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ObjectivesTo determine whether hydroxychloroquine (HCQ) is safe and effective at preventing COVID-19 infections among health care workers (HCWs).MethodsIn a 1: 1 randomized, placebo-controlled, double-blind, parallel-group, superiority trial at 34 US clinical centers, 1360 HCWs at risk for COVID-19 infection were enrolled between April and November 2020. Participants were randomized to HCQ or matched placebo. The HCQ dosing included a loading dose of HCQ 600 mg twice on day 1, followed by 400 mg daily for 29 days. The primary outcome was a composite of confirmed or suspected COVID-19 clinical infection by day 30, defined as new-onset fever, cough, or dyspnea and either a positive SARS-CoV-2 polymerase chain reaction test (confirmed) or a lack of confirmatory testing due to local restrictions (suspected).ResultsStudy enrollment closed before full accrual due to recruitment challenges. The primary end point occurred in 41 (6.0%) participants receiving HCQ and 53 (7.8%) participants receiving placebo. No difference in the proportion of participants experiencing clinical infection (estimated difference of -1.8%, 95% confidence interval -4.6-0.9%, P = 0.20) was identified nor any significant safety issues.ConclusionOral HCQ taken as prescribed appeared safe among HCWs. No significant clinical benefits were observed. The study was not powered to detect a small but potentially important reduction in infection.Trial registrationNCT04334148.

Wastewater-based epidemiology (WBE) has been deployed broadly as an early warning tool for emerging COVID-19 outbreaks. WBE can inform targeted interventions and identify communities with high transmission, enabling quick and effective responses. As the wastewater (WW) becomes an increasingly important indicator for COVID-19 transmission, more robust methods and metrics are needed to guide public health decision-making. This research aimed to develop and implement a mathematical framework to infer incident cases of COVID-19 from SARS-CoV-2 levels measured in WW. We propose a classification scheme to assess the adequacy of model training periods based on clinical testing rates and assess the sensitivity of model predictions to training periods. A testing period is classified as adequate when the rate of change in testing is greater than the rate of change in cases. We present a Bayesian deconvolution and linear regression model to estimate COVID-19 cases from WW data. The effective reproductive number is estimated from reconstructed cases using WW. The proposed modeling framework was applied to three Northern California communities served by distinct WW treatment plants. The results showed that training periods with adequate testing are essential to provide accurate projections of COVID-19 incidence.

INTRODUCTION: Over a third of the communities (39%) in the Central Valley of California, a richly diverse and important agricultural region, are classified as disadvantaged-with inadequate access to healthcare, lower socio-economic status, and higher exposure to air and water pollution. The majority of racial and ethnic minorities are also at higher risk of COVID-19 infection, hospitalization, and death according to the Centers for Disease Control and Prevention. Healthy Central Valley Together established a wastewater-based disease surveillance (WDS) program that aims to achieve greater health equity in the region through partnership with Central Valley communities and the Sewer Coronavirus Alert Network. WDS offers a cost-effective strategy to monitor trends in SARS-CoV-2 community infection rates. METHODS: In this study, we evaluated correlations between public health and wastewater data (represented as SARS-CoV-2 target gene copies normalized by pepper mild mottle virus target gene copies) collected for three Central Valley communities over two periods of COVID-19 infection waves between October 2021 and September 2022. Public health data included clinical case counts at county and sewershed scales as well as COVID-19 hospitalization and intensive care unit admissions. Lag-adjusted hospitalization:wastewater ratios were also evaluated as a retrospective metric of disease severity and corollary to hospitalization:case ratios. RESULTS: Consistent with other studies, strong correlations were found between wastewater and public health data. However, a significant reduction in case:wastewater ratios was observed for all three communities from the first to the second wave of infections, decreasing from an average of 4.7 ± 1.4 over the first infection wave to 0.8 ± 0.4 over the second. DISCUSSION: The decline in case:wastewater ratios was likely due to reduced clinical testing availability and test seeking behavior, highlighting how WDS can fill data gaps associated with under-reporting of cases. Overall, the hospitalization:wastewater ratios remained more stable through the two waves of infections, averaging 0.5 ± 0.3 and 0.3 ± 0.4 over the first and second waves, respectively.

BackgroundThe SARS CoV-2 virus has caused one of the deadliest pandemics in recent history, resulting in over 170 million deaths and global economic disruption. There remains an urgent need for clinical trials to test therapies for treatment and prevention.DesignAn online research platform was created to support a registry community of healthcare workers (HCWs) to understand their experiences and conduct clinical studies to address their concerns. The first study, HERO-HCQ, was a double-blind, multicenter, randomized, pragmatic trial to evaluate the superiority of hydroxychloroquine (HCQ) vs placebo for pre-exposure prophylaxis (PrEP) of COVID-19 clinical infection in HCWs. Secondary objectives were to assess the efficacy of HCQ in preventing viral shedding of COVID-19 among HCWs and to assess the safety and tolerability of HCQ.MethodsHCWs joined the Registry and were pre-screened for trial interest and eligibility. Trial participants were randomized 1:1 to receive HCQ or placebo. On-site baseline assessment included a COVID-19 nasopharyngeal PCR and blood serology test. Weekly follow-up was done via an online portal and included screening for symptoms of COVID-19, self-reported testing, adverse events, and quality of life assessments. The on-site visit was repeated at Day 30.DiscussionThe HERO research platform offers an approach to rapidly engage, screen, invite and enroll into clinical studies using a novel participant-facing online portal interface and remote data collection, enabling limited onsite procedures for conduct of a pragmatic clinical trial. This platform may be an example for future clinical trials of common conditions to enable more rapid evidence generation.

We investigated changes in students' reported sense of community in the context of a one-semester first-year seminar course using the Community and School Community Inventory (CSCI) research instrument across two years with differing instructional formats. We report a statistically significant increase in students' sense of perceived classroom community, but not school community, from pre- to post-course assessment in both years. Additionally, students' sense of social community is most significantly increased for women, students of color, and first-generation college students, but only when the instruction is face to face. Conversely, no student groups reported an increased sense of social community during online instruction. A significant increase in students' sense of learning community from pre- to post-course assessment was only reported by students who identified as male in 2020, and by no groups in 2019.

Inequities in birth outcomes are linked to experiential and environmental exposures. There have been expanding and intersecting wicked problems of inequity, racism, and quality gaps in childbearing care during the pandemic. We describe how an intentional transdisciplinary process led to development of a novel knowledge exchange vehicle that can improve health equity in perinatal services. We introduce the Quality Perinatal Services Hub, an open access digital platform to disseminate evidence based guidance, enhance health systems accountability, and provide a two-way flow of information between communities and health systems on rights-based perinatal services. The QPS-Hub responds to both community and decision-makers' needs for information on respectful maternity care. The QPS-Hub is well poised to facilitate collaboration between policy makers, healthcare providers and patients, with particular focus on the needs of childbearing families in underserved and historically excluded communities., Author(s): Saraswathi Vedam [sup.1] , Laurie Zephyrin [sup.2] , Pandora Hardtman [sup.3] , Indra Lusero [sup.4] , Rachel Olson [sup.5] , Sonia S. Hassan [sup.6] , Nynke van den Broek [...]

Children's spontaneous focus on numerosity (SFON) is described as an unprompted tendency that is stable across contexts. The attention to number task (AtN), an experimental forced-choice picture-matching task designed to evaluate select aspects of children's focus on numerosity, may reveal whether task materials can implicitly prompt children to focus on numerosity. In two studies, we replicate earlier findings showing an effect of task context on children's performance on the AtN: When asked to identify one or more matches to a target picture from an array of four options, the frequency with which preschoolers and adults identify a numerosity-based match varies as a function of the features on which the remaining match options are based. We addressed a limitation of the original AtN study by including novel combinations of features as additional trials, with which we continued to demonstrate contextual effects. We also showed that adults seemed more susceptible than children to be primed to attend to numerosity on subsequent trials. Children's focus on numerosity under these experimental conditions was remarkably low. We discuss the implications of these findings for better understanding the SFON construct.

Background: Gestational diabetes mellitus (GDM) is a common complication of pregnancy that carries lasting risks. For women who have a history of GDM, the risk of developing type 2 diabetes mellitus (T2DM) increases by 50 to 60%. To monitor and prevent the development of T2DM, guidelines suggest screening those with a history of GDM at 6-weeks and 3-years post-delivery. For patients with abnormal lab results at the 6-week mark, it is advised to complete lab work sooner, at the 1-year mark. Data suggests that these guidelines are not being followed globally, and most do not receive adequate screening for T2DM. Methods: A retroactive chart review of 203 women between 18 and 55 years old with a past medical history significant for GDM was conducted to determine if patients with GDM completed screening for T2DM at 6-week, 1-year, and 3-year timestamps post-delivery. Patient demographics (age, race, ethnicity, language), clinical characteristics (body mass index), provider gender, and whether prediabetes or T2DM developed were recorded. Patients who did not complete the required follow-up received educational materials via the online portal system, and hemoglobin A1c (HbA1c) screening tests were ordered. Results: Ninety days post-intervention, 38 patients (50%) completed the HbA1c screening test, which exceeded our goal of a 5% improvement. Age and BMI 1-year postpartum were found to be significant factors in whether a patient completed HbA1c screening, with 16/18 (89%) completing screening with a healthy BMI 1-year postpartum (18.5 ≤ BMI < 25.0) but only 11/41 (27%) completing screening for patients under 40 years with an unhealthy BMI 1-year postpartum. Of the 38 patients who completed HbA1c screening, 9 (23.7%) had abnormal screening results. Conclusion: Follow-up surveillance for T2DM among women with a history of GDM is poor. Electronic health records can be used to identify and rectify gaps in care. Dissemination of standardized educational materials and electronic order entry for patients improved screening between the handoff from obstetrics to primary care. [ABSTRACT FROM AUTHOR]