Background Quantitative serological assays detecting response to SARS-CoV-2 are needed to quantify immunity. This study analyzed the performance and correlation of two quantitative anti-S1 assays in oligo-/asymptomatic individuals from a population-based cohort. Methods In total, 362 plasma samples (108 with reverse transcription-polymerase chain reaction [RT-PCR]-positive pharyngeal swabs, 111 negative controls, and 143 with positive serology without confirmation by RT-PCR) were tested with quantitative assays (Euroimmun Anti-SARS-CoV-2 QuantiVac enzyme-linked immunosorbent assay [EI-S1-IgG-quant]) and Roche Elecsys ® Anti-SARS-CoV-2 S [Ro-RBD-Ig-quant]), which were compared with each other and confirmatory tests, including wild-type virus micro-neutralization (NT) and GenScript ® cPass™. Square roots R of coefficients of determination were calculated for continuous variables and non-parametric tests were used for paired comparisons. Results Quantitative anti-S1 serology correlated well with each other (true positives, 96%; true negatives, 97%). Antibody titers decreased over time (< 30 to > 240 days after initial positive RT-PCR). Agreement with GenScript-cPass was 96%/99% for true positives and true negatives, respectively, for Ro-RBD-Ig-quant and 93%/97% for EI-S1-IgG-quant. Ro-RBD-Ig-quant allowed distinct separation between positives and negatives, and less non-specific reactivity versus EI-S1-IgG-quant. Raw values (95% CI) ≥ 28.7 U/mL (22.6–36.4) for Ro-RBD-Ig-quant and ≥ 49.8 U/mL (43.4–57.1) for EI-S1-IgG-quant predicted NT > 1:5 in 95% of cases. Conclusions Our findings suggest both quantitative anti-S1 assays (EI-S1-IgG-quant and Ro-RBD-Ig-quant) may replace direct neutralization assays in quantitative measurement of immune protection against SARS-CoV-2 in certain circumstances. However, although the mean antibody titers for both assays tended to decrease over time, a higher proportion of Ro-RBD-Ig-quant values remained positive after 240 days. Supplementary Information The online version contains supplementary material available at 10.1007/s40121-021-00475-x.
Error messages are frequent in interactions with Conversational User Interfaces (CUI). Smart speakers respond to about every third user request with an error message. Errors can heavily affect user experience (UX) in interaction with CUI. However, there is limited research on how error responses should be formulated. In this paper, we present a system to study how people classify different categories (acknowledgement of user sentiment, acknowledgement of error and apology) of error messages, and evaluate peoples' preference of error responses with clear categories. The results indicate that if an error response has only one element (i.e. neutral acknowledgement of error, apology or sentiment), responses that acknowledge errors neutrally are preferred by participants. Moreover, we find that when interviewed, participants like error messages to include an apology, an explanation of what went wrong, and a suggestion how to fix the problem in addition to a neutral acknowledgement of an error. Our study has two main contributions: (1) our results inform about the design of error messages and (2) we present a framework for error response categorization and validation.
Four of the nine big Technical Universities in Germany, together with Chalmers University of Technology in Sweden, have developed a new Massive Open Online Course (MOOC) on the subject of Communication Acoustics. The idea is to foster education on the late Bachelor or early Master level by joining the expertise available at individual universities and by creating an online course offered both to local as well as remote students. The course started in winter term 2016 and is hosted on the EdX platform. It is offered in English language and roughly divided into two parts: The first part covers basics on acoustics, signal processing, human hearing, speech production, as well as electroacoustics and psychoacoustics. The second part introduces selected applications, such as sound recording and reproduction, sound fields and room acoustics, binaural technology, speech technology, as well as product sound design. The course material consists of explanatory videos and text as well as audiovisual material, exercises, and self-assessments. The final examination takes place as a written or online exam, with physical presence at the contributing sites. The talk will provide insights into the experiences we made, and illustrates how we overcame the obstacles inherent to cross-university education.
Psychological reactance is well known in psychology and marketing, but has not yet been adopted in HCI-research. The authors aim at assessing the benefit of measuring psychological reactance in the context of usability and user experience evaluation in a HCI context. To date, there are no tools that are designed to evaluate psychological reactance in the context of HCI. We used an established questionnaire from personality research for an exploratory factor analysis to test, if the concept can be applied to HCI. A between-subjects study was performed that compared effects of self-adaptive vs. user-adaptable systems on users' psychological reactance while interacting with a spoken dialogue system. Results show that interaction with self-adaptive systems can increase psychological reactance, compared to interaction with user-adaptable systems. It is argued, that the concept of psychological reactance is especially relevant for HCI with regard to smart services and assistants like Apple's Siri.
Background Population-based serological studies allow to estimate prevalence of SARS-CoV-2 infections despite a substantial number of mild or asymptomatic disease courses. This became even more relevant for decision making after vaccination started. The KoCo19 cohort tracks the pandemic progress in the Munich general population for over two years, setting it apart in Europe. Methods Recruitment occurred during the initial pandemic wave, including 5313 participants above 13 years from private households in Munich. Four follow-ups were held at crucial times of the pandemic, with response rates of at least 70%. Participants filled questionnaires on socio-demographics and potential risk factors of infection. From Follow-up 2, information on SARS-CoV-2 vaccination was added. SARS-CoV-2 antibody status was measured using the Roche Elecsys® Anti-SARS-CoV-2 anti-N assay (indicating previous infection) and the Roche Elecsys® Anti-SARS-CoV-2 anti-S assay (indicating previous infection and/or vaccination). This allowed us to distinguish between sources of acquired antibodies. Results The SARS-CoV-2 estimated cumulative sero-prevalence increased from 1.6% (1.1-2.1%) in May 2020 to 14.5% (12.7-16.2%) in November 2021. Underreporting with respect to official numbers fluctuated with testing policies and capacities, becoming a factor of more than two during the second half of 2021. Simultaneously, the vaccination campaign against the SARS-CoV-2 virus increased the percentage of the Munich population having antibodies, with 86.8% (85.5-87.9%) having developed anti-S and/or anti-N in November 2021. Incidence rates for infections after (BTI) and without previous vaccination (INS) differed (ratio INS/BTI of 2.1, 0.7-3.6). However, the prevalence of infections was higher in the non-vaccinated population than in the vaccinated one. Considering the whole follow-up time, being born outside Germany, working in a high-risk job and living area per inhabitant were identified as risk factors for infection, while other socio-demographic and health-related variables were not. Although we obtained significant within-household clustering of SARS-CoV-2 cases, no further geospatial clustering was found. Conclusions Vaccination increased the coverage of the Munich population presenting SARS-CoV-2 antibodies, but breakthrough infections contribute to community spread. As underreporting stays relevant over time, infections can go undetected, so non-pharmaceutical measures are crucial, particularly for highly contagious strains like Omicron.
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