Estimation of the Excess COVID-19 Cases in Seoul, South Korea by the Students Arriving from China

Using the Health Belief Model to Assess the Physical Exercise Behaviors of International Students in South Korea during the Pandemic

International students have the special status of being isolated in a foreign country during a pandemic. As Korea is a worldwide leader in education, it is important to understand the physical exercise behaviors of international students during this pandemic to assess the need for additional policies and support. The health belief model was used to score the physical exercise motivation and behaviors of international students in South Korea during the COVID-19 pandemic. In total, 315 valid questionnaires were obtained and analyzed for this study. The reliability and validity of the data were also assessed. For all variables, the values for combined reliability and the Cronbach's α were higher than 0.70. The following conclusions were drawn by comparing the differences between the measures. The results of the Kaiser-Meyer-Olkin and Bartlett tests were also higher than 0.70, confirming high reliability and validity. This study found a correlation between the health beliefs of international students and age, education, and accommodation. Consequently, international students with lower health belief scores should be encouraged to pay more attention to their personal health, participate in more physical exercise, strengthen their motivation to participate in physical exercise, and increase the frequency of their participation.

Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature

South Korea implemented interventions to curb the spread of the novel coronavirus disease 2019 (COVID-19) pandemic with discovery of the first case in early 2020. Mathematical modeling designed to reflect the dynamics of disease transmission has been shown to be an important tool for responding to COVID-19. This study aimed to review publications on the structure, method, and role of mathematical models focusing on COVID-19 transmission dynamics in Korea. In total, 42 papers published between August 7, 2020 and August 21, 2022 were studied and reviewed. This study highlights the construction and utilization of mathematical models to help craft strategies for predicting the course of an epidemic and evaluating the effectiveness of control strategies. Despite the limitations caused by a lack of available epidemiological and surveillance data, modeling studies could contribute to providing scientific evidence for policymaking by simulating various scenarios.

Incubation period of wild type of SARS-CoV-2 infections by age, gender, and epidemic periods

Background

The incubation period of the coronavirus disease 2019 (COVID-19) is estimated to vary by demographic factors and the COVID-19 epidemic periods.

Objective

This study examined the incubation period of the wild type of SARS-CoV-2 infections by the different age groups, gender, and epidemic periods in South Korea.

Methods

We collected COVID-19 patient data from the Korean public health authorities and estimated the incubation period by fitting three different distributions, including log-normal, gamma, and Weibull distributions, after stratification by gender and age groups. To identify any temporal impact on the incubation period, we divided the study period into two different epidemic periods (Period-1: 19 January−19 April 2020 and Period-2: 20 April−16 October 2020), and assessed for any differences.

Results

We identified the log-normal as the best-fit model. The estimated median incubation period was 4.6 (95% CI: 3.9–4.9) days, and the 95th percentile was 11.7 (95% CI: 10.2–12.2) days. We found that the incubation period did not differ significantly between males and females (p = 0.42), age groups (p = 0.60), and the two different epidemic periods (p = 0.77).

Conclusions

The incubation period of wild type of SARS-CoV-2 infection during the COVID-19 pandemic 2020, in South Korea, does not likely differ by age group, gender and epidemic period.

Compartmental structures used in modeling COVID-19: a scoping review

Background

The coronavirus disease 2019 (COVID-19) epidemic, considered as the worst global public health event in nearly a century, has severely affected more than 200 countries and regions around the world. To effectively prevent and control the epidemic, researchers have widely employed dynamic models to predict and simulate the epidemic’s development, understand the spread rule, evaluate the effects of intervention measures, inform vaccination strategies, and assist in the formulation of prevention and control measures. In this review, we aimed to sort out the compartmental structures used in COVID-19 dynamic models and provide reference for the dynamic modeling for COVID-19 and other infectious diseases in the future.

Main text

A scoping review on the compartmental structures used in modeling COVID-19 was conducted. In this scoping review, 241 research articles published before May 14, 2021 were analyzed to better understand the model types and compartmental structures used in modeling COVID-19. Three types of dynamics models were analyzed: compartment models expanded based on susceptible-exposed-infected-recovered (SEIR) model, meta-population models, and agent-based models. The expanded compartments based on SEIR model are mainly according to the COVID-19 transmission characteristics, public health interventions, and age structure. The meta-population models and the agent-based models, as a trade-off for more complex model structures, basic susceptible-exposed-infected-recovered or simply expanded compartmental structures were generally adopted.

Conclusion

There has been a great deal of models to understand the spread of COVID-19, and to help prevention and control strategies. Researchers build compartments according to actual situation, research objectives and complexity of models used. As the COVID-19 epidemic remains uncertain and poses a major challenge to humans, researchers still need dynamic models as the main tool to predict dynamics, evaluate intervention effects, and provide scientific evidence for the development of prevention and control strategies. The compartmental structures reviewed in this study provide guidance for future modeling for COVID-19, and also offer recommendations for the dynamic modeling of other infectious diseases.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-01001-y.

Assessing Knowledge, Preventive Practices, and Depression Among Chinese International Students and Local Korean Students in South Korea During the COVID-19 Pandemic: An Online Cross-Sectional Study

Depression among university students and international university students is an increasing problem globally. This study aimed to clarify the differences on the conditions and determinants of the knowledge, preventive practices and depression of the Chinese international students and local Korean students in South Korea during the COVID-19 pandemic. An online cross-sectional questionnaire including general demographic characteristics, COVID-19-related knowledge, preventive practice, and the Patient Health Questionnaire (PHQ-9) was applied from March 23 to April 22, 2020. A total of 533 university students (171 Chinese international students and 362 local South Korean students) were included in the study. The majority of both Chinese international students and local South Korean students had a good comprehension of COVID-19. Chinese international students in South Korea showed better preventive practice than local Korean students, while the proportion of moderate to severe depression of Chinese international students was relatively higher (28.07%) than that of local Korean students (22.38%). Determinants of depression of Chinese international students in South Korea were information satisfaction, likelihood of survival after infection, symptoms of a cough and feelings of discrimination, while for local Korean students were gender, educational level, family, suspected symptoms, self-assessed physical health status, COVID-19 detection, population contact history and online sources of information. These results could be used as a reference for decreasing the depressive symptoms among the university students.

A resposta da Coreia do Sul à pandemia de COVID-19: lições aprendidas e recomendações a gestores

Resumo: Os estudos publicados sobre a resposta da Coreia do Sul à COVID-19 apontam para distintos motivos para seu êxito. Não foram identificadas revisões sobre a Coreia do Sul entre janeiro de 2020 e abril de 2021 ou que analisassem o recrudescimento da pandemia. Visando melhor sistematização sobre o seu sucesso no controle da epidemia, desenvolveu-se uma revisão integrativa para analisar a experiência daquele país no enfrentamento da pandemia de COVID-19, buscando identificar a relação entre as medidas adotadas, as características do sistema de saúde e a evolução de indicadores selecionados. Utilizaram-se distintas bases de dados, além dos boletins epidemiológicos e conferências de imprensa do Centro Sul-coreano de Prevenção e Controle de Doenças (KCDC). Adicionalmente, analisaram-se relatórios da Organização Mundial da Saúde (OMS), do Observatório Europeu de Políticas e Sistemas de Saúde. Os resultados do presente estudo permitem identificar um conjunto de lições com base na experiência sul-coreana visando o controle e manejo da doença. A resposta da Coreia do Sul foi bem-sucedida devido às ações no controle de riscos e danos, atuação sobre determinantes sociais para mitigar os efeitos socioeconômicos da crise sanitária, a experiência prévia em outras epidemias respiratórias e a coordenação nacional expressiva.

Satisfaction with life among university students from nine countries: Cross-national study during the first wave of COVID-19 pandemic

Background

A cross-sectional study was performed to examine life satisfaction differences between university students from nine countries during the first wave of the COVID-19 pandemic. A cross-national comparison of the association between life satisfaction and a set of variables was also conducted.

Methods

Participants in the study were 2349 university students with a mean age of 23 years (M = 23.15, SD = 4.66). There was a predominance of women (69.26%) and individuals studying at the bachelor level (78%). The research was conducted between May and July 2020 in nine countries: Slovenia (n=209), the Czech Republic (Czechia)(n=308), Germany (n=267), Poland (n=301), Ukraine (n=310), Russia (n=285), Turkey (n=310), Israel (n=199), and Colombia (n=153). Participants completed an online survey involving measures of satisfaction with life (SWLS), exposure to COVID-19, perceived negative impact of coronavirus (PNIC) on students' well-being, general self-reported health (GSRH), physical activity (PA), and some demographics (gender, place of residence, level of study). A one-way ANOVA was used to explore cross-national differences in life satisfaction. The χ² independence test was performed separately in each country to examine associations between life satisfaction and other variables. Bivariate and multivariate logistic regressions were used to identify life satisfaction predictors among a set of demographic and health-related variables in each of the nine countries.

Results

The level of life satisfaction varied between university students from the nine countries. The results for life satisfaction and the other variables differed between countries. Numerous associations were noted between satisfaction with life and several variables, and these showed cross-national differences. Distinct predictors of life satisfaction were observed for each country. However, poor self-rated physical health was a predictor of low life satisfaction independent of the country.

Conclusions

The association between life satisfaction and subjective assessment of physical health seems to be universal, while the other variables are related to cross-cultural differences. Special public health attention should be focused on psychologically supporting people who do not feel healthy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12288-1.

Public health effects of travel-related policies on the COVID-19 pandemic: A mixed-methods systematic review

OBJECTIVES

To map travel policies implemented due to COVID-19 during 2020, and conduct a mixed-methods systematic review of health effects of such policies, and related contextual factors.

DESIGN

Policy mapping and systematic review. DATA SOURCES AND ELIGIBILITY CRITERIA: for the policy mapping, we searched websites of relevant government bodies and used data from the Oxford COVID-19 Government Response Tracker for a convenient sample of 31 countries across different regions. For the systematic review, we searched Medline (Ovid), PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and COVID-19 specific databases. We included randomized controlled trial, non-randomized studies, modeling studies, and qualitative studies. Two independent reviewers selected studies, abstracted data and assessed risk of bias.

RESULTS

Most countries adopted a total border closure at the start of the pandemic. For the remainder of the year, partial border closure banning arrivals from some countries or regions was the most widely adopted measure, followed by mandatory quarantine and screening of travelers. The systematic search identified 69 eligible studies, including 50 modeling studies. Both observational and modeling evidence suggest that border closure may reduce the number of COVID-19 cases, disease spread across countries and between regions, and slow the progression of the outbreak. These effects are likely to be enhanced when implemented early, and when combined with measures reducing transmission rates in the community. Quarantine of travelers may decrease the number of COVID-19 cases but its effectiveness depends on compliance and enforcement and is more effective if followed by testing, especially when less than 14 day-quarantine is considered. Screening at departure and/or arrival is unlikely to detect a large proportion of cases or to delay an outbreak. Effectiveness of screening may be improved with increased sensitivity of screening tests, awareness of travelers, asymptomatic screening, and exit screening at country source. While four studies on contextual evidence found that the majority of the public is supportive of travel restrictions, they uncovered concerns about the unintended harms of those policies.

CONCLUSION

Most countries adopted full or partial border closure in response to COVID-19 in 2020. Evidence suggests positive effects on controlling the COVID-19 pandemic for border closure (particularly when implemented early), as well as quarantine of travelers (particularly with higher levels of compliance). While these positive effects are enhanced when implemented in combination with other public health measures, they are associated with concerns by the public regarding some unintended effects.

Systematic review of predictive mathematical models of COVID-19 epidemic

BACKGROUND

Various mathematical models were published to predict the epidemiological consequences of the COVID-19 pandemic. This systematic review has studied the initial epidemiological models.

METHODS

Articles published from January to June 2020 were extracted from databases using search strings and those peer-reviewed with full text in English were included in the study. They were analysed as to whether they made definite predictions in terms of time and numbers, or contained only mathematical assumptions and open-ended predictions. Factors such as early vs. late prediction models, long-term vs. curve-fitting models and comparisons based on modelling techniques were analysed in detail.

RESULTS

Among 56,922 hits in 05 databases, screening yielded 434 abstracts, of which 72 articles were included. Predictive models comprised over 70% (51/72) of the articles, with susceptible, exposed, infectious and recovered (SEIR) being the commonest type (mean duration of prediction being 3 months). Common predictions were regarding cumulative cases (44/72, 61.1%), time to reach total numbers (41/72, 56.9%), peak numbers (22/72, 30.5%), time to peak (24/72, 33.3%), hospital utilisation (7/72, 9.7%) and effect of lockdown and NPIs (50/72, 69.4%). The commonest countries for which models were predicted were China followed by USA, South Korea, Japan and India. Models were published by various professionals including Engineers (12.5%), Mathematicians (9.7%), Epidemiologists (11.1%) and Physicians (9.7%) with a third (32.9%) being the result of collaborative efforts between two or more professions.

CONCLUSION

There was a wide diversity in the type of models, duration of prediction and the variable that they predicted, with SEIR model being the commonest type.

Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures

Existing coronavirus named as a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has speeded its spread across the globe immediately after emergence in China, Wuhan region, at the end of the year 2019. Different techniques, including genome sequencing, structural feature classification by electron microscopy, and chest imaging using computed tomography, are primarily used to diagnose and screen SARS-CoV-2 suspected individuals. Determination of the viral structure, surface proteins, and genome sequence has provided a design blueprint for the diagnostic investigations of novel SARS-CoV-2 virus and rapidly emerging diagnostic technologies, vaccine trials, and cell-entry-inhibiting drugs. Here, we describe recent understandings on the spike glycoprotein (S protein), receptor-binding domain (RBD), and angiotensin-converting enzyme 2 (ACE2) and their receptor complex. This report also aims to review recently established diagnostic technologies and developments in surveillance measures for SARS-CoV-2 as well as the characteristics and performance of emerging techniques. Smartphone apps for contact tracing can help nations to conduct surveillance measures before a vaccine and effective medicines become available. We also describe promising point-of-care (POC) diagnostic technologies that are under consideration by researchers for advancement beyond the proof-of-concept stage. Developing novel diagnostic techniques needs to be facilitated to establish automatic systems, without any personal involvement or arrangement to curb an existing SARS-CoV-2 epidemic crisis, and could also be appropriate for avoiding the emergence of a future epidemic crisis.

International travel-related control measures to contain the COVID-19 pandemic: a rapid review

BACKGROUND

In late 2019, the first cases of coronavirus disease 2019 (COVID-19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers.

OBJECTIVES

To assess the effectiveness of international travel-related control measures during the COVID-19 pandemic on infectious disease transmission and screening-related outcomes.

SEARCH METHODS

We searched MEDLINE, Embase and COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO Global Database on COVID-19 Research to 13 November 2020.

SELECTION CRITERIA

We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across international borders during the COVID-19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID-19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements.

MAIN RESULTS

Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel-related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross-border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low-certainty evidence for a reduction in COVID-19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low-certainty evidence that cross-border travel controls can slow the spread of COVID-19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure-based screening or test-based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure-based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate-certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low-certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low-certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low-certainty evidence), although all but one study observed this proportion to be less than 54%. For test-based screening, one modelling study provided very low-certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low-certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low- to low-certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low-certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low- to low-certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low-certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine.

AUTHORS' CONCLUSIONS

With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross-border travel and quarantine of travellers, there is a lack of 'real-world' evidence. The certainty of the evidence for most travel-related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure-based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure-based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel-related control measures from a societal perspective.

Factors Influencing Asia-Pacific Countries' Success Level in Curbing COVID-19: A Review Using a Social-Ecological System (SES) Framework

Little attention has been paid to the impacts of institutional-human-environment dimensions on the outcome of Coronavirus disease 2019 (COVID-19) abatement. Through the diagnostic social-ecological system (SES) framework, this review paper aimed to investigate what and how the multifaceted social, physical, and governance factors affected the success level of seven selected Asia-Pacific countries (namely, South Korea, Japan, Malaysia, Singapore, Vietnam, Indonesia, and New Zealand) in combatting COVID-19. Drawing on statistical data from the Our World In Data website, we measured the COVID-19 severity or abatement success level of the countries on the basis of cumulative positive cases, average daily cases, and mortality rates for the period of 1 February 2020 to 30 June 2020. A qualitative content analysis using three codes, i.e., present (P), partially present (PP), and absent (A) for each SES attribute, as well as score calculation and rank ordering for government response effectiveness and the abatement success level across the countries, was undertaken. Not only did the standard coding process ensure data comparability but the data were deemed substantially reliable with Cohen's kappa of 0.76. Among 13 attributes of the SES factors, high facility adequacy, comprehensive COVID-19 testing policies, strict lockdown measures, imposition of penalty, and the high trust level towards the government seemed to be significant in determining the COVID-19 severity in a country. The results show that Vietnam (ranked first) and New Zealand (ranked second), with a high presence of attributes/design principles contributing to high-level government stringency and health and containment indices, successfully controlled the virus, while Indonesia (ranked seventh) and Japan (ranked sixth), associated with the low presence of design principles, were deemed least successful. Two lessons can be drawn: (i) having high number of P for SES attributes does not always mean a panacea for the pandemic; however, it would be detrimental to a country if it lacked them severely, and (ii) some attributes (mostly from the governance factor) may carry higher weightage towards explaining the success level. This comparative study providing an overview of critical SES attributes in relation to COVID-19 offers novel policy insights, thus helping policymakers devise more strategic, coordinated measures, particularly for effective country preparedness and response in addressing the current and the future health crisis.

A Phenomenological Study on the Positive and Negative Experiences of Chinese International University Students From Hong Kong Studying in the U.K. and U.S. in the Early Stage of the COVID-19 Pandemic

Background: The COVID-19 pandemic has caused distress in students globally. The mental health of international students studying abroad has been neglected during the COVID-19 pandemic, especially Chinese students who have been unfairly targeted. Objective: To explore and document the positive and negative experiences of a group of Hong Kong Chinese international students studying in the U.K. and U.S. from an insider perspective in the early stage of the COVID-19 pandemic. Methods: The qualitative study used four 1.5-h online focus group interviews of 20 Chinese international students from Hong Kong aged 18 or older studying in universities in the United Kingdom or the United States, from 3 May to 12 May 2020. A framework approach with a semi-structured interview guide was used to reflect students' stressors, cognitive appraisals, coping, and outcomes (negative impacts and positive gains), in the early stages of COVID-19. Different strategies were used to ensure the credibility, dependability, confirmability, and transferability of the study. Transcripts were analyzed using qualitative thematic content analysis. Results: Twenty full-time international University students (60% female, 90% aged 18-25 years and 65% undergraduates) were recruited. Students reported (i) stress from personal (e.g., worries about health and academic attainment), interpersonal (e.g., perceived prejudice and lack of social support), and environmental factors (e.g., uncertainties about academic programme and unclear COVID-19-related information); (ii) significant differences in culture and cognitive appraisal in the levels of perceived susceptibility and severity; (iii) positive thinking and using alternative measures in meeting challenges, which included effective emotion and problem coping strategies, and the importance of support from family, friends and schools; and (iv) negative psychological impact (e.g., worries and stress) and positive personal growth in crisis management and gains in family relationships. Conclusions: With the rise in sinophobia and uncertain developments of the pandemic, proactive support from government and academic institutions are urgently needed to reduce stress and promote the well-being of international students, especially Chinese students in the U.K. and U.S. Clear information, public education and policies related to the pandemic, appropriate academic arrangements from universities and strong support systems play important roles in maintaining students' psychological health. Clinical Trial Registration: The study was registered with the National Institutes of Health (https://clinicaltrials.gov/, identifier: NCT04365361).

Does Physical Activity Matter for the Mental Health of University Students during the COVID-19 Pandemic?

Research indicates that university and college students are at higher risk of experiencing mental health problems than other populations. This study aims to examine the relationship between Physical Activity (PA) and the mental health of Ukrainian university students during the Corona Virus Disease 2019 (COVID-19) pandemic lockdown. The conventional sample consisted of 1512 students from 11 Ukrainian universities, with a mean age of 20 years (M = 20.06, SD = 3.05) and 69% of whom were female. The cross-sectional online survey was disseminated through the most popular social media channels in Ukraine (i.e., Facebook, Viber, Telegram) and included the Generalized Anxiety Disorder (GAD-7) scale to measure anxiety and the Patient Health Questionnaire (PHQ-9) to assess depression. Data were collected from 14 May to 4 June 2020 during the COVID-19 pandemic outbreak in Ukraine. Among university students, 43% were engaged in PA ≥ 150 min weekly, 24% met the criteria of GAD, and 32% met the criteria of depression. More students were involved in PA before the COVID-19 outbreak than during the national lockdown. Students with anxiety and depression were almost two times less likely to engage in PA than their counterparts without mental health disorders. The inactive group had higher scores of anxiety and depression than the physically active group. The relationship of PA with anxiety and depression was statistically significant but weak during the COVID-19 pandemic.

Interpretation of the Basic and Effective Reproduction Number

In epidemiology, the basic reproduction number (R₀) is a term that describes the expected number of infections generated by 1 case in a susceptible population. At the beginning of the coronavirus disease 2019 (COVID-19) pandemic, R₀ was frequently referenced by the public health community and the wider public. However, this metric is often misused or misinterpreted. Moreover, the complexity of the process of estimating R₀ has caused difficulties for a substantial number of researchers. In this article, in order to increase the accessibility of this concept, we address several misconceptions related to the threshold characteristics of R₀ and the effective reproduction number (R_t). Moreover, the appropriate interpretation of the metrics is discussed. R₀ should be considered as a population-averaged value that pools the contact structure according to a stochastic transmission process. Furthermore, it is necessary to understand the unavoidable time lag for R_t due to the incubation period of the disease.

Self-Quarantine Noncompliance During the COVID-19 Pandemic in South Korea

OBJECTIVES

In South Korea, many individuals were self-quarantined for the coronavirus disease 2019 (COVID-19) after the quarantine criteria were extended to all overseas travelers. This study was conducted to identify the noncompliance rate of self-quarantine for COVID-19 cases and assess the impact of a 1-strike out policy and an increased amount of penalty for the violating self-quarantine in South Korea.

METHODS

The self-quarantine noncompliance rate for COVID-19 was examined using publicly available data. We collected the daily number of quarantine and quarantine violation cases from March 22 to June 10, 2020. A Poisson regression analysis was conducted to identify the impact of additional sanctions for the quarantine violation.

RESULTS

The median number of individuals quarantined per day was 36,561 (interquartile range, 34,408-41,961). The median number of daily self-quarantine violations was 6 (range, 0-13). The median rate of self-quarantine violations was 1.6 per 10,000 self-quarantined individuals (range, 0.0-8.0 per 10,000 self-quarantined individuals). The additional sanction has no significant impact on the number of violations among quarantine individuals (P = 0.99).

CONCLUSIONS

The additional sanction for the violation of quarantined individuals did not reduce the self-quarantine violations. Further studies are warranted to strengthen the compliance of self-quarantine for future pandemics.

Anticipating the Need for Healthcare Resources Following the Escalation of the COVID-19 Outbreak in the Republic of Kazakhstan

Objectives

The lack of advance planning in a public health emergency can lead to wasted resources and inadvertent loss of lives. This study is aimed at forecasting the needs for healthcare resources following the expansion of the coronavirus disease 2019 (COVID-19) outbreak in the Republic of Kazakhstan, focusing on hospital beds, equipment, and the professional workforce in light of the developing epidemiological situation and the data on resources currently available.

Methods

We constructed a forecast model of the epidemiological scenario via the classic susceptible-exposed-infected-removed (SEIR) approach. The World Health Organization’s COVID-19 Essential Supplies Forecasting Tool was used to evaluate the healthcare resources needed for the next 12 weeks.

Results

Over the forecast period, there will be 104 713.7 hospital admissions due to severe disease and 34 904.5 hospital admissions due to critical disease. This will require 47 247.7 beds for severe disease and 1929.9 beds for critical disease at the peak of the COVID-19 outbreak. There will also be high needs for all categories of healthcare workers and for both diagnostic and treatment equipment. Thus, Republic of Kazakhstan faces the need for a rapid increase in available healthcare resources and/or for finding ways to redistribute resources effectively.

Conclusions

Republic of Kazakhstan will be able to reduce the rates of infections and deaths among its population by developing and following a consistent strategy targeting COVID-19 in a number of inter-related directions.

Travel-related control measures to contain the COVID-19 pandemic: a rapid review

BACKGROUND

In late 2019, first cases of coronavirus disease 2019, or COVID-19, caused by the novel coronavirus SARS-CoV-2, were reported in Wuhan, China. Subsequently COVID-19 spread rapidly around the world. To contain the ensuing pandemic, numerous countries have implemented control measures related to international travel, including border closures, partial travel restrictions, entry or exit screening, and quarantine of travellers.

OBJECTIVES

To assess the effectiveness of travel-related control measures during the COVID-19 pandemic on infectious disease and screening-related outcomes.

SEARCH METHODS

We searched MEDLINE, Embase and COVID-19-specific databases, including the WHO Global Database on COVID-19 Research, the Cochrane COVID-19 Study Register, and the CDC COVID-19 Research Database on 26 June 2020. We also conducted backward-citation searches with existing reviews.

SELECTION CRITERIA

We considered experimental, quasi-experimental, observational and modelling studies assessing the effects of travel-related control measures affecting human travel across national borders during the COVID-19 pandemic. We also included studies concerned with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) as indirect evidence. Primary outcomes were cases avoided, cases detected and a shift in epidemic development due to the measures. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome.

DATA COLLECTION AND ANALYSIS

One review author screened titles and abstracts; all excluded abstracts were screened in duplicate. Two review authors independently screened full texts. One review author extracted data, assessed risk of bias and appraised study quality. At least one additional review author checked for correctness of all data reported in the 'Risk of bias' assessment, quality appraisal and data synthesis. For assessing the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool for observational studies concerned with screening, ROBINS-I for observational ecological studies and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed certainty of evidence with GRADE, and the review author team discussed ratings.

MAIN RESULTS

We included 40 records reporting on 36 unique studies. We found 17 modelling studies, 7 observational screening studies and one observational ecological study on COVID-19, four modelling and six observational studies on SARS, and one modelling study on SARS and MERS, covering a variety of settings and epidemic stages. Most studies compared travel-related control measures against a counterfactual scenario in which the intervention measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of travel restrictions, or a combination of measures. There were concerns with the quality of many modelling studies and the risk of bias of observational studies. Many modelling studies used potentially inappropriate assumptions about the structure and input parameters of models, and failed to adequately assess uncertainty. Concerns with observational screening studies commonly related to the reference test and the flow of the screening process. Studies on COVID-19 Travel restrictions reducing cross-border travel Eleven studies employed models to simulate a reduction in travel volume; one observational ecological study assessed travel restrictions in response to the COVID-19 pandemic. Very low-certainty evidence from modelling studies suggests that when implemented at the beginning of the outbreak, cross-border travel restrictions may lead to a reduction in the number of new cases of between 26% to 90% (4 studies), the number of deaths (1 study), the time to outbreak of between 2 and 26 days (2 studies), the risk of outbreak of between 1% to 37% (2 studies), and the effective reproduction number (1 modelling and 1 observational ecological study). Low-certainty evidence from modelling studies suggests a reduction in the number of imported or exported cases of between 70% to 81% (5 studies), and in the growth acceleration of epidemic progression (1 study). Screening at borders with or without quarantine Evidence from three modelling studies of entry and exit symptom screening without quarantine suggests delays in the time to outbreak of between 1 to 183 days (very low-certainty evidence) and a detection rate of infected travellers of between 10% to 53% (low-certainty evidence). Six observational studies of entry and exit screening were conducted in specific settings such as evacuation flights and cruise ship outbreaks. Screening approaches varied but followed a similar structure, involving symptom screening of all individuals at departure or upon arrival, followed by quarantine, and different procedures for observation and PCR testing over a period of at least 14 days. The proportion of cases detected ranged from 0% to 91% (depending on the screening approach), and the positive predictive value ranged from 0% to 100% (very low-certainty evidence). The outcomes, however, should be interpreted in relation to both the screening approach used and the prevalence of infection among the travellers screened; for example, symptom-based screening alone generally performed worse than a combination of symptom-based and PCR screening with subsequent observation during quarantine. Quarantine of travellers Evidence from one modelling study simulating a 14-day quarantine suggests a reduction in the number of cases seeded by imported cases; larger reductions were seen with increasing levels of quarantine compliance ranging from 277 to 19 cases with rates of compliance modelled between 70% to 100% (very low-certainty evidence).

AUTHORS' CONCLUSIONS

With much of the evidence deriving from modelling studies, notably for travel restrictions reducing cross-border travel and quarantine of travellers, there is a lack of 'real-life' evidence for many of these measures. The certainty of the evidence for most travel-related control measures is very low and the true effects may be substantially different from those reported here. Nevertheless, some travel-related control measures during the COVID-19 pandemic may have a positive impact on infectious disease outcomes. Broadly, travel restrictions may limit the spread of disease across national borders. Entry and exit symptom screening measures on their own are not likely to be effective in detecting a meaningful proportion of cases to prevent seeding new cases within the protected region; combined with subsequent quarantine, observation and PCR testing, the effectiveness is likely to improve. There was insufficient evidence to draw firm conclusions about the effectiveness of travel-related quarantine on its own. Some of the included studies suggest that effects are likely to depend on factors such as the stage of the epidemic, the interconnectedness of countries, local measures undertaken to contain community transmission, and the extent of implementation and adherence.

Quarantine alone or in combination with other public health measures to control COVID-19: a rapid review

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a rapidly emerging disease classified as a pandemic by the World Health Organization (WHO). To support the WHO with their recommendations on quarantine, we conducted a rapid review on the effectiveness of quarantine during severe coronavirus outbreaks.

OBJECTIVES

To assess the effects of quarantine (alone or in combination with other measures) of individuals who had contact with confirmed or suspected cases of COVID-19, who travelled from countries with a declared outbreak, or who live in regions with high disease transmission.

SEARCH METHODS

An information specialist searched the Cochrane COVID-19 Study Register, and updated the search in PubMed, Ovid MEDLINE, WHO Global Index Medicus, Embase, and CINAHL on 23 June 2020.

SELECTION CRITERIA

Cohort studies, case-control studies, time series, interrupted time series, case series, and mathematical modelling studies that assessed the effect of any type of quarantine to control COVID-19. We also included studies on SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome) as indirect evidence for the current coronavirus outbreak.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened abstracts and titles in duplicate. Two review authors then independently screened all potentially relevant full-text publications. One review author extracted data, assessed the risk of bias and assessed the certainty of evidence with GRADE and a second review author checked the assessment. We used three different tools to assess risk of bias, depending on the study design: ROBINS-I for non-randomised studies of interventions, a tool provided by Cochrane Childhood Cancer for non-randomised, non-controlled studies, and recommendations from the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) for modelling studies. We rated the certainty of evidence for the four primary outcomes: incidence, onward transmission, mortality, and costs.

MAIN RESULTS

We included 51 studies; 4 observational studies and 28 modelling studies on COVID-19, one observational and one modelling study on MERS, three observational and 11 modelling studies on SARS, and three modelling studies on SARS and other infectious diseases. Because of the diverse methods of measurement and analysis across the outcomes of interest, we could not conduct a meta-analysis and undertook a narrative synthesis. We judged risk of bias to be moderate for 2/3 non-randomized studies of interventions (NRSIs) and serious for 1/3 NRSI. We rated risk of bias moderate for 4/5 non-controlled cohort studies, and serious for 1/5. We rated modelling studies as having no concerns for 13 studies, moderate concerns for 17 studies and major concerns for 13 studies. Quarantine for individuals who were in contact with a confirmed/suspected COVID-19 case in comparison to no quarantine Modelling studies consistently reported a benefit of the simulated quarantine measures, for example, quarantine of people exposed to confirmed or suspected cases may have averted 44% to 96% of incident cases and 31% to 76% of deaths compared to no measures based on different scenarios (incident cases: 6 modelling studies on COVID-19, 1 on SARS; mortality: 2 modelling studies on COVID-19, 1 on SARS, low-certainty evidence). Studies also indicated that there may be a reduction in the basic reproduction number ranging from 37% to 88% due to the implementation of quarantine (5 modelling studies on COVID-19, low-certainty evidence). Very low-certainty evidence suggests that the earlier quarantine measures are implemented, the greater the cost savings may be (2 modelling studies on SARS). Quarantine in combination with other measures to contain COVID-19 in comparison to other measures without quarantine or no measures When the models combined quarantine with other prevention and control measures, such as school closures, travel restrictions and social distancing, the models demonstrated that there may be a larger effect on the reduction of new cases, transmissions and deaths than measures without quarantine or no interventions (incident cases: 9 modelling studies on COVID-19; onward transmission: 5 modelling studies on COVID-19; mortality: 5 modelling studies on COVID-19, low-certainty evidence). Studies on SARS and MERS were consistent with findings from the studies on COVID-19. Quarantine for individuals travelling from a country with a declared COVID-19 outbreak compared to no quarantine Very low-certainty evidence indicated that the effect of quarantine of travellers from a country with a declared outbreak on reducing incidence and deaths may be small for SARS, but might be larger for COVID-19 (2 observational studies on COVID-19 and 2 observational studies on SARS).

AUTHORS' CONCLUSIONS

The current evidence is limited because most studies on COVID-19 are mathematical modelling studies that make different assumptions on important model parameters. Findings consistently indicate that quarantine is important in reducing incidence and mortality during the COVID-19 pandemic, although there is uncertainty over the magnitude of the effect. Early implementation of quarantine and combining quarantine with other public health measures is important to ensure effectiveness. In order to maintain the best possible balance of measures, decision makers must constantly monitor the outbreak and the impact of the measures implemented. This review was originally commissioned by the WHO and supported by Danube-University-Krems. The update was self-initiated by the review authors.

Incubation period of the coronavirus disease 2019 (COVID-19) in Busan, South Korea

The assessment of the incubation period, which is the period between the infection and the illness onset, is essential to identify the sufficient isolation period for infectious diseases. In South Korea, a few cases of the coronavirus disease 2019 (COVID-19) were identified after the 14-day self-quarantine program, and the length of this quarantine has raised controversial issues for the Korean public health professionals.

We estimated the COVID-19 incubation period using the log-normal distribution from publicly available data. The data were obtained from the press release of the Busan city department of public health and news reports.

We collected and analysed information for 47 patients with a median age of 30. We estimated that the median incubation period was three days (95% Confidence Interval, 0.6–8.2). We also did not find any significant difference in the incubation period between males and females.

Our findings indicate that a 14-day self-quarantine program should be sufficient to prevent spreading in the infection of suspected individuals with COVID-19 in the community.