In-person schooling and associated COVID-19 risk in the United States over spring semester 2021

What is the specific role of schools and daycares in COVID-19 transmission? A final report from a living rapid review

Due to rapidly evolving conditions, the question of how to safely operate schools and daycares remained a top priority throughout the COVID-19 pandemic. In response to growing and changing evidence, the National Collaborating Centre for Methods and Tools in Canada maintained a living rapid review on the role of schools and daycares in COVID-19 transmission to guide evidence-informed decision making. This Review presents the final iteration of this living rapid review. 31 sources were searched until Oct 17, 2022. In the final version, eligible studies reported data from Jan 1, 2021 onward on transmission of COVID-19 in school or daycare settings, the effect of infection prevention and control measures on transmission, or the effect of operating schools or daycares on community-level COVID-19 rates. As a rapid review, titles and abstracts were screened by a single reviewer with artificial intelligence integrated into later versions. Full-text screening, data extraction, and critical appraisal were completed by one reviewer and checked by a second reviewer. The Johanna Briggs Institute tools were used for critical appraisal. The certainty of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach, and results were synthesised narratively. Three citizen partners provided input for the final interpretation. This final update includes 73 primary studies. Secondary attack rates were low within school settings when infection prevention and control measures were in place (moderate certainty). Masks might reduce transmission, test-to-stay policies might not increase transmission risk compared with mandatory quarantine, cohorting and hybrid learning might make little to no difference in transmission (low certainty), and the effect of surveillance testing within schools remained inconclusive (very low certainty). Findings indicate that school settings do not substantially contribute to community incidence, hospitalisations, or mortality (low certainty). This living review provides a synthesis of global evidence for the role of schools and daycares during COVID-19, which might be helpful in future pandemics.

Estimating SARS-CoV-2 transmission parameters between coinciding outbreaks in a university population and the surrounding community

Prior studies suggest that population heterogeneity in SARS-CoV-2 (COVID-19) transmission plays an important role in epidemic dynamics. During the fall of 2020, many US universities and the surrounding communities experienced an increase in reported incidence of SARS-CoV-2 infections, with a high disease burden among students. We explore the transmission dynamics of an outbreak of SARS-CoV-2 among university students, how it impacted the non-student population via cross-transmission, and how it could influence pandemic planning and response. Using surveillance data of reported SARS-CoV-2 cases, we developed a two-population SEIR model to estimate transmission parameters and evaluate how these subpopulations interacted during the 2020 Fall semester. We estimated the transmission rate among the university students (βU) and community residents (βC), as well as the rate of cross-transmission between the two subpopulations (βM) using particle Markov Chain Monte Carlo (pMCMC) simulation-based methods. We found that both populations were more likely to interact with others in their population and that cross-transmission was minimal. The cross-transmission estimate (βM) was considerably smaller [0.04 × 10-5 (95% CI: 0.00 × 10-5, 0.15 × 10-5)] compared to the community estimate (βC) at 2.09 × 10-5 (95% CI: 1.12 × 10-5, 2.90 × 10-5) and university estimate (βU) at 27.92 × 10-5 (95% CI: 19.97 × 10-5, 39.15 × 10-5). The higher within population transmission rates among the university and the community (698 and 52 times higher, respectively) when compared to the cross-transmission rate, suggests that these two populations did not transmit between each other heavily, despite their geographic overlap. During the first wave of the pandemic, two distinct epidemics occurred among two subpopulations within a relatively small US county population where university students accounted for roughly 41% of the total population. Transmission parameter estimates varied substantially with minimal or no cross-transmission between the subpopulations. Assumptions that county-level and other small populations are well-mixed during a respiratory viral pandemic should be reconsidered. More granular models reflecting overlapping subpopulations may assist with better-targeted interventions for local public health and healthcare facilities.

Prevalence of high-risk conditions for severe COVID-19 among Medicaid-enrolled children with autism and mental health diagnoses in the United States

LAY ABSTRACT

Children are at risk of varying severity of illness and even death from COVID-19. We aim to determine whether autistic children or children with mental health conditions have more underlying health conditions that put people at risk of severe illness from COVID-19. We use data from a national sample of Medicaid-enrolled children for the years 2008-2016. These data include children across the 50 states and the District of Columbia. We compare the prevalence of underlying conditions among autistic children and children with mental health condition to that of other children in Medicaid. This study included 888,487 autistic children, 423,397 with any mental health condition (but not autism), and 932,625 children without any of these diagnoses. We found 29.5% of autistic children and 25.2% of children with mental health conditions had an underlying condition with high risk for severe illness from COVID, compared to 14.1% of children without these diagnoses. Autistic children had over twice the odds of having any underlying conditions, when accounting for age, race, sex, and other characteristics. Children with mental health conditions had 70% higher odds of having these underlying conditions. Mitigation measures in schools and other areas could minimize risk of short- and long-term impacts from COVID for autistic and all children.

COVID-19 Policies, Pandemic Disruptions, and Changes in Child Mental Health and Sleep in the United States

IMPORTANCE

The adverse effects of COVID-19 containment policies disrupting child mental health and sleep have been debated. However, few current estimates correct biases of these potential effects.

OBJECTIVES

To determine whether financial and school disruptions related to COVID-19 containment policies and unemployment rates were separately associated with perceived stress, sadness, positive affect, COVID-19-related worry, and sleep.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was based on the Adolescent Brain Cognitive Development Study COVID-19 Rapid Response Release and used data collected 5 times between May and December 2020. Indexes of state-level COVID-19 policies (restrictive, supportive) and county-level unemployment rates were used to plausibly address confounding biases through 2-stage limited information maximum likelihood instrumental variables analyses. Data from 6030 US children aged 10 to 13 years were included. Data analysis was conducted from May 2021 to January 2023.

EXPOSURES

Policy-induced financial disruptions (lost wages or work due to COVID-19 economic impact); policy-induced school disruptions (switches to online or partial in-person schooling).

MAIN OUTCOMES AND MEASURES

Perceived stress scale, National Institutes of Health (NIH)-Toolbox sadness, NIH-Toolbox positive affect, COVID-19-related worry, and sleep (latency, inertia, duration).

RESULTS

In this study, 6030 children were included in the mental health sample (weighted median [IQR] age, 13 [12-13] years; 2947 [48.9%] females, 273 [4.5%] Asian children, 461 [7.6%] Black children, 1167 [19.4%] Hispanic children, 3783 [62.7%] White children, 347 [5.7%] children of other or multiracial ethnicity). After imputing missing data, experiencing financial disruption was associated with a 205.2% [95% CI, 52.9%-509.0%] increase in stress, a 112.1% [95% CI, 22.2%-268.1%] increase in sadness, 32.9% [95% CI, 3.5%-53.4%] decrease in positive affect, and a 73.9 [95% CI, 13.2-134.7] percentage-point increase in moderate-to-extreme COVID-19-related worry. There was no association between school disruption and mental health. Neither school disruption nor financial disruption were associated with sleep.

CONCLUSIONS AND RELEVANCE

To our knowledge, this study presents the first bias-corrected estimates linking COVID-19 policy-related financial disruptions with child mental health outcomes. School disruptions did not affect indices of children's mental health. These findings suggest public policy should consider the economic impact on families due to pandemic containment measures, in part to protect child mental health until vaccines and antiviral drugs become available.

Lifting Universal Masking in Schools - Covid-19 Incidence among Students and Staff

BACKGROUND

In February 2022, Massachusetts rescinded a statewide universal masking policy in public schools, and many Massachusetts school districts lifted masking requirements during the subsequent weeks. In the greater Boston area, only two school districts - the Boston and neighboring Chelsea districts - sustained masking requirements through June 2022. The staggered lifting of masking requirements provided an opportunity to examine the effect of universal masking policies on the incidence of coronavirus disease 2019 (Covid-19) in schools.

METHODS

We used a difference-in-differences analysis for staggered policy implementation to compare the incidence of Covid-19 among students and staff in school districts in the greater Boston area that lifted masking requirements with the incidence in districts that sustained masking requirements during the 2021-2022 school year. Characteristics of the school districts were also compared.

RESULTS

Before the statewide masking policy was rescinded, trends in the incidence of Covid-19 were similar across school districts. During the 15 weeks after the statewide masking policy was rescinded, the lifting of masking requirements was associated with an additional 44.9 cases per 1000 students and staff (95% confidence interval, 32.6 to 57.1), which corresponded to an estimated 11,901 cases and to 29.4% of the cases in all districts during that time. Districts that chose to sustain masking requirements longer tended to have school buildings that were older and in worse condition and to have more students per classroom than districts that chose to lift masking requirements earlier. In addition, these districts had higher percentages of low-income students, students with disabilities, and students who were English-language learners, as well as higher percentages of Black and Latinx students and staff. Our results support universal masking as an important strategy for reducing Covid-19 incidence in schools and loss of in-person school days. As such, we believe that universal masking may be especially useful for mitigating effects of structural racism in schools, including potential deepening of educational inequities.

CONCLUSIONS

Among school districts in the greater Boston area, the lifting of masking requirements was associated with an additional 44.9 Covid-19 cases per 1000 students and staff during the 15 weeks after the statewide masking policy was rescinded.

Simulating respiratory disease transmission within and between classrooms to assess pandemic management strategies at schools

The global spread of coronavirus disease 2019 (COVID-19) has emphasized the need for evidence-based strategies for the safe operation of schools during pandemics that balance infection risk with the society's responsibility of allowing children to attend school. Due to limited empirical data, existing analyses assessing school-based interventions in pandemic situations often impose strong assumptions, for example, on the relationship between class size and transmission risk, which could bias the estimated effect of interventions, such as split classes and staggered attendance. To fill this gap in school outbreak studies, we parameterized an individual-based model that accounts for heterogeneous contact rates within and between classes and grades to a multischool outbreak data of influenza. We then simulated school outbreaks of respiratory infectious diseases of ongoing threat (i.e., COVID-19) and potential threat (i.e., pandemic influenza) under a variety of interventions (changing class structures, symptom screening, regular testing, cohorting, and responsive class closures). Our results suggest that interventions changing class structures (e.g., reduced class sizes) may not be effective in reducing the risk of major school outbreaks upon introduction of a case and that other precautionary measures (e.g., screening and isolation) need to be employed. Class-level closures in response to detection of a case were also suggested to be effective in reducing the size of an outbreak.