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

Lee, Hansol; Kim, Kyung‐Tae; Choi, Kwonkyu; Hong, Sang‐Bum; Son, Hyunjin; Ryu, Sukhyun

doi:10.1016/j.jiac.2020.06.018

Cited by 27 publications

(32 citation statements)

References 11 publications

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“…the estimated median and its range with other study, we saw a similar trend where our estimations are similar or higher than most studies where median estimation was available [4,5,7,8]. Nonetheless, extreme estimation of incubation periods (95 th or 97.5 th percentiles) in studies are well within 14 days from possible infection [4,5,[7][8][9][10][11][12][13]. https://doi.org/10.1371/journal.pone.0243889.g002…”

Section: Plos Onesupporting

confidence: 84%

“…However, the country has limited resources, hence understanding the time of intensive monitoring will be beneficial to plan for effective measures to minimize the risk for hidden SARS-CoV-2 infection. While estimations of incubation period of SARS-CoV-2 have been conducted elsewhere in the world [4][5][6][7][8][9][10][11][12][13], there is no estimation of this parameter using data from Vietnam, instead, efforts were only focusing on describing pattern of COVID-19 pandemic in Vietnam [14][15][16]. This study aims to estimate the incubation period of Vietnamese confirmed COVID-19 cases.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of the incubation period of COVID-19 in Vietnam

Bui¹,

Nguyen

Levine

et al. 2020

PLoS ONE

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Objective To estimate the incubation period of Vietnamese confirmed COVID-19 cases. Methods Only confirmed COVID-19 cases who are Vietnamese and locally infected with available data on date of symptom onset and clearly defined window of possible SARS-CoV-2 exposure were included. We used three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference to estimate incubation period for Vietnamese COVID-19 cases. Leave-one-out Information Criterion was used to assess the performance of three models. Results A total of 19 cases identified from 23 Jan 2020 to 13 April 2020 was included in our analysis. Average incubation periods estimated using different distribution model ranged from 6.0 days to 6.4 days with the Weibull distribution demonstrated the best fit to the data. The estimated mean of incubation period using Weibull distribution model was 6.4 days (95% credible interval (CrI): 4.89–8.5), standard deviation (SD) was 3.05 (95%CrI 3.05–5.30), median was 5.6, ranges from 1.35 to 13.04 days (2.5th to 97.5th percentiles). Extreme estimation of incubation periods is within 14 days from possible infection. Conclusion This analysis provides evidence for an average incubation period for COVID-19 of approximately 6.4 days. Our findings support existing guidelines for 14 days of quarantine of persons potentially exposed to SARS-CoV-2. Although for extreme cases, the quarantine period should be extended up to three weeks.

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Section: Plos Onesupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Estimation of the incubation period of COVID-19 in Vietnam

Bui¹,

Nguyen

Levine

et al. 2020

PLoS ONE

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“…3 In South Korea, in order to prevent seeding new SARS-CoV-2 infection, any individual who has traveled from a country with a high COVID-19 infection risk is also obliged to selfquarantine. 4 The quarantined individuals are asked to comply with self-quarantine and are monitored for 14 days. Since April 1, 2020, all overseas travelers have been included in the self-quarantine program, which has greatly increased the number of quarantined individuals in South Korea ( Figure 1A).…”

Section: Introductionmentioning

confidence: 99%

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

Ryu

Hwang

Yoon

et al. 2020

Disaster med. public health prep.

Self Cite

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Background: 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 non-compliance rate of self-quarantine for COVID-19 cases and assess the impact of a one-strike out policy and an increased amount of penalty for the violating self-quarantine in South Korea. Methods: The self-quarantine non-compliance 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 of 34,408–41,961). The median number of daily self-quarantine violations was six (range of 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.

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“…The adoption of 14 days corresponds to the disease incubation period as reported by the World Health Organization (WHO) 8 and medical empirical research 9,10,11 . Thus, we expected to observe a delayed policy effect.…”

Section: Data Collectionmentioning

confidence: 99%

The effect of lockdown on the COVID-19 epidemic in Brazil: evidence from an interrupted time series design

2020

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In response to the COVID-19 pandemic, governments worldwide have implemented social distancing policies with different levels of both enforcement and compliance. We conducted an interrupted time series analysis to estimate the impact of lockdowns on reducing the number of cases and deaths due to COVID-19 in Brazil. Official daily data was collected for four city capitals before and after their respective policies interventions based on a 14 days observation window. We estimated a segmented linear regression to evaluate the effectiveness of lockdown measures on COVID-19 incidence and mortality. The initial number of new cases and new deaths had a positive trend prior to policy change. After lockdown, a statistically significant decrease in new confirmed cases was found in all state capitals. We also found evidence that lockdown measures were likely to reverse the trend of new daily deaths due to COVID-19. In São Luís, we observed a reduction of 37.85% while in Fortaleza the decrease was 33.4% on the average difference in daily deaths if the lockdown had not been implemented. Similarly, the intervention diminished mortality in Recife by 21.76% and Belém by 16.77%. Social distancing policies can be useful tools in flattening the epidemic curve.

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

Cited by 27 publications

References 11 publications

Estimation of the incubation period of COVID-19 in Vietnam

Estimation of the incubation period of COVID-19 in Vietnam

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

The effect of lockdown on the COVID-19 epidemic in Brazil: evidence from an interrupted time series design

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