Estimating the proportion of SARS-CoV-2 infections reported through diagnostic testing

The number of positive diagnostic tests for SARS-CoV-2 is a critical metric that is commonly used to assess epidemic severity and the efficacy of current levels of control. However, a proportion of individuals infected with SARS-CoV-2 may never receive a diagnostic test, while many of those who are tested may receive a false negative result. Consequently, cases reported through testing of symptomatic individuals represent only a fraction of the total number of infections, and this proportion is expected to vary depending on changes in natural factors and variability in test-seeking behaviour. Here we combine a number of data sources from England to estimate the proportion of infections that have resulted in a positive diagnosis. Using published estimates of the incubation period distribution and time-dependent test sensitivity, we estimate SARS-CoV-2 incidence from daily reported diagnostic test data. By calibrating this estimate against surveillance data we find that approximately 25% of infections were consistently reported through diagnostic testing before November 2020. This percentage increased through the final months of 2020, predominantly in regions with a large presence of the the UK variant of concern (VOC), before falling rapidly in the last two weeks of January 2021. These changes are not explained by variation in rates of lateral flow device or PCR testing, but are consistent with there being an increased probability for the VOC that infection will result in an eventual positive diagnosis.

Understanding the spread of prevention and cessation messages on social media for substance use in youth

PurposeEngagement is a critical metric to the effectiveness of online health messages. This paper explores how people engage in youth-generated prevention messages in social media.Design/methodology/approachThe data sample consisted of engagement measures of 82 youth-generated messages hosted in a social media channel and a follow-up survey on content creators' motivation for promoting their messages and their dissemination strategies. A comparative analysis of engagement metrics along with qualitative analysis of the message types was performed.FindingsTwo types of messages were considered: stop messages and prevent messages. Our analyses found that people interacted with stop messages on social media more frequently than prevent messages. On analyzing the youth's motivation and promotion strategies, no significant difference was observed between stop message creators and prevent message creators.Social implicationsThis work has implications for programs promoting prevention and health information in social media.Originality/valueThis is the first study in social media-based prevention programs the authors are aware of that differentiated between the strategies of youth-produced prevention messages.

Battery-Aware Electric Truck Delivery Route Exploration

The energy-optimal routing of Electric Vehicles (EVs) in the context of parcel delivery is more complicated than for conventional Internal Combustion Engine (ICE) vehicles, in which the total travel distance is the most critical metric. The total energy consumption of EV delivery strongly depends on the order of delivery because of transported parcel weight changing over time, which directly affects the battery efficiency. Therefore, it is not suitable to find an optimal routing solution with traditional routing algorithms such as the Traveling Salesman Problem (TSP), which use a static quantity (e.g., distance) as a metric. In this paper, we explore appropriate metrics considering the varying transported parcel total weight and achieve a solution for the least-energy delivery problem using EVs. We implement an electric truck simulator based on EV powertrain model and nonlinear battery model. We evaluate different metrics to assess their quality on small size instances for which the optimal solution can be computed exhaustively. A greedy algorithm using the empirically best metric (namely, distance × residual weight) provides significant reductions (up to 33%) with respect to a common-sense heaviest first package delivery route determined using a metric suggested by the battery properties. This algorithm also outperforms the state-of-the-art TSP heuristic algorithms, which consumes up to 12.46% more energy and 8.6 times more runtime. We also estimate how the proposed algorithms work well on real roads interconnecting cities located at different altitudes as a case study.

Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems

User engagement is a critical metric for evaluating the quality of open-domain dialogue systems. Prior work has focused on conversation-level engagement by using heuristically constructed features such as the number of turns and the total time of the conversation. In this paper, we investigate the possibility and efficacy of estimating utterance-level engagement and define a novel metric, predictive engagement, for automatic evaluation of open-domain dialogue systems. Our experiments demonstrate that (1) human annotators have high agreement on assessing utterance-level engagement scores; (2) conversation-level engagement scores can be predicted from properly aggregated utterance-level engagement scores. Furthermore, we show that the utterance-level engagement scores can be learned from data. These scores can be incorporated into automatic evaluation metrics for open-domain dialogue systems to improve the correlation with human judgements. This suggests that predictive engagement can be used as a real-time feedback for training better dialogue models.

A conceptual map of health-related quality of life dimensions: key lessons for a new instrument

Purpose Quality-adjusted life years (QALYs) represent a critical metric in economic evaluations impacting key healthcare decisions in many countries. However, there is widespread disagreement as to which is the best of the health state utility (HSU) instruments that are designed to measure the Q in the QALY. Instruments differ in their descriptive systems as well as their valuation methodologies; that is, they simply measure different things. We propose a visual framework that can be utilized to make meaningful comparisons across HSU instruments. Methods The framework expands on existing HRQoL models, by incorporating four distinctive continua, and by putting HRQoL within the broader notion of subjective well-being (SWB). Using this conceptual map, we locate the five most widely used HSU-instruments (EQ-5D, SF-6D, HUI, 15D, AQoL). Results By individually mapping dimensions onto this visual framework, we provide a clear picture of the significant conceptual and operational differences between instruments. Moreover, the conceptual map demonstrates the varying extent to which each instrument moves outside the traditional biomedical focus of physical health, to also incorporate indicators of mental health and social well-being. Conclusion Our visual comparison provides useful insights to assess the suitability of different instruments for particular purposes. Following on from this comparative analyses, we extract some important lessons for a new instrument that cover the domains of physical, mental and social aspects of health, i.e. it is in alignment with the seminal 1948 WHO definition of health.

More Than IQ: Executive Function Explains Adaptive Behavior Above and Beyond Nonverbal IQ in Youth With Autism and Lower IQ

Adaptive behavior is a critical metric for measuring outcomes in those with autism spectrum disorder (ASD). Executive function skills predict adaptive behavior in youth with ASD with average or higher IQ; however, no study has examined this relationship in ASD with lower IQ (IQ ≤ 75). The current study evaluated whether executive function predicted adaptive behavior in school-age youth with ASD with lower IQ, above and beyond nonverbal IQ. We examined adaptive behavior and executive function through informant report on 100 youth with ASD with lower IQ. Executive function skills explained variance in adaptive social and communication domains, beyond nonverbal IQ; monitoring skills played a significant role. This research suggests that malleable skills like executive function may contribute to functional outcomes in this population.

A Quantitative Perspective on Surface Marker Selection for the Isolation of Functional Tumor Cells

Much effort has gone into developing fluid biopsies of patient peripheral blood for the monitoring of metastatic cancers. One common approach is to isolate and analyze tumor cells in the peripheral blood. Widespread clinical implementation of this approach has been hindered by the current choice of targeting epithelial markers known to be highly variable in primary tumor sites. Here, we review current antigen-based tumor cell isolation strategies and offer biological context for commonly studied cancer surface markers. Expression levels of the most common markers are quantitated for three breast cancer and two non-small cell lung cancer (NSCLC) lineage models. These levels are contrasted with that present on healthy peripheral blood mononuclear cells (PBMC) for comparison to expected background levels in a fluid biopsy setting. A key feature of this work is establishing a metric of markers per square micrometer. This describes an average marker density on the cell membrane surface, which is a critical metric for emerging isolation strategies. These results serve to extend expression of key tumor markers in a sensitive and dynamic manner beyond traditional positive/negative immunohistochemical staining to guide future fluid biopsy targeting strategies.