The COVID HOME study research protocol: Prospective cohort study of non-hospitalised COVID-19 patients (preprint)

Background. Guidelines on COVID-19 management are developed as we learn from this pandemic. However, most research has been done on hospitalised patients and the impact of the disease on non-hospitalised and their role in transmission are not yet well understood. The COVID HOME study conducts research among COVID-19 patients and their family members who were not hospitalised during acute disease, to guide patient care and inform public health guidelines for infection prevention and control in the community and household. Methods. An ongoing prospective longitudinal observational study of COVID-19 outpatients was established in March 2020 in the Netherlands. Laboratory confirmed SARS-CoV-2 infected individuals of all ages that did not merit hospitalisation, and their household (HH) members, were enrolled after written informed consent. Enrolled participants were visited at home within 48 hours after initial diagnosis, and then weekly on days 7, 14 and 21 to obtain clinical data, a blood sample for biochemical parameters/cytokines and serological determination; and a nasopharyngeal/throat swab plus urine, stool and sperm or vaginal secretion (if consenting) to test for SARS-CoV-2 by RT-PCR (viral shedding) and for viral culturing. Weekly nasopharyngeal/throat swabs and stool samples, plus a blood sample on days 0 and 21 were also taken from HH members to determine whether and when they became infected. All participants were invited to continue follow-up at 3-, 6-, 12- and 18-months post-infection to assess long-term sequelae and immunological status. Preliminary Results. A total of 256 participants belonging to 103 HH were included of which, 190 (74.2%) were positive for SARS-CoV-2 infection. Most individuals (183/190, 96.3%) developed mild to moderate disease. At the time of writing, all participants had reached the 3 and 6 month time-points of the long-term follow-up, while approximately 78% reached 12 month and 23% the 18 month time-point. Preliminary analysis showed that 43% (52/121) positive individuals reported having complaints at 3 months post-infection, while 42.7% (61/143) had complaints at 6 months.

Booster Dose Study to Assess the Safety and Immunogenicity of ACM-001 Administered Intramuscularly or Intranasally.

Encounters with Visual Misinformation and Labels Across Platforms

Social media platforms face rampant misinformation spread through multimedia posts shared in highly-personalized contexts [10, 11]. Foundational qualitative research is necessary to ensure platforms' misinformation interventions are aligned with users' needs and understanding of information in their own contexts, across platforms. In two studies, we combined in-depth interviews (n=15) with diary and co-design methods (n=23) to investigate how a mix of Americans exposed to misinformation during COVID-19 understand their information environments, including encounters with interventions such as Facebook fact-checking labels. Analysis reveals a deep division in user attitudes about platform labeling interventions, perceived by 7/15 interview participants as biased and punitive. As a result, we argue for the need to better research the unintended consequences of labeling interventions on factual beliefs and attitudes. Alongside these findings, we discuss our methods as a model for continued independent qualitative research on cross-platform user experiences of misinformation in order to inform interventions.

Towards an Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns

This ongoing work attempts to understand and address the requirements of UNICEF, a leading organization working in children's welfare, where they aim to tackle the problem of air quality for children at a global level. We are motivated by the lack of a proper model to account for heavily fluctuating air quality levels across the world in the wake of the COVID-19 pandemic, leading to uncertainty among public health professionals on the exact levels of children's exposure to air pollutants. We create an initial model as per the agency's requirement to generate insights through a combination of virtual meetups and online presentations. Our research team comprised of UNICEF's researchers and a group of volunteer data scientists. The presentations were delivered to a number of scientists and domain experts from UNICEF and community champions working with open data. We highlight their feedback and possible avenues to develop this research further.

Tracing Contacts With Mobile Phones to Curb the Pandemic: Topics and Stances in People's Online Comments About the Official German Contact-Tracing App

The Covid-19 pandemic has led to a health crisis with 90 million infections and two million deaths by the end of January 2021. To prevent an overload of medical capacities, quickly identifying potentially infected persons is vital to stop the spread of the virus. Mobile apps for tracing people's contacts seem efective, but raise public concerns, e. g., about privacy. Hence, they are contested in public discourse. We report a large-scale NLP-supported analysis of people's comments about the German contact-tracing app on news websites, social media and app stores. We identifed prevalent topics, stances, and how commenting developed over time. We found privacy to be among the most debated topics discussed from various perspectives. Commenting peaked at one point in time, when public discourse centered on the potential tracing protocols and their privacy protection. We encourage further research on the link between the public discussions and actual adoption rates of the app.

Using Tweets to Assess Mental Well-being of EssentialWorkers During the COVID-19 Pandemic

The Covid-19 pandemic has led to large-scale lifestyle changes and increased social isolation and stress on a societal level. This has had a unique impact on US "essential workers" (EWs) - who continue working outside their homes to provide critical services, such as hospital and infrastructure employees. We examine the use of Twitter by EWs as a step toward understanding the pandemic's impact on their mental well-being, as compared to the population as a whole. We found that EWs authored a higher ratio of mental health related tweets during the pandemic than the average user, but authored fewer tweets with Covid related keywords than average users. Despite this, sentiment analysis showed that, on average, EWs' tweets yield a more positive sentiment score than average Twitter users, both before and during the pandemic. Based on these initial insights, we highlight our future aims to investigate individual differences in this impact to EWs.

The Case for "Weird Social" in VR/XR A Vision of Social Superpowers Beyond Meatspace

COVID underscores the potential of VR meeting tools to compensate for lack of embodied communication in applications like Zoom. But both research and commercial VR meeting environments typically seek to approximate physical meetings, instead of exploring new capacities of communication and coordination. We argue the most transformative features of VR (and XR more broadly) may look and feel very different from familiar social rituals of physical meetings. Embracing "weird" forms of sociality and embodiment, we incorporate inspiration from a range of sources including: (1) emerging rituals in commercial social VR, (2) existing research on social augmentation systems for meetings, (3) novel examples of embodied VR communication, and (4) a fictionalized vignette envisioning a future with aspects of "Weird Social XR" folded into everyday life. We call upon the research community to approach these speculative forms of alien sociality as opportunities to explore new kinds of social superpowers.

This is Not a Paper Applying a Design Research lens to video conferencing, publication formats, eggs ... and other things

This is like an to a paper, but it is more . In fact, it is the introduction to something which is a not paper. The global Covid-19 pandemic of 2020 represented an infection point for our post-post-modern world, a moment where our old normal was dramatically arrested. We are now in a state of comprehensive flux as 'new normals' emerge, begin to solidify, and may evolve into an-as yet undetermined-futures. This not paper is a facet and exploration of that flux as it relates to publication and conference culture, video conferencing systems, and how we both conduct, and share, research. You should read the whole of this , but then you should take a step inside the not paper, it lives on the web over here https://designresearch.works/thisisnotapaper/

Speculating on Biodesign in the Future Home

The home is a place of shelter, a place for family, and for separation from other parts of life, such as work. Global challenges, the most pressing of which are currently the COVID-19 pandemic and climate change has forced extra roles into many homes and will continue to do so in the future. Biodesign integrates living organisms into designed solutions and can offer opportunities for new kinds of technologies to facilitate a transition to the home of the future. Many families have had to learn to work alongside each other, and technology has mediated a transition from standard models of operation for industries. These are the challenges of the 21st century that mandate careful thinking around interactive systems and innovations that support new ways of living and working at home. In this workshop, we will explore opportunities for biodesign interactive systems in the future home. We will bring together a broad group of researchers in HCI, design, and biosciences to build the biodesign community and discuss speculative design futures. The outcome will generate an understanding of the role of interactive biodesign systems at home, as a place with extended functionalities.

DistCare: Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis

Due to the characteristics of COVID-19, the epidemic develops rapidly and overwhelms health service systems worldwide. Many patients suffer from life-threatening systemic problems and need to be carefully monitored in ICUs. An intelligent prognosis can help physicians take an early intervention, prevent adverse outcomes, and optimize the medical resource allocation, which is urgently needed, especially in this ongoing global pandemic crisis. However, in the early stage of the epidemic outbreak, the data available for analysis is limited due to the lack of effective diagnostic mechanisms, the rarity of the cases, and privacy concerns. In this paper, we propose a distilled transfer learning framework, DistCare, which leverages the existing publicly available online Electronic Medical Records to enhance the prognosis for inpatients with emerging infectious diseases. It learns to embed the COVID-19-related medical features based on massive existing EMR data. The transferred parameters are further trained to imitate the teacher model's representation based on distillation, which embeds the health status more comprehensively on the source dataset. We conduct Length-of-Stay prediction experiments for patients in ICUs on real-world COVID-19 datasets. The experiment results indicate that our proposed model consistently outperforms competitive baseline methods. In order to further verify the scalability of DistCare to deal with different clinical tasks on different EMR datasets, we conduct an additional mortality prediction experiment on End-Stage Renal Disease datasets. The extensive experiments demonstrate that DistCare can benefit the prognosis for emerging pandemics and other diseases with limited EMR.

Understanding the influence of stress on sedentary workers' sitting behavior in screen-based interaction context

Sedentary work has become a significant part of a workday context, and this situation becomes more salient due to the COVID-19 pandemic. Existing studies show that body posture can be a good indicator of emotional states. However, to our knowledge, there are no studies that investigated the relationship between the characteristics of whole-body regions while seated and affective information related to stress for sedentary workers in screen-based working scenarios. This paper conducted a preliminary within-subjects study with eight participants performing three types of screen-based tasks at different difficulty levels for simulating natural working conditions. We developed a rapid posture coding technique to analyze sedentary workers' real-time sitting behavior and deployed multiple methods for continuously detecting their stress conditions. The results indicated that stress conditions and task determinants play an essential role in the postural changes of different body regions while seated. Our preliminary findings provide design implications and recommendations for developing a more unobtrusive health-promoting system in the real-life working context.

U-net for learning and inference of dense representation of multiple air pollutants from satellite imagery

Air pollution is an important topic on countless fronts and is an active area of research. The goal of this work is to provide a machine learning model for learning and inference of pollution concentrations and air quality measures, namely Particulate Matter 2.5, NO3, Nitrate Pollution, and NH4, Atmospheric Ammonium, with high granularity by using easily obtainable satellite imagery data. In order to achieve this, we propose the fully convolutional network U-net that, unlike previous work, can predict these pollutant values at a pixel-level high-resolution instead of being able only to predict a single value for an entire geographical region. We demonstrate that this approach can reconstruct the considered pollutant concentrations on ground-truth data and can predict the concentrations and their spatial structure reasonably well, even for data that the network has temporally not yet seen. Finally, we illustrate that the model's pollutant predictions can offer valuable insights into the current COVID-19 pandemic.

COVID19(alpha) : Interactive Spatio-Temporal Visualization of COVID-19 Symptoms through Tweet Analysis

In this demo, we focus on analyzing COVID-19 related symptoms across the globe reported through tweets by building an interactive spatio-temporal visualization tool, i.e., COVID19(alpha). Using around 462 million tweets collected over a span of six months, COVID19(alpha) provides three different types of visualization tools: 1) Spatial Visualization with a focus on visualizing COVID-19 symptoms across different geographic locations;2) Temporal Visualization with a focus on visualizing the evolution of COVID-19 symptoms over time for a particular geographic location;and 3) Spatio-Temporal Visualization with a focus on combining both spatial and temporal analysis to provide comparative visualizations between two (or more) symptoms across time and space. We believe that health professionals, scientists, and policymakers will be able to leverage this interactive tool to devise better and targeted health intervention policies. Our developed interactive visualization tool is publicly available at https://bijoy-sust.github.io/Covid19/.

Children and adults with mild COVID-19 symptoms develop memory T cell immunity to SARS-CoV-2 (preprint)

BackgroundSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to considerable morbidity/mortality worldwide, but most infections, especially among children, have a mild course. However, it remains largely unknown whether infected children develop cellular immune memory. MethodsTo determine whether a memory T cell response is being developed as an indicator for long-term immune protection, we performed a longitudinal assessment of the SARS-CoV-2-specific T cell response by IFN-{gamma} ELISPOT and activation marker expression analyses of peripheral blood samples from children and adults with mild-to-moderate COVID-19. ResultsUpon stimulation of PBMCs with heat-inactivated SARS-CoV-2 or overlapping peptides of spike (S-SARS-CoV-2) and nucleocapsid proteins, we found S-SARS-CoV-2-specific IFN-{gamma} T cell responses in most infected children (83%) and all adults (100%) that were absent in unexposed controls. Frequencies of SARS-CoV-2-specific T cells were higher in infected adults, especially in those with moderate symptoms, compared to infected children. The S-SARS-CoV-2 IFN-{gamma} T cell response correlated with S1-SARS-CoV-2-specific serum IgM, IgG, and IgA antibody concentrations. Predominantly, effector memory CD4+ T cells of a Th1 phenotype were activated upon exposure to SARS-CoV-2 antigens, which persisted for 4-8 weeks after symptom onset. We detected very low frequencies of SARS-CoV-2-reactive CD8+ T cells in these individuals. ConclusionsOur data indicate that an antigen-specific memory CD4+ T cell response is induced in children and adults with mild SARS-CoV-2 infection. T cell immunity induced after mild COVID-19 could contribute to protection against re-infection.

Induction of trained immunity by influenza vaccination - impact on COVID-19 (preprint)

Non-specific protective effects of certain vaccines have been reported, and long-term boosting of innate immunity, termed trained immunity, has been proposed as one of the mechanisms mediating these effects. Several epidemiological studies suggested cross-protection between influenza vaccination and COVID-19. In a large academic Dutch hospital, we found that SARS-CoV-2 infection was less common among employees who had received a previous influenza vaccination: relative risk reductions of 37% and 49% were observed following influenza vaccination during the first and second COVID-19 waves, respectively. The quadrivalent inactivated influenza vaccine induced a trained immunity program that boosted innate immune responses against various viral stimuli and fine-tuned the anti-SARS-CoV-2 response, which may result in better protection against COVID-19. Influenza vaccination led to transcriptional reprogramming of monocytes and reduced systemic inflammation. These epidemiological and immunological data argue for potential benefits of influenza vaccination against COVID-19, and future randomized trials are warranted to test this possibility.

Research on the Influencing Factors and Management Countermeasures of College Students' Sense of Security under the Environment of Big Data-an Empirical Analysis based on the Event of COVID-19

Exposed in environment of big data, college students come easily into contact with massive data presentation. When crisis events occur, college students will be affected not only by crisis events but also by human psychological crisis. The greater psychological threat, faced by college students in the crisis environment, is the loss of sense of security. Through literature review, the hypotheses in crisis events are as followed: crisis events, government and media response, university coping measures, group coping behavior are the four main factors that affect college students' sense of security in crisis events. The outbreak of COVID-19 in Wuhan, Hubei affecting all the people, all colleges and universities across the country delayed the opening time. Among the affected universities, take the University of Electronic Science and Technology as an example, 600 samples were randomly selected to collect data. Through the exploratory factor analysis test, the influence hypotheses are verified. Through the structural equation model test, the four kinds of factors can explain the loss of college students' sense of security in the crisis, but show differences in explanatory power. Based on the elements of college students' sense of security, this paper puts forward an further explanation on the action path of the four factors on the public sense of security. According to the conclusion, we come to the conclusion that improving the coping ability of colleges and universities, enhancing the sense of crisis determination and the efficiency of control are the key to improve college students' sense of security and ensure the effectiveness of crisis management in colleges and universities.

On-site rapid molecular testing, mobile sampling teams and eHealth to support primary care physicians during the COVID-19 pandemic (preprint)

Objectives We evaluated the effects of on-site rapid molecular testing at a drive-through sampling facility, deployment of mobile sampling teams and implementation of an online eHealth platform as supportive measures for general practitioners (GPs) during the COVID-19 pandemic. Methods An eHealth platform was developed that allowed GPs to either refer patients to a drive-through sampling facility or to request a home visit by a sampling team. Nasopharyngeal swab samples from patients marked as urgent (n=333) were tested immediately on-site using a GeneXpert System. Non-urgent samples (n=1,460) were sent once a day to a university hospital laboratory for routine testing. Time stamps starting from referral to the moment of test report sent were recorded to calculate the turnaround time. Results The eHealth platform was rapidly adopted and used by a total of 517 GPs to test 1,793 patients in a period of 13 weeks. On-site rapid molecular testing reduced the median turnaround time to 03h:41m compared to 29h:15m for routine testing. Positive SARS-CoV-2 test results were identified amongst 84/1,477 (5.7%) and 33/316 (10.4%) patients sampled at the drive-through or at home, respectively. In the age category of >80 years, 80.4% of patients were tested by a mobile sampling team. Conclusions The combination of rapid molecular testing and eHealth reduced the time between referral and results sent back to the GP to less than four hours. In addition, mobile sampling teams helped in reaching non-mobile, elderly patient populations with a higher prevalence of COVID-19.

Unravelling the modes of transmission of SARS-CoV-2 during a nursing home outbreak: looking beyond the church super-spread event (preprint)

BackgroundAn outbreak of COVID-19 in a nursing home in the Netherlands, following an on-site church service held on March 8, 2020, triggered an investigation to unravel sources and chain(s) of transmission.MethodsEpidemiological data were collected from registries and through a questionnaire among church visitors. Symptomatic residents and healthcare workers (HCWs) were tested for SARS-CoV-2 by RT-PCR and subjected to whole genome sequencing (WGS). Sequences from a selection of people from the same area were included as community reference.ResultsAfter the church service, 30 of 39 visitors (77%) developed symptoms; 14 were tested and were positive for COVID-19 (11 residents and 3 non-residents). In the following five weeks, 62 of 300 residents (21%) and 30 of 640 HCWs (5%) tested positive for COVID-19; 21 of 62 residents (34%) died. The outbreak was controlled through a cascade of measures. WGS of samples from residents and HCWs identified a diversity of sequence types, grouped into eight clusters. Seven resident church visitors all were infected with distinct viruses, four of which belonged to two larger clusters in the nursing home.ConclusionsAlthough initial investigation suggested the church service as source of the outbreak, detailed analysis showed a more complex picture, most consistent with widespread regional circulation of the virus in the weeks before the outbreak, and multiple introductions into the nursing home before the visitor ban. The findings underscore the importance of careful outbreak investigations to understand SARS-CoV-2 transmission to develop evidence-based mitigation measures.

A systems approach to inflammation identifies therapeutic targets in SARS-CoV-2 infection (preprint)

Background Infection with SARS-CoV-2 manifests itself as a mild respiratory tract infection in the majority of individuals, which progresses to a severe pneumonia and acute respiratory distress syndrome (ARDS) in 10-15% of patients. Inflammation plays a crucial role in the pathogenesis of ARDS, with immune dysregulation in severe COVID-19 leading to a hyperinflammatory response. A comprehensive understanding of the inflammatory process in COVID-19 is lacking. Methods In this prospective, multicenter observational study, patients with PCR-proven or clinically presumed COVID-19 admitted to the intensive care unit (ICU) or clinical wards were included. Demographic and clinical data were obtained and plasma was serially collected. Concentrations of IL-6, TNF-, complement components C3a, C3c and the terminal complement complex (TCC) were determined in plasma by ELISA. Additionally, 269 circulating biomarkers were assessed using targeted proteomics. Results were compared between ICU and non ICU patients. Findings A total of 119 (38 ICU and 91 non ICU) patients were included. IL-6 plasma concentrations were elevated in COVID-19 (ICU vs. non ICU, median 174.5 pg/ml [IQR 94.5-376.3 vs. 40.0 pg/ml [16.5-81.0]), whereas TNF- concentrations were relatively low and not different between ICU and non ICU patients (median 24.0 pg/ml [IQR 16.5-33.5] and 21.5 pg/ml [IQR 16.0-33.5], respectively). C3a and terminal complement complex (TCC) concentrations were significantly higher in ICU vs. non ICU patients (median 556.0 ng/ml [IQR 333.3-712.5]) vs. 266.5 ng/ml [IQR 191.5-384.0 for C3a and 4506 mAU/ml [IQR 3661-6595 vs. 3582 mAU/ml [IQR 2947-4300] for TCC) on the first day of blood sampling. Targeted proteomics demonstrated that IL-6 (logFC 2.2), several chemokines and hepatocyte growth factor (logFC 1.4) were significantly upregulated in ICU vs. non ICU patients. In contrast, stem cell factor was significantly downregulated (logFC -1.3) in ICU vs. non ICU patients, as were DPP4 (logFC -0.4) and protein C inhibitor (log FC -1.0), the latter two factors also being involved in the regulation of the kinin-kallikrein pathway. Unsupervised clustering pointed towards a homogeneous pathogenetic mechanism in the majority of patients infected with SARS-CoV-2, with patient clustering mainly based on disease severity. Interpretation We identified important pathways involved in dysregulation of inflammation in patients with severe COVID-19, including the IL-6, complement system and kinin-kallikrein pathways. Our findings may aid the development of new approaches to host-directed therapy.