Model-based projections for COVID-19 outbreak size and student-days lost to closure in Ontario childcare centres and primary schools

The effect of smaller classes on infection-related school absence: evidence from the Project STAR randomized controlled trial

BACKGROUND

In an effort to reduce viral transmission, many schools reduced class sizes during the recent pandemic. Yet the effect of class size on transmission is unknown.

METHODS

We used data from Project STAR, a randomized controlled trial in which 10,816 Tennessee elementary students were assigned at random to smaller classes (13 to 17 students) or larger classes (22 to 26 students) in 1985-89. We merged Project STAR schools with data on local deaths from pneumonia and influenza in the 122 Cities Mortality Report System. Using mixed effects linear, Poisson, and negative binomial regression, we estimated the main effect of smaller classes on absence. We used an interaction to test whether the effect of small classes on absence was larger when and where community pneumonia and influenza prevalence was high.

RESULTS

Small classes reduced absence by 0.43 days/year (95% CI -0.06 to -0.80, p < 0.05), but small classes had no significant interaction with community pneumonia and influenza mortality (95% CI -0.27 to + 0.30, p > 0.90), indicating that the reduction in absence due to small classes was not larger when community disease prevalence was high.

CONCLUSION

Small classes reduced absence, but the reduction was not larger when disease prevalence was high, so the reduction in absence was not necessarily achieved by reducing infection. Small classes, by themselves, may not suffice to reduce the spread of respiratory viruses.

A descriptive study of COVID-19 cases in primary and secondary schools in the Maltese islands: a nationwide experience

BACKGROUND

As part of the measures to contain the initial cases of Coronavirus Disease (COVID-19) in 2020, all educational facilities were closed in March 2020 and remained so for the remainder of that scholastic year. When they reopened in October 2020, most educational facilities on the Maltese islands did so with various mitigation measures in place.

METHODS

A Schools Contact Tracing Team (SCTT) dedicated to the management of COVID-19 cases within schools was set up and networks established between the Ministries responsible for Health and Education to facilitate timely communication and, consequently, effective contact tracing. All cases pertaining to educational facilities, be they students, teaching or non-teaching staff were assessed and managed by this Team.

RESULTS

Between October 2020 and June 2021, the SCTT assessed 2603 COVID-19 cases within educational facilities in Malta. The highest rate of cases overall was observed in teaching staff (56.53/1000). In 72.45% of cases, no contacts were identified as high risk and thus nobody was placed in quarantine. In 3.07% of school cases >21 high-risk contacts were placed in mandatory quarantine together with their household members. Only 11% of the cases were epi-linked to another positive case within school.

CONCLUSIONS

The strong collaboration between the health and education authorities combined with strict measures observed in schools ensured that schools remained open throughout most of this pandemic. This study describes the processes by which contact tracing for COVID-19 cases in Maltese schools was carried out and analyses the data collected throughout the scholastic year 2020-21.

A Longitudinal Cohort Study of Youth Mental Health and Substance use Before and During the COVID-19 Pandemic in Ontario, Canada: An Exploratory Analysis

BACKGROUND

Youth mental health appears to have been negatively impacted by the COVID-19 pandemic. The impact on substance use is less clear, as is the impact on subgroups of youth, including those with pre-existing mental health or substance use challenges.

OBJECTIVE

This hypothesis-generating study examines the longitudinal evolution of youth mental health and substance use from before the COVID-19 pandemic to over one year into the pandemic among youth with pre-existing mental health or substance use challenges.

METHOD

A total of 168 youth aged 14-24 participated. Participants provided sociodemographic data, as well as internalizing disorder, externalizing disorder, and substance use data prior to the pandemic's onset, then every two months between April 2020-2021. Linear mixed models and Generalized Estimating Equations were used to analyze the effect of time on mental health and substance use. Exploratory analyses were conducted to examine interactions with sociodemographic and clinical characteristics.

RESULTS

There was no change in internalizing or externalizing disorder scores from prior to the pandemic to any point throughout the first year of the pandemic. Substance use scores during the pandemic declined compared to pre-pandemic scores. Exploratory analyses suggest that students appear to have experienced more mental health repercussions than non-students; other sociodemographic and clinical characteristics did not appear to be associated with mental health or substance use trajectories.

CONCLUSIONS

While mental health remained stable and substance use declined from before the COVID-19 pandemic to during the pandemic among youth with pre-existing mental health challenges, some youth experienced greater challenges than others. Longitudinal monitoring among various population subgroups is crucial to identifying higher risk populations. This information is needed to provide empirical evidence to inform future research directions.

Evaluation of Real-life Use of Point-of-care Rapid Antigen Testing for SARS-CoV-2 in Schools (EPOCRATES): a cohort study

BACKGROUND

SARS-CoV-2 transmission has an impact on education. In this study, we assessed the performance of rapid antigen detection tests (RADTs) versus polymerase chain reaction (PCR) for the diagnosis of SARS-CoV-2 infection in school settings, and RADT use for monitoring exposed contacts.

METHODS

In this real-world, prospective observational cohort study, high-school students and staff were recruited from 2 high schools in Montréal, Canada, and followed from Jan. 25 to June 10, 2021. Twenty-five percent of asymptomatic participants were tested weekly by RADT (nasal) and PCR (gargle). Class contacts of cases were tested. Symptomatic participants were tested by RADT (nasal) and PCR (nasal and gargle). The number of cases and outbreaks were compared with those of other high schools in the same area.

RESULTS

Overall, 2099 students and 286 school staff members consented to participate. The overall specificity of RADTs varied from 99.8% to 100%, with a lower sensitivity, varying from 28.6% in asymptomatic to 83.3% in symptomatic participants. Secondary cases were identified in 10 of 35 classes. Returning students to school after a 7-day quarantine, with a negative PCR result on days 6-7 after exposure, did not lead to subsequent outbreaks. Of cases for whom the source was known, 37 of 51 (72.5%) were secondary to household transmission, 13 (25.5%) to intraschool transmission, and 1 to community contacts between students in the same school.

INTERPRETATION

Rapid antigen detection tests did not perform well compared with PCR in asymptomatic individuals. Reinforcing policies for symptom screening when entering schools and testing symptomatic individuals with RADTs on the spot may avoid subsequent substantial exposures in class. Preprint: medRxiv - doi.org/10.1101/2021.10.13.21264960.

COVID-19 Exposure Assessment Tool (CEAT): Exposure quantification based on ventilation, infection prevalence, group characteristics, and behavior

The coronavirus disease 2019 (COVID-19) Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for various scenarios, providing understanding of how combinations of protective measures affect risk. CEAT incorporates mechanistic, stochastic, and epidemiological factors including the (i) emission rate of virus, (ii) viral aerosol degradation and removal, (iii) duration of activity/exposure, (iv) inhalation rates, (v) ventilation rates (indoors/outdoors), (vi) volume of indoor space, (vii) filtration, (viii) mask use and effectiveness, (ix) distance between people (taking into account both near-field and far-field effects of proximity), (x) group size, (xi) current infection rates by variant, (xii) prevalence of infection and immunity in the community, (xiii) vaccination rates, and (xiv) implementation of COVID-19 testing procedures. CEAT applied to published studies of COVID-19 transmission events demonstrates the model's accuracy. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures.

Unintended consequences of measures implemented in the school setting to contain the COVID-19 pandemic: a scoping review

BACKGROUND

With the emergence of SARS-CoV-2 in late 2019, governments worldwide implemented a multitude of non-pharmaceutical interventions in order to control the spread of the virus. Most countries have implemented measures within the school setting in order to reopen schools or keep them open whilst aiming to contain the spread of SARS-CoV-2. For informed decision-making on implementation, adaptation, or suspension of such measures, it is not only crucial to evaluate their effectiveness with regard to SARS-CoV-2 transmission, but also to assess their unintended consequences.

OBJECTIVES

To comprehensively identify and map the evidence on the unintended health and societal consequences of school-based measures to prevent and control the spread of SARS-CoV-2. We aimed to generate a descriptive overview of the range of unintended (beneficial or harmful) consequences reported as well as the study designs that were employed to assess these outcomes. This review was designed to complement an existing Cochrane Review on the effectiveness of these measures by synthesising evidence on the implications of the broader system-level implications of school measures beyond their effects on SARS-CoV-2 transmission.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, four non-health databases, and two COVID-19 reference collections on 26 March 2021, together with reference checking, citation searching, and Google searches.

SELECTION CRITERIA

We included quantitative (including mathematical modelling), qualitative, and mixed-methods studies of any design that provided evidence on any unintended consequences of measures implemented in the school setting to contain the SARS-CoV-2 pandemic. Studies had to report on at least one unintended consequence, whether beneficial or harmful, of one or more relevant measures, as conceptualised in a logic model.  DATA COLLECTION AND ANALYSIS: We screened the titles/abstracts and subsequently full texts in duplicate, with any discrepancies between review authors resolved through discussion. One review author extracted data for all included studies, with a second review author reviewing the data extraction for accuracy. The evidence was summarised narratively and graphically across four prespecified intervention categories and six prespecified categories of unintended consequences; findings were described as deriving from quantitative, qualitative, or mixed-method studies.

MAIN RESULTS

Eighteen studies met our inclusion criteria. Of these, 13 used quantitative methods (3 experimental/quasi-experimental; 5 observational; 5 modelling); four used qualitative methods; and one used mixed methods. Studies looked at effects in different population groups, mainly in children and teachers. The identified interventions were assigned to four broad categories: 14 studies assessed measures to make contacts safer; four studies looked at measures to reduce contacts; six studies assessed surveillance and response measures; and one study examined multiple measures combined. Studies addressed a wide range of unintended consequences, most of them considered harmful. Eleven studies investigated educational consequences. Seven studies reported on psychosocial outcomes. Three studies each provided information on physical health and health behaviour outcomes beyond COVID-19 and environmental consequences. Two studies reported on socio-economic consequences, and no studies reported on equity and equality consequences.

AUTHORS' CONCLUSIONS

We identified a heterogeneous evidence base on unintended consequences of measures implemented in the school setting to prevent and control the spread of SARS-CoV-2, and summarised the available study data narratively and graphically. Primary research better focused on specific measures and various unintended outcomes is needed to fill knowledge gaps and give a broader picture of the diverse unintended consequences of school-based measures before a more thorough evidence synthesis is warranted. The most notable lack of evidence we found was regarding psychosocial, equity, and equality outcomes. We also found a lack of research on interventions that aim to reduce the opportunity for contacts. Additionally, study investigators should provide sufficient data on contextual factors and demographics in order to ensure analyses of such are feasible, thus assisting stakeholders in making appropriate, informed decisions for their specific circumstances.

Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK

Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations.

Assessing the impact of lateral flow testing strategies on within-school SARS-CoV-2 transmission and absences: A modelling study

Rapid testing strategies that replace the isolation of close contacts through the use of lateral flow device tests (LFTs) have been suggested as a way of controlling SARS-CoV-2 transmission within schools that maintain low levels of pupil absences. We developed an individual-based model of a secondary school formed of exclusive year group bubbles (five year groups, with 200 pupils per year) to assess the likely impact of strategies using LFTs in secondary schools over the course of a seven-week half-term on transmission, absences, and testing volume, compared to a policy of isolating year group bubbles upon a pupil returning a positive polymerase chain reaction (PCR) test. We also considered the sensitivity of results to levels of participation in rapid testing and underlying model assumptions. While repeated testing of year group bubbles following case detection is less effective at reducing infections than a policy of isolating year group bubbles, strategies involving twice weekly mass testing can reduce infections to lower levels than would occur under year group isolation. By combining regular testing with serial contact testing or isolation, infection levels can be reduced further still. At high levels of pupil participation in lateral flow testing, strategies replacing the isolation of year group bubbles with testing substantially reduce absences, but require a high volume of testing. Our results highlight the conflict between the goals of minimising within-school transmission, minimising absences and minimising testing burden. While rapid testing strategies can reduce school transmission and absences, they may lead to a large number of daily tests.

Covid-19 Exposure Assessment Tool (CEAT): Easy-to-use tool to quantify exposure based on airflow, group behavior, and infection prevalence in the community

The COVID-19 Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to SARS-CoV-2 for various scenarios, providing understanding of how combinations of protective measures affect exposure, dose, and risk. CEAT incorporates mechanistic, stochastic and epidemiological factors including the: 1) emission rate of virus, 2) viral aerosol degradation and removal, 3) duration of activity/exposure, 4) inhalation rates, 5) ventilation rates (indoors/outdoors), 6) volume of indoor space, 7) filtration, 8) mask use and effectiveness, 9) distance between people, 10) group size, 11) current infection rates by variant, 12) prevalence of infection and immunity in the community, 13) vaccination rates of the community, and 14) implementation of COVID-19 testing procedures. Demonstration of CEAT, from published studies of COVID-19 transmission events, shows the model accurately predicts transmission. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures. Given its accuracy and flexibility, the wide use of CEAT will have a long lasting beneficial impact in managing both the current COVID-19 pandemic as well as a variety of other scenarios.

Quantifying pupil-to-pupil SARS-CoV-2 transmission and the impact of lateral flow testing in English secondary schools

A range of measures have been implemented to control within-school SARS-CoV-2 transmission in England, including the self-isolation of close contacts and twice weekly mass testing of secondary school pupils using lateral flow device tests (LFTs). Despite reducing transmission, isolating close contacts can lead to high levels of absences, negatively impacting pupils. To quantify pupil-to-pupil SARS-CoV-2 transmission and the impact of implemented control measures, we fit a stochastic individual-based model of secondary school infection to both swab testing data and secondary school absences data from England, and then simulate outbreaks from 31st August 2020 until 23rd May 2021. We find that the pupil-to-pupil reproduction number, R_school, has remained below 1 on average across the study period, and that twice weekly mass testing using LFTs has helped to control pupil-to-pupil transmission. We also explore the potential benefits of alternative containment strategies, finding that a strategy of repeat testing of close contacts rather than isolation, alongside mass testing, substantially reduces absences with only a marginal increase in pupil-to-pupil transmission.

Twice weekly mass testing using lateral flow tests has helped to control pupil-to-pupil transmission in English secondary schools. Here, the authors show that repeat testing of contacts alongside mass testing could greatly reduce absences with only a marginal increase in transmission, compared to isolating contacts.

Measures implemented in the school setting to contain the COVID-19 pandemic

BACKGROUND

In response to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the impact of coronavirus disease 2019 (COVID-19), governments have implemented a variety of measures to control the spread of the virus and the associated disease. Among these, have been measures to control the pandemic in primary and secondary school settings.

OBJECTIVES

To assess the effectiveness of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic, with particular focus on the different types of measures implemented in school settings and the outcomes used to measure their impacts on transmission-related outcomes, healthcare utilisation outcomes, other health outcomes as well as societal, economic, and ecological outcomes.  SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and the Educational Resources Information Center, as well as COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO COVID-19 Global literature on coronavirus disease (indexing preprints) on 9 December 2020. We conducted backward-citation searches with existing reviews.

SELECTION CRITERIA

We considered experimental (i.e. randomised controlled trials; RCTs), quasi-experimental, observational and modelling studies assessing the effects of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic. Outcome categories were (i) transmission-related outcomes (e.g. number or proportion of cases); (ii) healthcare utilisation outcomes (e.g. number or proportion of hospitalisations); (iii) other health outcomes (e.g. physical, social and mental health); and (iv) societal, economic and ecological outcomes (e.g. costs, human resources and education). We considered studies that included any population at risk of becoming infected with SARS-CoV-2 and/or developing COVID-19 disease including students, teachers, other school staff, or members of the wider community.  DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles, abstracts and full texts. One review author extracted data and critically appraised each study. One additional review author validated the extracted data. To critically appraise included studies, we used the ROBINS-I tool for quasi-experimental and observational studies, the QUADAS-2 tool for observational screening studies, and a bespoke tool for modelling studies. We synthesised findings narratively. Three review authors made an initial assessment of the certainty of evidence with GRADE, and several review authors discussed and agreed on the ratings.

MAIN RESULTS

We included 38 unique studies in the analysis, comprising 33 modelling studies, three observational studies, one quasi-experimental and one experimental study with modelling components. Measures fell into four broad categories: (i) measures reducing the opportunity for contacts; (ii) measures making contacts safer; (iii) surveillance and response measures; and (iv) multicomponent measures. As comparators, we encountered the operation of schools with no measures in place, less intense measures in place, single versus multicomponent measures in place, or closure of schools. Across all intervention categories and all study designs, very low- to low-certainty evidence ratings limit our confidence in the findings. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the model structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to deviations from intended interventions or missing data. Across all categories, few studies reported on implementation or described how measures were implemented. Where we describe effects as 'positive', the direction of the point estimate of the effect favours the intervention(s); 'negative' effects do not favour the intervention.  We found 23 modelling studies assessing measures reducing the opportunity for contacts (i.e. alternating attendance, reduced class size). Most of these studies assessed transmission and healthcare utilisation outcomes, and all of these studies showed a reduction in transmission (e.g. a reduction in the number or proportion of cases, reproduction number) and healthcare utilisation (i.e. fewer hospitalisations) and mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 11 modelling studies and two observational studies assessing measures making contacts safer (i.e. mask wearing, cleaning, handwashing, ventilation). Five studies assessed the impact of combined measures to make contacts safer. They assessed transmission-related, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed a reduction in transmission, and a reduction in hospitalisations; however, studies showed mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 13 modelling studies and one observational study assessing surveillance and response measures, including testing and isolation, and symptomatic screening and isolation. Twelve studies focused on mass testing and isolation measures, while two looked specifically at symptom-based screening and isolation. Outcomes included transmission, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed effects in favour of the intervention in terms of reductions in transmission and hospitalisations, however some showed mixed or negative effects on societal, economic and ecological outcomes (e.g. fewer number of days spent in school). We found three studies that reported outcomes relating to multicomponent measures, where it was not possible to disaggregate the effects of each individual intervention, including one modelling, one observational and one quasi-experimental study. These studies employed interventions, such as physical distancing, modification of school activities, testing, and exemption of high-risk students, using measures such as hand hygiene and mask wearing. Most of these studies showed a reduction in transmission, however some showed mixed or no effects.   As the majority of studies included in the review were modelling studies, there was a lack of empirical, real-world data, which meant that there were very little data on the actual implementation of interventions.

AUTHORS' CONCLUSIONS

Our review suggests that a broad range of measures implemented in the school setting can have positive impacts on the transmission of SARS-CoV-2, and on healthcare utilisation outcomes related to COVID-19. The certainty of the evidence for most intervention-outcome combinations is very low, and the true effects of these measures are likely to be substantially different from those reported here. Measures implemented in the school setting may limit the number or proportion of cases and deaths, and may delay the progression of the pandemic. However, they may also lead to negative unintended consequences, such as fewer days spent in school (beyond those intended by the intervention). Further, most studies assessed the effects of a combination of interventions, which could not be disentangled to estimate their specific effects. Studies assessing measures to reduce contacts and to make contacts safer consistently predicted positive effects on transmission and healthcare utilisation, but may reduce the number of days students spent at school. Studies assessing surveillance and response measures predicted reductions in hospitalisations and school days missed due to infection or quarantine, however, there was mixed evidence on resources needed for surveillance. Evidence on multicomponent measures was mixed, mostly due to comparators. The magnitude of effects depends on multiple factors. New studies published since the original search date might heavily influence the overall conclusions and interpretation of findings for this review.

Impact of Changes in Infection Control Measures on the Dynamics of COVID-19 Infections in Schools and Pre-schools

Introduction: With the increased emergence of SARS-CoV-2 variants, the impact on schools and preschools remains a matter of debate. To ensure that schools and preschools are kept open safely, the identification of factors influencing the extent of outbreaks is of importance. Aim: To monitor dynamics of COVID-19 infections in schools and preschools and identify factors influencing the extent of outbreaks. Methods: In this prospective observational study we analyzed routine surveillance data of Mecklenburg-Western Pomerania, Germany, from calendar week (CW) 32, 2020 to CW19, 2021 regarding SARS-CoV-2 infection events in schools and preschools considering changes in infection control measures over time. A multivariate linear regression model was fitted to evaluate factors influencing the number of students, teachers and staff tested positive following index cases in schools and preschools. Due to an existing multicollinearity in the common multivariate regression model between the variables "face mask obligation for children" and "face mask obligation for adults", two further separate regression models were set up (Multivariate Model Adults and Multivariate Model Children). Results: We observed a significant increase in secondary cases in preschools in the first quarter of 2021 (CW8 to CW15, 2021), and simultaneously a decrease in secondary cases in schools. In multivariate regression analysis, the strongest predictor of the extent of the outbreaks was the teacher/ caregiver mask obligation (B = -1.9; 95% CI: -2.9 to -1.0; p < 0.001). Furthermore, adult index cases (adult only or child+adult combinations) increased the likelihood of secondary cases (B = 1.3; 95% CI: 0.9 to 1.8; p < 0.001). The face mask obligation for children also showed a significant reduction in the number of secondary cases (B = -0.6; 95% CI: -0.9 to -0.2; p = 0.004. Conclusion: The present study indicates that outbreak events at schools and preschools are effectively contained by an obligation for adults and children to wear face masks.

Within and between classroom transmission patterns of seasonal influenza among primary school students in Matsumoto city, Japan

Schools play a central role in the transmission of many respiratory infections. Heterogeneous social contact patterns associated with the social structures of schools (i.e., classes/grades) are likely to influence the within-school transmission dynamics, but data-driven evidence on fine-scale transmission patterns between students has been limited. Using a mathematical model, we analyzed a large-scale dataset of seasonal influenza outbreaks in Matsumoto city, Japan, to infer social interactions within and between classes/grades from observed transmission patterns. While the relative contribution of within-class and within-grade transmissions to the reproduction number varied with the number of classes per grade, the overall within-school reproduction number, which determines the initial growth of cases and the risk of sustained transmission, was only minimally associated with class sizes and the number of classes per grade. This finding suggests that interventions that change the size and number of classes, e.g., splitting classes and staggered attendance, may have a limited effect on the control of school outbreaks. We also found that vaccination and mask-wearing of students were associated with reduced susceptibility (vaccination and mask-wearing) and infectiousness (mask-wearing), and hand washing was associated with increased susceptibility. Our results show how analysis of fine-grained transmission patterns between students can improve understanding of within-school disease dynamics and provide insights into the relative impact of different approaches to outbreak control.

Exploring the epidemiological changes of common respiratory viruses since the COVID-19 pandemic: a hospital study in Hangzhou, China

Adenovirus, respiratory syncytial virus, and influenza virus are common causes of respiratory infections. The COVID-19 pandemic had a significant impact on their prevalence. The aim of this study was to analyze the epidemic changes of common respiratory viruses in the Affiliated Hospital of Hangzhou Normal University in Hangzhou, China, from October of 2017 to February of 2021. We collected statistics from 121,529 patients in the outpatient and inpatient departments of the hospital who had throat or nose swabs collected for testing for four virus antigens by the colloidal gold method. Of these, 13,200 (10.86%) were positive for influenza A virus, 8,402 (6.91%) were positive for influenza B virus, 6,056 (4.98%) were positive for adenovirus, and 4,739 (3.90%) were positive for respiratory syncytial virus. The positivity rates of the influenza A virus (0-14 years old, P = 0.376; over 14 years old, P = 0.197) and respiratory syncytial virus (0-14 years old, P = 0.763; over 14 years old, P = 0.465) did not differ significantly by gender. After January of 2020, influenza virus infection decreased significantly. The positivity rate of respiratory syncytial virus remained high, and its epidemic season was similar to before. Strict respiratory protection and regulation of crowd activities have a great impact on the epidemic characteristics of viruses. After major changes in the public health environment, virus epidemics and their mutations should be monitored closely, extensively, and continuously.

A review of mathematical model-based scenario analysis and interventions for COVID-19

Mathematical model-based analysis has proven its potential as a critical tool in the battle against COVID-19 by enabling better understanding of the disease transmission dynamics, deeper analysis of the cost-effectiveness of various scenarios, and more accurate forecast of the trends with and without interventions. However, due to the outpouring of information and disparity between reported mathematical models, there exists a need for a more concise and unified discussion pertaining to the mathematical modeling of COVID-19 to overcome related skepticism. Towards this goal, this paper presents a review of mathematical model-based scenario analysis and interventions for COVID-19 with the main objectives of (1) including a brief overview of the existing reviews on mathematical models, (2) providing an integrated framework to unify models, (3) investigating various mitigation strategies and model parameters that reflect the effect of interventions, (4) discussing different mathematical models used to conduct scenario-based analysis, and (5) surveying active control methods used to combat COVID-19.

COVID-19 in schools: Mitigating classroom clusters in the context of variable transmission

Widespread school closures occurred during the COVID-19 pandemic. Because closures are costly and damaging, many jurisdictions have since reopened schools with control measures in place. Early evidence indicated that schools were low risk and children were unlikely to be very infectious, but it is becoming clear that children and youth can acquire and transmit COVID-19 in school settings and that transmission clusters and outbreaks can be large. We describe the contrasting literature on school transmission, and argue that the apparent discrepancy can be reconciled by heterogeneity, or “overdispersion” in transmission, with many exposures yielding little to no risk of onward transmission, but some unfortunate exposures causing sizeable onward transmission. In addition, respiratory viral loads are as high in children and youth as in adults, pre- and asymptomatic transmission occur, and the possibility of aerosol transmission has been established. We use a stochastic individual-based model to find the implications of these combined observations for cluster sizes and control measures. We consider both individual and environment/activity contributions to the transmission rate, as both are known to contribute to variability in transmission. We find that even small heterogeneities in these contributions result in highly variable transmission cluster sizes in the classroom setting, with clusters ranging from 1 to 20 individuals in a class of 25. None of the mitigation protocols we modeled, initiated by a positive test in a symptomatic individual, are able to prevent large transmission clusters unless the transmission rate is low (in which case large clusters do not occur in any case). Among the measures we modeled, only rapid universal monitoring (for example by regular, onsite, pooled testing) accomplished this prevention. We suggest approaches and the rationale for mitigating these larger clusters, even if they are expected to be rare.

During the COVID-19 pandemic many jurisdictions closed schools in order to limit transmission of SARS-CoV-2. Because school closures are costly and damaging to students, schools were later reopened despite the risk of contact among students contributing to increased prevalence of the virus. Early data showed schools being mostly a low risk setting, but occasionally large outbreaks were observed. We argue that this heterogenous behaviour can be explained by variability in the rate of transmission, both at the level of the individual student and at the level of the classroom. We created a mathematical model of transmission in the classroom to explore the consequences of this variability for cluster size and control measures, considering what happens when a single infectious individual attends a classroom of susceptible students. We used the model to study different interventions with the aim of reducing the size of infection clusters, in situations where such clusters would be large. We found that interventions based on acting after symptomatic students receive a positive test, as is standard practice in many jurisdictions, are ineffective at preventing most infections, and instead found that only frequent screening of the entire class was able to reduce the size of clusters substantially.