In Vitro Nasal Tissue Model for the Validation of Nasopharyngeal and Midturbinate Swabs for SARS-CoV-2 Testing.

Large-scale population testing is a key tool to mitigate the spread of respiratory pathogens, such as the current COVID-19 pandemic, where swabs are used to collect samples in the upper airways (e.g., nasopharyngeal and midturbinate nasal cavities) for diagnostics. However, the high volume of supplies required to achieve large-scale population testing has posed unprecedented challenges for swab manufacturing and distribution, resulting in a global shortage that has heavily impacted testing capacity worldwide and prompted the development of new swabs suitable for large-scale production. Newly designed swabs require rigorous preclinical and clinical validation studies that are costly and time-consuming (i.e., months to years long); reducing the risks associated with swab validation is therefore paramount for their rapid deployment. To address these shortages, we developed a 3D-printed tissue model that mimics the nasopharyngeal and midturbinate nasal cavities, and we validated its use as a new tool to rapidly test swab performance. In addition to the nasal architecture, the tissue model mimics the soft nasal tissue with a silk-based sponge lining, and the physiological nasal fluid with asymptomatic and symptomatic viscosities of synthetic mucus. We performed several assays comparing standard flocked and injection-molded swabs. We quantified the swab pickup and release and determined the effect of viral load and mucus viscosity on swab efficacy by spiking the synthetic mucus with heat-inactivated SARS-CoV-2 virus. By molecular assay, we found that injected molded swabs performed similarly or superiorly in comparison to standard flocked swabs, and we underscored a viscosity-dependent difference in cycle threshold values between the asymptomatic and symptomatic mucuses for both swabs. To conclude, we developed an in vitro nasal tissue model that corroborated previous swab performance data from clinical studies; this model will provide to researchers a clinically relevant, reproducible, safe, and cost-effective validation tool for the rapid development of newly designed swabs.

An ecological perspective on early educator well-being at the start of the COVID-19 pandemic.

Early educator well-being is increasingly understood as a critical ingredient of high-quality early education and care. The COVID-19 pandemic has threatened educator well-being by exacerbating existing stressors and introducing novel stressors to all aspects of early educators' lives, and early educators have had differential access to resources to cope with these new circumstances. Using survey data collected between April and June 2020 with a sample of 666 early educators in community-based center, family child care, Head Start, and public school prekindergarten programs across Massachusetts, we document the pandemic's initial influence on educators' sense of well-being. Adopting an ecological perspective, we consider educator-, program-, and community-level factors that may be associated with reported changes in well-being. Most educators indicated that their mental and financial well-being had been affected. These changes were not systematically associated with most contextual factors, although there was clear evidence of variability in reported impacts by provider type. These findings underscore the need to support educator well-being, as well as to create policy solutions that meet the heterogeneous needs of this essential workforce.

Changes in Children's Behavioral Health and Family Well-Being During the COVID-19 Pandemic.

OBJECTIVE: The coronavirus disease 2019 pandemic and associated public health measures have influenced all aspects of life for children and families. In this study, we examine changes in children's behavioral health and families' well-being at the start of the pandemic. METHOD: We used longitudinal data on 2880 children from 1 US state collected over 3 waves to compare family and child well-being before and after a state-wide stay-at-home advisory set in March 2020. We descriptively examined levels and changes in 4 child behavioral health outcomes (externalizing, internalizing, adaptive, and dysregulated behaviors) and 4 family well-being outcomes (parental mental health, parental stress, parent-child relationship conflict, and household chaos) across the preshutdown and postshutdown periods. Fixed effects regression models were used to predict within-child and within-family differences in preshutdown and postshutdown outcomes. RESULTS: Fixed effects analyses showed children's externalizing (0.09 points; 95% confidence interval [CI] 0.05-0.13), internalizing (0.04 points; 95% CI, 0.01-0.08), and dysregulated (0.11 points; 95% CI, 0.06-0.16) behaviors increased after the shutdown, whereas children's adaptive behaviors declined (-0.10 points; 95% CI, -0.15 to -0.05). Parental mental health issues (0.22 points; 95% CI, 0.17-0.27), parental stress (0.08 points; 95% CI, 0.03-0.12), parent-child relationship conflict (0.10 points; 95% CI, 0.04-0.16), and household chaos (0.10 points; 95% CI, 0.05-0.14) all increased relative to preshutdown levels. CONCLUSION: Many children experienced declines in behavioral health and many families experienced declines in well-being in the early months of the public health crisis, suggesting the need for family-focused and child-focused policies to mitigate these changes.