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      KCI등재 SCI SCIE SCOPUS

      Estimating the Effectiveness of Non-pharmaceutical Interventions on COVID-19 Control in Korea

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      https://www.riss.kr/link?id=A107040734

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      다국어 초록 (Multilingual Abstract)

      Background: The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spr...

      Background: The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model.
      Methods: A compartment model with a susceptible-exposed-infectious-quarantined- hospitalized structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs' sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI.
      Results: Relaxed social distancing among adults would have increased the number of cases 27.4-fold until the end of March. Spring semester non-postponement would have increased the number of cases 1.7-fold among individuals aged 0–19, while lower quarantine and detection rates would have increased the number of cases 1.4-fold.
      Conclusion: Among the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered when preparing for the 2nd wave of COVID-19.

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      참고문헌 (Reference)

      1 Pan Y, "Viral load of SARS-CoV-2 in clinical samples" 20 (20): 411-412, 2020

      2 Liu Y, "Viral dynamics in mild and severe cases of COVID-19" 20 (20): 656-657, 2020

      3 Lauer SA, "The incubation period of coronavirus disease 2019(COVID-19)from publicly reported confirmed cases : estimation and application" 172 (172): 577-582, 2020

      4 Walker PG, "The global impact of covid-19and strategies for mitigation and suppression"

      5 Kraemer MU, "The effect of human mobility and control measures on the COVID-19 epidemic in China" 368 (368): 493-497, 2020

      6 Maliszewska M, "The Potential Impact of COVID-19 on GDP and Trade: a Preliminary Assessment" The World Bank 2020

      7 김소영, "School Opening Delay Effect on Transmission Dynamics of Coronavirus Disease 2019 in Korea: Based on Mathematical Modeling and Simulation Study" 대한의학회 35 (35): 1-9, 2020

      8 Korean Society of Infectious Diseases, "Report on the Epidemiological Features of Coronavirus Disease 2019 (COVID-19) Outbreak in the Republic of Korea from January 19 to March 2, 2020" 대한의학회 35 (35): 1-11, 2020

      9 Prem K, "Projecting social contact matrices in 152 countries using contact surveys and demographic data" 13 (13): e1005697-, 2017

      10 Ferguson N, "Impact of Non-pharmaceutical Interventions(NPIs)to Reduce COVID-19 Mortality and Healthcare Demand"

      1 Pan Y, "Viral load of SARS-CoV-2 in clinical samples" 20 (20): 411-412, 2020

      2 Liu Y, "Viral dynamics in mild and severe cases of COVID-19" 20 (20): 656-657, 2020

      3 Lauer SA, "The incubation period of coronavirus disease 2019(COVID-19)from publicly reported confirmed cases : estimation and application" 172 (172): 577-582, 2020

      4 Walker PG, "The global impact of covid-19and strategies for mitigation and suppression"

      5 Kraemer MU, "The effect of human mobility and control measures on the COVID-19 epidemic in China" 368 (368): 493-497, 2020

      6 Maliszewska M, "The Potential Impact of COVID-19 on GDP and Trade: a Preliminary Assessment" The World Bank 2020

      7 김소영, "School Opening Delay Effect on Transmission Dynamics of Coronavirus Disease 2019 in Korea: Based on Mathematical Modeling and Simulation Study" 대한의학회 35 (35): 1-9, 2020

      8 Korean Society of Infectious Diseases, "Report on the Epidemiological Features of Coronavirus Disease 2019 (COVID-19) Outbreak in the Republic of Korea from January 19 to March 2, 2020" 대한의학회 35 (35): 1-11, 2020

      9 Prem K, "Projecting social contact matrices in 152 countries using contact surveys and demographic data" 13 (13): e1005697-, 2017

      10 Ferguson N, "Impact of Non-pharmaceutical Interventions(NPIs)to Reduce COVID-19 Mortality and Healthcare Demand"

      11 Hellewell J, "Feasibility of controlling COVID-19outbreaks by isolation of cases and contacts" 8 (8): e488-e496, 2020

      12 Pastorino B, "Evaluation of heating and chemical protocols for inactivating SARS-CoV-2"

      13 Mizumoto K, "Estimating the asymptomatic proportion of coronavirus disease 2019(COVID-19)cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020" 25 (25): 2000180-, 2020

      14 기모란, "Epidemiologic characteristics of early cases with 2019 novel coronavirus (2019-nCoV) disease in Korea" 한국역학회 42 : 1-7, 2020

      15 Lai S, "Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China"

      16 Morton A, "Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods" 54 (54): 575-594, 2005

      17 Day M, "Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village" 368 : m1165-, 2020

      18 World Health Organization, "Coronavirus Disease 2019 (COVID-19):" World Health Organization 2020

      19 Gyeonggi Infectious Disease Control Center, "Coronavirus Disease 2019 (COVID-19) Gyeonggi Daily Report" Gyeonggi Infectious Disease Control Center 2020

      20 O'Neill PD, "A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods" 180 (180): 103-114, 2002

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2011-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2009-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2005-01-01 평가 SCI 등재 (등재유지) KCI등재
      2002-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1999-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.48 0.37 1.06
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.85 0.75 0.691 0.11
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