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基于新的随机动力学模型预测中国的 COVID-19 疫情。

Prediction of the COVID-19 outbreak in China based on a new stochastic dynamic model.

机构信息

School of Mathematical Sciences, Peking University, Beijing, 100871, China.

Center for Statistical Sciences, Peking University, Beijing, 100871, China.

出版信息

Sci Rep. 2020 Dec 9;10(1):21522. doi: 10.1038/s41598-020-76630-0.

Abstract

The current outbreak of coronavirus disease 2019 (COVID-19) has become a global crisis due to its quick and wide spread over the world. A good understanding of the dynamic of the disease would greatly enhance the control and prevention of COVID19. However, to the best of our knowledge, the unique features of the outbreak have limited the applications of all existing dynamic models. In this paper, a novel stochastic model was proposed aiming to account for the unique transmission dynamics of COVID-19 and capture the effects of intervention measures implemented in Mainland China. We found that: (1) instead of aberration, there was a remarkable amount of asymptomatic virus carriers, (2) a virus carrier with symptoms was approximately twice more likely to pass the disease to others than that of an asymptomatic virus carrier, (3) the transmission rate reduced significantly since the implementation of control measures in Mainland China, and (4) it was expected that the epidemic outbreak would be contained by early March in the selected provinces and cities in China.

摘要

当前 2019 年冠状病毒病(COVID-19)的爆发因其在世界范围内迅速而广泛的传播已成为一场全球危机。对疾病动态的良好理解将极大地增强对 COVID19 的控制和预防。然而,据我们所知,疫情的独特特征限制了所有现有动力学模型的应用。在本文中,我们提出了一种新的随机模型,旨在考虑 COVID-19 的独特传播动态,并捕捉在中国大陆实施的干预措施的效果。我们发现:(1)存在大量无症状病毒携带者,而不是异常情况,(2)有症状的病毒携带者将疾病传染给他人的可能性大约是无症状病毒携带者的两倍,(3)自中国大陆实施控制措施以来,传播率显著降低,(4)预计疫情将在选定的中国省份和城市于 3 月初得到控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3462/7725788/5f84ef7b8aba/41598_2020_76630_Fig1_HTML.jpg

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本文引用的文献

1
Reconstruction of the full transmission dynamics of COVID-19 in Wuhan.
Nature. 2020 Aug;584(7821):420-424. doi: 10.1038/s41586-020-2554-8. Epub 2020 Jul 16.
2
Estimation of the time-varying reproduction number of COVID-19 outbreak in China.
Int J Hyg Environ Health. 2020 Jul;228:113555. doi: 10.1016/j.ijheh.2020.113555. Epub 2020 May 11.
3
Restructured society and environment: A review on potential technological strategies to control the COVID-19 pandemic.
Sci Total Environ. 2020 Jul 10;725:138858. doi: 10.1016/j.scitotenv.2020.138858. Epub 2020 Apr 23.
5
An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China.
Science. 2020 May 8;368(6491):638-642. doi: 10.1126/science.abb6105. Epub 2020 Mar 31.
6
Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2).
Science. 2020 May 1;368(6490):489-493. doi: 10.1126/science.abb3221. Epub 2020 Mar 16.
7
Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19).
Int J Infect Dis. 2020 May;94:154-155. doi: 10.1016/j.ijid.2020.03.020. Epub 2020 Mar 14.
8
Early dynamics of transmission and control of COVID-19: a mathematical modelling study.
Lancet Infect Dis. 2020 May;20(5):553-558. doi: 10.1016/S1473-3099(20)30144-4. Epub 2020 Mar 11.
9
Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China.
Sci China Life Sci. 2020 May;63(5):706-711. doi: 10.1007/s11427-020-1661-4. Epub 2020 Mar 4.
10
The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak.
Science. 2020 Apr 24;368(6489):395-400. doi: 10.1126/science.aba9757. Epub 2020 Mar 6.

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