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利用考虑韩国行为变化的数学模型预测 COVID-19 传播动态。

Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes in Korea.

机构信息

Department of Mathematics, Konkuk University, Seoul, Korea.

Division of Infectious Diseases, Department of Internal Medicine, Hallym University College of Medicine, Chuncheon, Korea.

出版信息

Epidemiol Health. 2020;42:e2020026. doi: 10.4178/epih.e2020026. Epub 2020 Apr 13.

DOI:10.4178/epih.e2020026
PMID:32375455
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7285444/
Abstract

OBJECTIVES

Since the report of the first confirmed case in Daegu on February 18, 2020, local transmission of coronavirus disease 2019 (COVID-19) in Korea has continued. In this study, we aimed to identify the pattern of local transmission of COVID-19 using mathematical modeling and predict the epidemic size and the timing of the end of the spread.

METHODS

We modeled the COVID-19 outbreak in Korea by applying a mathematical model of transmission that factors in behavioral changes. We used the Korea Centers for Disease Control and Prevention data of daily confirmed cases in the country to estimate the nationwide and Daegu/Gyeongbuk area-specific transmission rates as well as behavioral change parameters using a least-squares method.

RESULTS

The number of transmissions per infected patient was estimated to be about 10 times higher in the Daegu/Gyeongbuk area than the average of nationwide. Using these estimated parameters, our models predicts that about 13,800 cases will occur nationwide and 11,400 cases in the Daegu/Gyeongbuk area until mid-June.

CONCLUSIONS

We mathematically demonstrate that the relatively high per-capita rate of transmission and the low rate of changes in behavior have caused a large-scale transmission of COVID-19 in the Daegu/Gyeongbuk area in Korea. Since the outbreak is expected to continue until May, non-pharmaceutical interventions that can be sustained over the long term are required.

摘要

目的

自 2020 年 2 月 18 日韩国大邱首例确诊病例报告以来,2019 年冠状病毒病(COVID-19)在韩国的本地传播持续存在。在这项研究中,我们旨在通过数学建模确定 COVID-19 的本地传播模式,并预测疫情规模和传播结束的时间。

方法

我们通过应用考虑行为变化的传播数学模型来模拟韩国的 COVID-19 疫情。我们使用韩国疾病控制与预防中心(KCDC)在全国范围内每日确诊病例的数据,使用最小二乘法估计全国和大邱/庆尚北道特定地区的传播率以及行为变化参数。

结果

感染患者的传播数量估计在大邱/庆尚北道比全国平均水平高约 10 倍。使用这些估计的参数,我们的模型预测,截至 6 月中旬,全国将发生约 13800 例病例,大邱/庆尚北道将发生 11400 例病例。

结论

我们从数学上证明,相对较高的人均传播率和行为变化率低导致了韩国大邱/庆尚北道 COVID-19 的大规模传播。由于预计疫情将持续到 5 月,因此需要采取能够长期持续的非药物干预措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d45/7285444/65fc9c01d1fb/epih-42-e2020026f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d45/7285444/47930e1de3e3/epih-42-e2020026f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d45/7285444/65fc9c01d1fb/epih-42-e2020026f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d45/7285444/47930e1de3e3/epih-42-e2020026f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d45/7285444/65fc9c01d1fb/epih-42-e2020026f3.jpg

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Epidemiol Health. 2020;42:e2020007. doi: 10.4178/epih.e2020007. Epub 2020 Feb 9.
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