Implications of the school-household network structure on SARS-CoV-2 transmission under school reopening strategies in England

Non-pharmaceutical interventions to reduce COVID-19 transmission in the UK: a rapid mapping review and interactive evidence gap map

BACKGROUND

Non-pharmaceutical interventions (NPIs) were crucial in the response to the COVID-19 pandemic, although uncertainties about their effectiveness remain. This work aimed to better understand the evidence generated during the pandemic on the effectiveness of NPIs implemented in the UK.

METHODS

We conducted a rapid mapping review (search date: 1 March 2023) to identify primary studies reporting on the effectiveness of NPIs to reduce COVID-19 transmission. Included studies were displayed in an interactive evidence gap map.

RESULTS

After removal of duplicates, 11 752 records were screened. Of these, 151 were included, including 100 modelling studies but only 2 randomized controlled trials and 10 longitudinal observational studies.Most studies reported on NPIs to identify and isolate those who are or may become infectious, and on NPIs to reduce the number of contacts. There was an evidence gap for hand and respiratory hygiene, ventilation and cleaning.

CONCLUSIONS

Our findings show that despite the large number of studies published, there is still a lack of robust evaluations of the NPIs implemented in the UK. There is a need to build evaluation into the design and implementation of public health interventions and policies from the start of any future pandemic or other public health emergency.

A dashboard for the evaluation of the effect of school closures on wellbeing of children and parents

BACKGROUND

We present a dashboard for the evaluation of the impact of school closures on children and parents during the first wave of the COVID pandemic in 2020 on the various components of wellbeing.

METHODS

Starting from an explorative literature search by a team of experts from diverse fields (e.g., epidemiology, virology, psychology, education, sociology), we developed a dashboard that allows for the quick evaluation of the general effect of school closures on various indicators of well-being in different groups and for the quality of the available research, at a time where a crisis is ongoing.

RESULTS

It is concluded that there is evidence that the school closures reduced the transmission of COVID in the first wave in springtime 2020. Nevertheless, a multitude of studies show that the school closures also had a negative impact on different components of wellbeing such as academic achievement, time spent on learning and mental health. Furthermore, the school closures affected not only the children and adolescents, but also the parents that were forced to provide more childcare and help with schoolwork. Longitudinal studies on large representative samples with repeated assessments of wellbeing are necessary to understand the long-term effects of the school closures.

CONCLUSIONS

The dashboard provides a first visual overview of the effects of school closures on wellbeing, and can serve as the basis for a future more systematic review and meta-analysis of the effects of school closures on wellbeing. It can be considered as a paradigm for rapid obtention of scientific evidence, during a quickly unfolding crisis, also in view of underpinning policy advice.

Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies

There are many contrasting results concerning the effectiveness of Test-Trace-Isolate (TTI) strategies in mitigating SARS-CoV-2 spread. To shed light on this debate, we developed a novel static-temporal multiplex network characterizing both the regular (static) and random (temporal) contact patterns of individuals and a SARS-CoV-2 transmission model calibrated with historical COVID-19 epidemiological data. We estimated that the TTI strategy alone could not control the disease spread: assuming R0 = 2.5, the infection attack rate would be reduced by 24.5%. Increased test capacity and improved contact trace efficiency only slightly improved the effectiveness of the TTI. We thus investigated the effectiveness of the TTI strategy when coupled with reactive social distancing policies. Limiting contacts on the temporal contact layer would be insufficient to control an epidemic and contacts on both layers would need to be limited simultaneously. For example, the infection attack rate would be reduced by 68.1% when the reactive distancing policy disconnects 30% and 50% of contacts on static and temporal layers, respectively. Our findings highlight that, to reduce the overall transmission, it is important to limit contacts regardless of their types in addition to identifying infected individuals through contact tracing, given the substantial proportion of asymptomatic and pre-symptomatic SARS-CoV-2 transmission.

Big data technology in infectious diseases modeling, simulation, and prediction after the COVID-19 outbreak

After the outbreak of COVID-19, the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods. Starting from the research purpose and data, researchers improved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems. In terms of modeling methods, the researchers use compartment subdivision, dynamic parameters, agent-based model methods, and artificial intelligence related methods. In terms of factors studied, the researchers studied 6 categories: human mobility, nonpharmaceutical interventions (NPIs), ages, medical resources, human response, and vaccine. The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies. This review started with a research structure of research purpose, factor, data, model, and conclusion. Focusing on the post-COVID-19 infectious disease prediction simulation research, this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.

Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation

To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have had less of a societal impact, but comparable epidemiological impact. Here, using the first COVID-19 wave in the Netherlands as a case in point, we address this issue by developing a high-resolution analysis framework that uses a demographically stratified population and a spatially explicit, dynamic, individual contact-pattern based epidemiology, calibrated to hospital admissions data and mobility trends extracted from mobile phone signals and Google. We demonstrate how a subnational approach could achieve similar level of epidemiological control in terms of hospital admissions, while some parts of the country could stay open for a longer period. Our framework is exportable to other countries and settings, and may be used to develop policies on subnational approach as a better strategic choice for controlling future epidemics.

Empirical evidence of transmission over a school-household network for SARS-CoV-2; exploration of transmission pairs stratified by primary and secondary school

BACKGROUND

Children play a key role in the transmission of many infectious diseases. They have many of their close social encounters at home or at school. We hypothesized that most of the transmission of respiratory infections among children occur in these two settings and that transmission patterns can be predicted by a bipartite network of schools and households.

AIM AND METHODS

To confirm transmission over a school-household network, SARS-CoV-2 transmission pairs in children aged 4-17 years were analyzed by study year and primary/secondary school. Cases with symptom onset between 1 March 2021 and 4 April 2021 identified by source and contact-tracing in the Netherlands were included. In this period, primary schools were open and secondary school students attended class at least once per week. Within pairs, spatial distance between the postcodes was calculated as the Euclidean distance.

RESULTS

A total of 4059 transmission pairs were identified; 51.9% between primary schoolers; 19.6% between primary and secondary schoolers; 28.5% between secondary schoolers. Most (68.5%) of the transmission for children in the same study year occurred at school. In contrast, most of the transmission of children from different study years (64.3%) and most primary-secondary transmission (81.7%) occurred at home. The average spatial distance between infections was 1.2 km (median 0.4) for primary school pairs, 1.6 km (median 0) for primary-secondary school pairs and 4.1 km (median 1.2) for secondary school pairs.

CONCLUSION

The results provide evidence of transmission on a bipartite school-household network. Schools play an important role in transmission within study years, and households play an important role in transmission between study years and between primary and secondary schools. Spatial distance between infections in a transmission pair reflects the smaller school catchment area of primary schools versus secondary schools. Many of these observed patterns likely hold for other respiratory pathogens.

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.

During the COVID-19 pandemic, a range of measures have been implemented to reduce transmission in schools. If an infected pupil is detected, one approach involves ‘isolating’ their contacts, who must then remain at home and not attend school. However, this may lead to high levels of pupil absences, which in turn may impact educational attainment. An alternative approach involves testing the contacts of infected individuals each day, who are allowed to attend school if they test negative. This can be achieved using lateral flow device tests, which can be taken at home and return a result in under thirty minutes. In this paper, using an individual-based model, we compare the impact of strategies that use lateral flow device tests to rapidly test secondary school pupils to strategies that require the contacts of infected individuals to isolate. We find that a strategy that combines testing pupils regularly with testing the contacts of identified infected individuals for a period of seven days has the potential to keep both transmission and absences low. However, such a strategy requires a high number of tests. Our results demonstrate the conflict between the competing aims of minimising transmission, minimising absences, and minimising test burden.

An assessment of the vaccination of school-aged children in England against SARS-CoV-2

BACKGROUND

Children and young persons are known to have a high number of close interactions, often within the school environment, which can facilitate rapid spread of infection; yet for SARS-CoV-2, it is the elderly and vulnerable that suffer the greatest health burden. Vaccination, initially targeting the elderly and vulnerable before later expanding to the entire adult population, has been transformative in the control of SARS-CoV-2 in England. However, early concerns over adverse events and the lower risk associated with infection in younger individuals means that the expansion of the vaccine programme to those under 18 years of age needs to be rigorously and quantitatively assessed.

METHODS

Here, using a bespoke mathematical model matched to case and hospital data for England, we consider the potential impact of vaccinating 12-17 and 5-11-year-olds. This analysis is reported from an early model (generated in June 2021) that formed part of the evidence base for the decisions in England, and a later model (from November 2021) that benefits from a richer understanding of vaccine efficacy, greater knowledge of the Delta variant wave and uses data on the rate of vaccine administration. For both models, we consider the population wide impact of childhood vaccination as well as the specific impact on the age groups targeted for vaccination.

RESULTS

Projections from June suggested that an expansion of the vaccine programme to those 12-17 years old could generate substantial reductions in infection, hospital admission and deaths in the entire population, depending on population behaviour following the relaxation of control measures. The benefits within the 12-17-year-old cohort were less marked, saving between 660 and 1100 (95% PI (prediction interval) 280-2300) hospital admissions and between 22 and 38 (95% PI 9-91) deaths depending on assumed population behaviour. For the more recent model, the benefits within this age group are reduced, saving on average 630 (95% PI 300-1300) hospital admissions and 11 (95% PI 5-28) deaths for 80% vaccine uptake, while the benefits to the wider population represent a reduction of 8-10% in hospital admissions and deaths. The vaccination of 5-11-year-olds is projected to have a far smaller impact, in part due to the later roll-out of vaccines to this age group.

CONCLUSIONS

Vaccination of 12-170-year-olds and 5-11-year-olds is projected to generate a reduction in infection, hospital admission and deaths for both the age groups involved and the population in general. For any decision involving childhood vaccination, these benefits needs to be balanced against potential adverse events from the vaccine, the operational constraints on delivery and the potential for diverting resources from other public health campaigns.

Schools opening and Covid-19 diffusion: Evidence from geolocalized microdata

Are schools triggering the diffusion of the Covid-19? This question is at the core of an extensive debate about the social and long-run costs of stopping the economic activity and human capital accumulation from reducing the contagion. In principle, many confounding factors, such as climate, health system treatment, and other forms of restrictions, may impede disentangling the link between schooling and Covid-19 cases when focusing on a country or regional-level data. This work sheds light on the potential impact of school opening on the upsurge of contagion by combining a weekly panel of geocoded Covid-19 cases in Sicilian census areas with a unique set of school data. The identification of the effect takes advantage of both a spatial and time-variation in school opening, stemming from the flexibility in opening dates determined by a Regional Decree, and by the occurrence of a national referendum, which pulled a set of poll-station schools towards opening earlier or later September 24th. The analysis finds that census areas where schools opened earlier observed a significant and positive increase in the growth rate of Covid-19 cases between 2.5-3.7%. This result is consistent across several specifications, including accounting for several determinants of school opening, such as the number of temporary teachers, Covid-19 cases in August, and pupils with special needs. Finally, the analysis finds lower effects in more densely populated areas, on younger population, and on smaller class size. The results imply that school reopening generated an increase of one third in cases.

Investigating the transmission risk of infectious disease outbreaks through the Aotearoa Co-incidence Network (ACN): a population-based study

BACKGROUND

The emergence and re-emergence of infectious diseases presents a significant challenge to public health and broader society. This study utilises novel nationwide data to calculate the transmission risk and potential inequity of infectious disease outbreaks through use of network analysis.

METHODS

Nationwide employment and education microdata (∼4.7 million individuals in Aotearoa New Zealand) were used to develop the Aotearoa Co-incidence Network (ACN). The ACN considers connections generated when individuals are employed at the same workplaces or enrolled at the same schools. Through forms of network analysis, connections between geospatial areas can be established and provide proxy measures of infectious disease transmission risk. The ACN was also overlayed with nationwide population vulnerability data based on the number of older adults (>65 years) and individuals with long-term health conditions.

FINDINGS

We identify areas that have both high potential transmission risk (i.e., highly connected) and high vulnerability to infectious diseases. Community detection identified geographic boundaries that can be relevant to the application of regional restrictions for limiting infectious disease transmission.

INTERPRETATION

Integrating novel network science and geospatial analytics provides a simple way to study infectious disease transmission risk and population vulnerability to outbreaks. Our replicable method has utility for researchers globally with access to such data. It can help inform equitable preparation for, and responses to infectious disease outbreaks.

FUNDING

This project was funded by the Health Research Council of New Zealand (20/1442) and from the NZ Government via Ministry for Business Innovation and Employment and Department of Prime Minister and Cabinet.

Comparison of Indoor Environment and Energy Consumption before and after Spread of COVID-19 in Schools in Japanese Cold-Climate Region

A report released by the WHO indicates that aerosols from infected people are one of the major sources of the spread of COVID-19. Therefore, as the COVID-19 infection caused by the SARS-CoV-2 virus spreads, it has become necessary to reconsider the design and operation of buildings. Inside school buildings in cold regions, not only is it not easy to increase ventilation during the winter, but it may also be difficult for students to attend classes while wearing masks during the summer because such buildings are not equipped with air-conditioning systems. In short, school buildings in cold climates have more problems than those in warm climates. We report on the results of indoor environmental measurement using our developed CO2-concentration meters, a questionnaire survey on students’ feeling of being hot or cold (i.e., ‘thermal sensation’), and a comparison of energy consumption before and after the spread of COVID-19 infection in schools in Sapporo, Japan, a cold-climate area. The results indicate that (1) more than 70% of the students participated in window ventilation by the CO2 meter, and (2) a relatively good indoor environment was maintained through the efforts of teachers and students. However, we also found that (1) 90% of the students felt hot in summer and (2) 40% felt cold in winter, (3) energy efficiency worsened by 7% due to increased ventilation, and (4) air quality was not as clean as desired during the coldest months of the year. Therefore, investment in insulation and air conditioning systems for school buildings is needed.

Do the Benefits of School Closure Outweigh Its Costs?

School closure has been a common response to COVID-19. Yet, its implementation has hardly ever been based on rigorous analysis of its costs and benefits. We aim to first illustrate the unintended consequences and side effects of school closure, and then discuss the policy and research implications. This commentary frames evidence from the most recent papers on the topic from a public-health epidemiology and disaster risk reduction perspective. In particular, we argue that the benefits of school closure in terms of reduced infection rates should be better compared with its costs in terms of both short- and long-term damage on the physical, mental, and social well-being of children and society at large.

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.

Model-based evaluation of alternative reactive class closure strategies against COVID-19

There are contrasting results concerning the effect of reactive school closure on SARS-CoV-2 transmission. To shed light on this controversy, we developed a data-driven computational model of SARS-CoV-2 transmission. We found that by reactively closing classes based on syndromic surveillance, SARS-CoV-2 infections are reduced by no more than 17.3% (95%CI: 8.0-26.8%), due to the low probability of timely identification of infections in the young population. We thus investigated an alternative triggering mechanism based on repeated screening of students using antigen tests. Depending on the contribution of schools to transmission, this strategy can greatly reduce COVID-19 burden even when school contribution to transmission and immunity in the population is low. Moving forward, the adoption of antigen-based screenings in schools could be instrumental to limit COVID-19 burden while vaccines continue to be rolled out.

Association of Elementary School Reopening Status and County COVID-19 Incidence

OBJECTIVE

To examine the association between elementary school opening status (ESOS) and changes in pediatric COVID-19 incidence.

METHODS

We conducted a cross-sectional study of US counties with school districts with ≥500 elementary school students. The main exposure was ESOS in September, 2020. The outcome was county incidence of COVID-19. Age-stratified negative binomial regression models were constructed using county adult COVID-19 incidence.

RESULTS

Among 3220 US counties, 618 (19.2%) were remote, 391 (12.1%) were hybrid, 2022 (62.8%) were in-person. In unadjusted models, COVID-19 incidence after school started was higher among children in hybrid or in-person counties compared with remote counties. After adjustment for local adult incidence, among children aged 0 to 9, the incidence rate ratio of COVID-19 (IRR) compared with remote counties was 1.01 (95% confidence interval [CI] 0.93-1.08) in hybrid counties and 0.79 (95% CI 0.75-0.84) in in-person counties.

CONCLUSIONS

Counties with in-person learning did not have higher rates of COVID-19 after adjustment for local adult rates.

COVID-19 Propagation Model Based on Economic Development and Interventions

In order to understand the influencing factors affecting the COVID-19 propagation, and analyze the development trend of the epidemic situation in the world, COVID-19 propagation model to simulate the COVID-19 propagation in the population is proposed in this paper. First of all, this paper analyzes the economic factors and interventions affecting the COVID-19 propagation in various different countries. Then, the touch number for COVID-19 High-risk Population Dynamic Network in this paper was redefined, and it predicts and analyzes the development trend of the epidemic situation in different countries. The simulation data and the published confirmed data by the world health organization could fit well, which also verified the reliability of the model. Finally, this paper also analyzes the impact of public awareness of prevention on the control of the epidemic. The analysis shows that increasing the awareness of prevention, timely and early adoption of protective measures such as wearing masks, and reducing travel can greatly reduce the risk of infection and the outbreak scale.

Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

BACKGROUND

Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear.

METHODS

We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number.

RESULTS

Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone.

CONCLUSION

Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics

In the recent COVID-19 pandemic, mathematical modeling constitutes an important tool to evaluate the prospective effectiveness of non-pharmaceutical interventions (NPIs) and to guide policy-making. Most research is, however, centered around characterizing the epidemic based on point estimates like the average infectiousness or the average number of contacts. In this work, we use stochastic simulations to investigate the consequences of a population's heterogeneity regarding connectivity and individual viral load levels. Therefore, we translate a COVID-19 ODE model to a stochastic multi-agent system. We use contact networks to model complex interaction structures and a probabilistic infection rate to model individual viral load variation. We observe a large dependency of the dispersion and dynamical evolution on the population's heterogeneity that is not adequately captured by point estimates, for instance, used in ODE models. In particular, models that assume the same clinical and transmission parameters may lead to different conclusions, depending on different types of heterogeneity in the population. For instance, the existence of hubs in the contact network leads to an initial increase of dispersion and the effective reproduction number, but to a lower herd immunity threshold (HIT) compared to homogeneous populations or a population where the heterogeneity stems solely from individual infectivity variations.