A global assessment of the impact of school closure in reducing COVID-19 spread

The ethicality of the COVID-19 response in children and adolescents

Childhood and adolescence are critical periods of physiological growth as well as development in biological, emotional, and social domains. During the COVID-19 pandemic, children and adolescent's lives were drastically changed. Many countries including the United Kingdom and Ireland imposed strict universal lockdowns, which included the closing of creches, schools and universities as well as restricting peer interactions, social activities, and recreational pursuits. Evidence is emerging of a catastrophic impact on the younger generation, which leads the authors to explore the ethicality of the COVID-19 response in this population in relation to the four pillars of medical ethics: beneficence, nomaleficence, autonomy, and justice.

Impact of "Long Covid" on Children: Global and Hong Kong Perspectives

BACKGROUND

The coronavirus disease (COVID-19) pandemic spares no nation or city, and the virus is responsible for the escalating incidence and mortality worldwide.

OBJECTIVE

This article reviews the impact of "Long Covid" on Children.

METHODS

A PubMed search was conducted in December 2021 in Clinical Queries using the key terms "COVID-19" OR "long COVID". The search was restricted to children and adolescent aged < 18 years and English literature.

RESULTS

Many large-scale studies have provided strong scientific evidence as to the detrimental and irreversible sequelae of COVID-19 on the health, psychology, and development of affected children. Many insights into managing this disease can be obtained from comparing the management of influenza. COVID-19 is generally a mild respiratory disease in children. Several syndromes, such as multisystem inflammatory syndrome in children (MIS-C) and COVID toe, are probably not specific to SARS-CoV-2. "Long COVID", or the long-term effects of SARS-CoV-2 infection, or the prolonged isolation and containment strategies on education and psychosocial influences on children associated with the pandemic, are significant.

CONCLUSION

Healthcare providers must be aware of the potential effects of quarantine on children's mental health. More importantly, healthcare providers must appreciate the importance of the decisions and actions made by governments, non-governmental organizations, the community, schools, and parents in reducing the possible effects of this situation. Multifaceted age-specific and developmentally appropriate strategies must be adopted by healthcare authorities to lessen the negative impact of quarantine on the psychological well-being of children.

A two-strain model of infectious disease spread with asymmetric temporary immunity periods and partial cross-immunity

We introduce a two-strain model with asymmetric temporary immunity periods and partial cross-immunity. We derive explicit conditions for competitive exclusion and coexistence of the strains depending on the strain-specific basic reproduction numbers, temporary immunity periods, and degree of cross-immunity. The results of our bifurcation analysis suggest that, even when two strains share similar basic reproduction numbers and other epidemiological parameters, a disparity in temporary immunity periods and partial or complete cross-immunity can provide a significant competitive advantage. To analyze the dynamics, we introduce a quasi-steady state reduced model which assumes the original strain remains at its endemic steady state. We completely analyze the resulting reduced planar hybrid switching system using linear stability analysis, planar phase-plane analysis, and the Bendixson-Dulac criterion. We validate both the full and reduced models with COVID-19 incidence data, focusing on the Delta (B.1.617.2), Omicron (B.1.1.529), and Kraken (XBB.1.5) variants. These numerical studies suggest that, while early novel strains of COVID-19 had a tendency toward dramatic takeovers and extinction of ancestral strains, more recent strains have the capacity for co-existence.

Extensive SARS-CoV-2 testing reveals BA.1/BA.2 asymptomatic rates and underreporting in school children

Background

Case underreporting during the coronavirus disease 2019 (COVID-19) pandemic has been a major challenge to the planning and evaluation of public health responses. School children were often considered a less vulnerable population and underreporting rates may have been particularly high. In January 2022, the Canadian province of Newfoundland and Labrador (NL) was experiencing an Omicron variant outbreak (BA.1/BA.2 subvariants) and public health officials recommended that all returning students complete two rapid antigen tests (RATs) to be performed three days apart.

Methods

To estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we asked parents and guardians to report the results of the RATs completed by K-12 students (approximately 59,000 students) using an online survey.

Results

When comparing the survey responses with the number of cases and tests reported by the NL testing system, we found that one out of every 4.3 (95% CI, 3.1-5.3) positive households were captured by provincial case count, with 5.1% positivity estimated from the RAT results and 1.2% positivity reported by the provincial testing system. Of positive test results, 62.9% (95% CI, 44.3-83.0) were reported for elementary school students, and the remaining 37.1% (95% CI, 22.7-52.9) were reported for junior high and high school students. Asymptomatic infections were 59.8% of the positive cases. Given the low survey participation rate (3.5%), our results may suffer from sample selection biases and should be interpreted with caution.

Conclusion

The underreporting ratio is consistent with ratios calculated from serology data and provides insights into infection prevalence and asymptomatic infections in school children; a currently understudied population.

Efficacy and effectiveness of case isolation and quarantine during a growing phase of the COVID-19 epidemic in Finland

Based on data collected as part of the contact tracing activity of the City of Helsinki Epidemiological Operations Unit, we evaluated the efficacy and effectiveness of isolating SARS-CoV-2 cases and quarantining their exposed contacts during a mildly growing phase of the COVID-19 epidemic in Finland in autumn 2020. Based on the observed symptom-to-symptom intervals in 1016 pairs of primary and secondary cases, we estimated that without case isolation or quarantine 40[Formula: see text] (90[Formula: see text] credible interval, CI 25-59) of transmission would have occurred on the day of or after symptom onset. One third of SARS-CoV-2 cases (N = 1521) had initially been quarantined, with a self-reported time until isolation (quarantine) of 0.8 days before symptom onset. This delay translates into an efficacy of 50[Formula: see text] (90[Formula: see text] CI 40-63) of averting secondary infections per quarantined case. Due to later isolation (mean 2.6 days after symptoms), the efficacy was smaller (24[Formula: see text]; 90[Formula: see text] CI 12-41) in those two third of the cases (N = 3101) whose isolation was prompted by their symptoms, i.e. without being previously quarantined. At the population level, we evaluated the effectiveness of case isolation and quarantine on the growth rate of the COVID-19 epidemic in the autumn of 2020. Under a wide range of underlying assumptions, the rate would have been at least 2 times higher without case isolation and quarantine. The numbers needed to isolate or quarantine to prevent one secondary case were 2 and 20, respectively.

Modeling COVID-19 Transmission Dynamics: A Bibliometric Review

A good amount of research has evolved just in three years in COVID-19 transmission, mortality, vaccination, and some socioeconomic studies. A few bibliometric reviews have already been performed in the literature, especially on the broad theme of COVID-19, without any particular area such as transmission, mortality, or vaccination. This paper fills this gap by conducting a bibliometric review on COVID-19 transmission as the first of its kind. The main aim of this study is to conduct a bibliometric review of the literature in the area of COVID-19 transmission dynamics. We have conducted bibliometric analysis using descriptive and network analysis methods to review the literature in this area using RStudio, Openrefine, VOSviewer, and Tableau. We reviewed 1103 articles published in 2020-2022. The result identified the top authors, top disciplines, research patterns, and hotspots and gave us clear directions for classifying research topics in this area. New research areas are rapidly emerging in this area, which needs constant observation by researchers to combat this global epidemic.

Impact of school closures due to COVID-19 on education in low- and middle-income countries

Coronavirus disease 2019 (COVID-19) has dismantled many long-established systems in society. Distance learning has rapidly replaced traditional classes at school. Keeping all other activities open, educational institutions were closed first to contain COVID-19 transmission when the number of cases started to rise, causing a massive adverse impact on education and students’ well-being. Students of lower socio-economic classes are dealing with the worst consequences as they are not able to afford the means of online schooling, especially in low- and middle-income countries like Bangladesh.

Evaluating scenarios for school reopening under COVID19

BACKGROUND

Thousands of school systems have struggled with the decisions about how to deliver education safely and effectively amid the COVID19 pandemic. This study evaluates the public health impact of various school reopening scenarios (when, and how to return to in-person instruction) on the spread of COVID19.

METHODS

An agent-based simulation model was adapted and used to project the impact of various school reopening strategies on the number of infections, hospitalizations, and deaths in the state of Georgia during the study period, i.e., February 18^th-November 24^th, 2020. The tested strategies include (i) schools closed, i.e., all students receive online instruction, (ii) alternating school day, i.e., half of the students receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iii) alternating school day for children, i.e., half of the children (ages 0-9) receive in-person instruction on Mondays and Wednesdays and the other half on Tuesdays and Thursdays, (iv) children only, i.e., only children receive in-person instruction, (v) regular, i.e., all students return to in-person instruction. We also tested the impact of universal masking in schools.

RESULTS

Across all scenarios, the number of COVID19-related deaths ranged from approximately 8.8 to 9.9 thousand, the number of cumulative infections ranged from 1.76 to 1.96 million for adults and 625 to 771 thousand for children and youth, and the number of COVID19-related hospitalizations ranged from approximately 71 to 80 thousand during the study period. Compared to schools reopening August 10 with a regular reopening strategy, the percentage of the population infected reduced by 13%, 11%, 9%, and 6% in the schools closed, alternating school day for children, children only, and alternating school day reopening strategies, respectively. Universal masking in schools for all students further reduced outcome measures.

CONCLUSIONS

Reopening schools following a regular reopening strategy would lead to higher deaths, hospitalizations, and infections. Hybrid in-person and online reopening strategies, especially if offered as an option to families and teachers who prefer to opt-in, provide a good balance in reducing the infection spread compared to the regular reopening strategy, while ensuring access to in-person education.

Data science approaches to infectious disease surveillance

Novel data science approaches are needed to confront large-scale infectious disease epidemics such as COVID-19, human immunodeficiency viruses, African swine flu and Ebola. Human beings are now equipped with richer data and more advanced data analytics methodologies, many of which have become available only in the last decade. The theme issue Data Science Approaches to Infectious Diseases Surveillance reports the latest interdisciplinary research on developing novel data science methodologies to capitalize on the rich 'big data' of human behaviours to confront infectious diseases, with a particular focus on combating the ongoing COVID-19 pandemic. Compared to conventional public health research, articles in this issue present innovative data science approaches that were not possible without the growing human behaviour data and the recent advances in information and communications technology. This issue has 12 research papers and one review paper from a strong lineup of contributors from multiple disciplines, including data science, computer science, computational social sciences, applied maths, statistics, physics and public health. This introductory article provides a brief overview of the issue and discusses the future of this emerging field. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

A global assessment of the impact of school closure in reducing COVID-19 spread

Prolonged school closure has been adopted worldwide to control COVID-19. Indeed, UN Educational, Scientific and Cultural Organization figures show that two-thirds of an academic year was lost on average worldwide due to COVID-19 school closures. Such pre-emptive implementation was predicated on the premise that school children are a core group for COVID-19 transmission. Using surveillance data from the Chinese cities of Shenzhen and Anqing together, we inferred that compared with the elderly aged 60 and over, children aged 18 and under and adults aged 19-59 were 75% and 32% less susceptible to infection, respectively. Using transmission models parametrized with synthetic contact matrices for 177 jurisdictions around the world, we showed that the lower susceptibility of school children substantially limited the effectiveness of school closure in reducing COVID-19 transmissibility. Our results, together with recent findings that clinical severity of COVID-19 in children is lower, suggest that school closure may not be ideal as a sustained, primary intervention for controlling COVID-19. This article is part of the theme issue 'Data science approach to infectious disease surveillance'.