Wastewater-based surveillance (WBS) has become a widespread method to monitor transmission of SARS-CoV-2 and other human pathogens in Europe. We conducted a survey about WBS systems\' objectives, approaches, representativeness and usefulness in 10 invited European countries in 2023, i.e. Austria, Belgium, Denmark, Finland, Greece, Hungary, Italy, Luxembourg, the Netherlands and Norway. All countries completed the study questionnaire about their SARS-CoV-2 WBS systems, and shared information about WBS of other pathogens as deemed relevant. SARS-CoV-2 WBS systems primarily monitored national and subnational trends (population coverage: 25-99%), and a majority (8/10) also tracked variant distribution. Nine of 10 countries reported that their SARS-CoV-2 WBS systems were representative of their population and all countries remarked that the findings were valuable for public health decision-making. Results were shared with relevant public health authorities and published via dedicated websites and/or dashboards. WBS systems of other pathogens were mostly in the early stages, with some countries implementing pilots. Notable exceptions were the well-established poliovirus surveillance systems in Finland, Italy and the Netherlands. This study brings understanding the diverse landscape of WBS in Europe, offering insights for future developments and collaborations. Furthermore, it highlights the need for further integration of WBS into other European surveillance systems.

Anticipation is key to performance in many sports. By definition, anticipation as a perceptual-cognitive process is meant to inform action and help athletes reduce potential motor costs under spatiotemporal pressure. Anticipation research has repeatedly been criticized for neglecting action and raised the need for predominant testing under conditions of perception-action coupling (PAC). To the best of our knowledge, however, there is a lack of explicit criteria to characterize and define PAC conditions. This can lead to blurred terminology and may complicate interpretation and comparability of PAC conditions and results across studies. Here, we make a first proposal for a 7-level classification of PAC conditions with the defining dimensions of stimulus presentation and response mode. We hope this classification may constitute a helpful orientation for study planning and reporting in research on anticipation. Further, we illustrate the potential utilization of the PAC classification as a template for experimental protocol analysis in a review on anticipation in racket sports. Analysis of N = 115 studies reported in N = 91 articles confirms an underrepresentation of representative PAC conditions and reveals little change in PAC approaches over more than 40 years of research in that domain. We discuss potential reasons for these findings, the benefits of adopting the proposed PAC classification and reiterate the call for more action in anticipation research.

UNASSIGNED: South Korea has implemented a hand, foot, and mouth disease (HFMD) surveillance system since 2009 to monitor incidence trends and identify disease burden. This nationwide surveillance involves a network of approximately 100 pediatric clinics that report all probable and confirmed HFMD cases. Following the COVID-19 pandemic, infectious disease surveillance systems must be evaluated to ensure the effective use of limited public health resources.
UNASSIGNED: This study aimed to evaluate the HFMD sentinel surveillance system in South Korea from 2017 to 2022, focusing on the transition period after the COVID-19 pandemic.
UNASSIGNED: We retrospectively reviewed the HFMD sentinel surveillance system from the Korea Disease Control and Prevention Agency using systematic guidelines for public health surveillance system evaluation developed by the US Centers for Disease Control and Prevention. We assessed the system\'s overall performance in 5 main factors: timeliness, stability, completeness, sensitivity, and representativeness (ie, the age and geographic distribution of sentinels). We rated these factors as weak, moderate, or good.
UNASSIGNED: Our study showed that the completeness, sensitivity, and age representativeness of the HFMD surveillance performance were temporarily reduced to moderate levels from 2020 to 2021 and recovered in 2022, while the timeliness and geographic representativeness were maintained at a good level throughout the study period. The stability of the surveillance was moderate from 2017 to 2021 and weak in 2022.
UNASSIGNED: This is the first study to evaluate the HFMD surveillance system after the acute phase of the COVID-19 pandemic. We identified a temporarily reduced level of performance (ie, completeness, sensitivity, and age-specific representativeness) during the acute phase of the pandemic and good performance in 2022. Surveillance system evaluation and maintenance during public health emergencies will provide robust and reliable data to support public health policy development. Regular staff training programs and reducing staff turnover will improve HFMD surveillance system stability.

BACKGROUND: Recruitment for surveys has been a great challenge, especially in general practice.
METHODS: Here, we reported recruitment strategies, data collection, participation rates (PR) and representativeness of the PRICOV-19 study, an international comparative, cross-sectional, online survey among general practices (GP practices) in 37 European countries and Israel.
RESULTS: Nine (24%) countries reported a published invitation; 19 (50%) had direct contact with all GPs/GP practices; 19 (50%) contacted a sample of GPs /GP practices; and 7 (18%) used another invitation strategy. The median participation rate was 22% (IQR = 10%, 28%). Multiple invitation strategies (P-value 0.93) and multiple strategies to increase PR (P-value 0.64) were not correlated with the PR. GP practices in (semi-) rural areas, GP practices serving more than 10,000 patients, and group practices were over-represented (P-value < 0.001). There was no significant correlation between the PR and strength of the primary care (PC) system [Spearman\'s r 0.13, 95% CI (-0.24, 0.46); P-value 0.49]; the COVID-19 morbidity [Spearman\'s r 0.19, 95% CI (-0.14, 0.49); P-value 0.24], or COVID-19 mortality [Spearman\'s r 0.19, 95% CI (-0.02, 0.58); P-value 0.06] during the three months before country-specific study commencement.
CONCLUSIONS: Our main contribution here was to describe the survey recruitment and representativeness of PRICOV-19, an important and novel study.

BACKGROUND: Findings from studies assessing Long Covid in children and young people (CYP) need to be assessed in light of their methodological limitations. For example, if non-response and/or attrition over time systematically differ by sub-groups of CYP, findings could be biased and any generalisation limited. The present study aimed to (i) construct survey weights for the Children and young people with Long Covid (CLoCk) study, and (ii) apply them to published CLoCk findings showing the prevalence of shortness of breath and tiredness increased over time from baseline to 12-months post-baseline in both SARS-CoV-2 Positive and Negative CYP.
METHODS: Logistic regression models were fitted to compute the probability of (i) Responding given envisioned to take part, (ii) Responding timely given responded, and (iii) (Re)infection given timely response. Response, timely response and (re)infection weights were generated as the reciprocal of the corresponding probability, with an overall \'envisioned population\' survey weight derived as the product of these weights. Survey weights were trimmed, and an interactive tool developed to re-calibrate target population survey weights to the general population using data from the 2021 UK Census.
RESULTS: Flexible survey weights for the CLoCk study were successfully developed. In the illustrative example, re-weighted results (when accounting for selection in response, attrition, and (re)infection) were consistent with published findings.
CONCLUSIONS: Flexible survey weights to address potential bias and selection issues were created for and used in the CLoCk study. Previously reported prospective findings from CLoCk are generalisable to the wider population of CYP in England. This study highlights the importance of considering selection into a sample and attrition over time when considering generalisability of findings.

BACKGROUND: Studies confirm that significant biases exist in online recommendation platforms, exacerbating pre-existing disparities and leading to less-than-optimal outcomes for underrepresented demographics. We study issues of bias in inclusion and representativeness in the context of healthcare information disseminated via videos on the YouTube social media platform, a widely used online channel for multi-media rich information. With one in three US adults using the Internet to learn about a health concern, it is critical to assess inclusivity and representativeness regarding how health information is disseminated by digital platforms such as YouTube.
METHODS: Leveraging methods from fair machine learning (ML), natural language processing and voice and facial recognition methods, we examine inclusivity and representativeness of video content presenters using a large corpus of videos and their metadata on a chronic condition (diabetes) extracted from the YouTube platform. Regression models are used to determine whether presenter demographics impact video popularity, measured by the video\'s average daily view count. A video that generates a higher view count is considered to be more popular.
RESULTS: The voice and facial recognition methods predicted the gender and race of the presenter with reasonable success. Gender is predicted through voice recognition (accuracy = 78%, AUC = 76%), while the gender and race predictions use facial recognition (accuracy = 93%, AUC = 92% and accuracy = 82%, AUC = 80%, respectively). The gender of the presenter is more significant for video views only when the face of the presenter is not visible while videos with male presenters with no face visibility have a positive relationship with view counts. Furthermore, videos with white and male presenters have a positive influence on view counts while videos with female and non - white group have high view counts.
CONCLUSIONS: Presenters\' demographics do have an influence on average daily view count of videos viewed on social media platforms as shown by advanced voice and facial recognition algorithms used for assessing inclusion and representativeness of the video content. Future research can explore short videos and those at the channel level because popularity of the channel name and the number of videos associated with that channel do have an influence on view counts.

UNASSIGNED: Distinctive differences in multiple sclerosis (MS) have been observed by race and ethnicity. We aim to (1) assess how often race and ethnicity were reported in clinical trials registered on ClinicalTrials.gov, (2) evaluate whether the population was diverse enough, and (3) compare with publications.
UNASSIGNED: We included phase 3 clinical trials registered with results on ClinicalTrials.gov between 2007 and 2023. When race and/or ethnicity were reported, we searched for the corresponding publications.
UNASSIGNED: Out of the 99 included studies, 56% reported race and/or ethnicity, of which only 26% of those primarily completed before 2017. Studies reporting race or ethnicity contributed to a total of 33,891 participants, mainly enrolled in Eastern Europe. Most were White (93%), and the median percentage of White participants was 93% (interquartile range (IQR) = 86%-98%), compared to 3% for Black (IQR = 1%-12%) and 0.2% for Asian (IQR = 0%-1%). Four trials omitted race and ethnicity in publications and even when information was reported, some discrepancies in terminology were identified and categories with fewer participants were often collapsed.
UNASSIGNED: More efforts should be done to improve transparency, accuracy, and representativeness, in publications and at a design phase, by addressing social determinants of health that historically limit the enrollment of underrepresented population.

UNASSIGNED: Pragmatic trials often implement an intervention across a population of patients but require information unavailable at the population level that must be reported by a subset of patients. In this pragmatic clinical trial, we compared characteristics of seriously ill patients with those who completed a survey evaluating advance care planning across 3 academic health systems.
UNASSIGNED: A deliberate process including health system and external stakeholders and patients was used to design materials for and the approach to seriously ill patients. We developed a survey and conducted a multistep process to identify seriously ill primary care patients. We evaluated the relationships of age, gender, race and ethnicity, and vulnerability using the social vulnerability index in this population, and explored the representativeness of survey respondents compared with the underlying seriously ill population in terms of age, race and ethnicity, and vulnerability measured.
UNASSIGNED: About 5% (8707 patients) of the primary care population was classified as seriously ill, 5351 were mailed a survey and 1100 provided survey responses. Hispanic and Black patients were younger than White patients, and Black and Hispanic patients were more vulnerable than White and Asian patients and patients of other races. Representativeness was high across age and race and ethnicity, although White and Hispanic patients were more likely to respond than Black and Asian patients and patients of other races. Vulnerability in the surveyed sample was nearly identical to the population.
UNASSIGNED: A tailored survey and recruitment strategy yielded a representative sample of seriously ill, largely older, primary care respondents in the context of a pragmatic clinical trial.

In this chapter, we consider lack of racial, ethnic, and geographic diversity in research studies from a public health perspective in which representation of a target population is critical. We review the state of the research field with respect to racial, ethnic, and geographic diversity in study participants. We next focus on key factors which can arise from the lack of diversity and can negatively impact external validity. Finally, we argue that the public\'s health, and future research, will ultimately be served by approaches from both recruitment and representation science and population neuroscience, and we close with recommendations from these two fields to improve diversity in studies.

The U.S. Centers for Disease Control and Prevention (CDC) received surveillance data on how many people tested positive for SARS-CoV-2, but there was little information about what individuals did to mitigate transmission. To fill the information gap, we conducted an online, probability-based survey among a nationally representative panel of adults living in the United States to better understand the behaviors of individuals following a positive SARS-CoV-2 test result. Given the low response rates commonly associated with panel surveys, we assessed how well the survey data aligned with CDC surveillance data from March, 2020 to March, 2022. We used CDC surveillance data to calculate monthly aggregated COVID-19 case counts and compared these to monthly COVID-19 case counts captured by our survey during the same period. We found high correlation between our overall survey data estimates and monthly case counts reported to the CDC during the analytic period (r: +0.94; p < 0.05). When stratified according to demographic characteristics, correlations remained high. These correlations strengthened our confidence that the panel survey participants were reflective of the cases reported to CDC and demonstrated the potential value of panel surveys to inform decision making.