dynamics of SARS-CoV-2 variants from wastewater are robust to differential shedding"

One of the factors which perpetuates gender inequality is the inequitable division of household labor, and particularly the division of child caretaking labor. Even when women are employed outside the home, many remain primarily responsible for household duties and child caretaking. This research utilizes individual interviews (N=40) with heterosexual, married or cohabitating parents of children 5 and under where fathers do the majority of child caretaking. I explore how lead-dad households are similar to and different from those with a traditional lead-mother arrangement, as well as what motivates lead-father families to choose this arrangement, and how they explain it to others. This project also considers the impact of the COVID-19 pandemic on lead-dad households and whether it has disrupted household roles in these families. This project uses atypical or negative cases to better understand the issue of gender identity of both mothers and fathers in atypical households.

A series of experiments in stationary and moving passenger railcars was conducted to measure the removal rates of particles in the size ranges of SARS-CoV-2 viral aerosols, and the air changes per hour provided by the existing and modified air handling systems. The effect of ventilation and air filtration systems on removal rates and their effects on estimated probability (i.e., risk) of infection was evaluated in a range of representative conditions: (1) for two different ratios of recirculated air (RA) to outdoor air (OA) (90:10 RA:OA and 67:33 RA:OA); (2) using minimum efficiency reporting value (MERV) filters with standard (MERV-8) and increased (MERV-13) filtration ratings; and (3) in the presence and absence of a portable high-efficiency particulate-air (HEPA) room air purifier system operated at clean air delivery rate (CADR) of 150 and 550 cfm. The higher-efficiency MERV-13 filters significantly increased particle removal rates on average by 3.8 to 8.4 hr−1 across particle sizes ranging from 0.3 to 10 µm (p < 0.01) compared to MERV-8 filters. The different RA:OA ratios and the use of a portable HEPA air purifier system had little effect on particle removal rates. MERV-13 filters reduced the estimated probability of infection by 42% compared to the MERV-8 filter. The use of a HEPA-air purifier with a MERV-13 filter causes a 50% reduction in the estimated probability of infection. Upgrading the efficiency of HVAC filters from MERV-8 to MERV-13 in public transit vehicles is the most effective exposure control method resulting in a clear reduction in the removal rates of aerosol particles and the estimated probability of infection.

In-Memory Computing (IMC) is considered a great candidate to replace the von-Neumann computing architecture to overcome the memory wall. Content Addressable Memories (CAMs) are the main building blocks in IMC-based architectures, such as the associative processors, and they are being used to accelerate machine learning tasks such as inference on Decision Trees (DTs). Decision trees are popular and powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications that have limited power and latency budget. In this paper, we first present a juxtaposition between the capacitive and resistive sensing schemes in 2 Transistor-2 Resistive (2T-2R) Ternary CAMs (TCAMs). A Figure of Merit (FOM), function of the dynamic range, latency, and energy, is defined to have a fair comparison between the two sensing techniques. A mathematical model for the transient behavior of both sensing schemes is derived and verified through SPICE simulations. We then study the performance of the two schemes with an in-memory addition application and the results reveal that resistive sensing has an edge in that context. In addition, we propose a CAM Compiler for DT inference acceleration. In particular, we propose a novel ”adaptive-precision” scheme that results in a compact implementation and enables an efficient bijective mapping to TCAMs while maintaining high inference accuracies. Also, a Resistive-CAM (ReCAM) functional synthesizer is developed for mapping the decision tree to the ReCAM arrays with the capacitive sensing scheme and performing functional simulations for energy, latency, and accuracy evaluations. We study the decision tree accuracy under hardware non-idealities including device defects, manufacturing variability, and input encoding noise. We test our framework on various DT datasets including Give Me Some Credit, Titanic, and COVID-19. Our results reveal up to 42.4% energy savings and up to 17.8x better energy-delay-area product compared to the state-of-art hardware accelerators and up to 333 million decisions per sec for the pipelined implementation.