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Analysis of inflammatory parameters and disease severity for 88 hospitalized COVID-19 patients in Wuhan, China.分析 88 例在中国武汉住院的 COVID-19 患者的炎症参数和疾病严重程度。
Int J Med Sci. 2020 Jul 25;17(13):2052-2062. doi: 10.7150/ijms.47935. eCollection 2020.
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Coronavirus Disease 2019 in Children - United States, February 12-April 2, 2020.2019 年冠状病毒病在儿童中的情况-美国,2020 年 2 月 12 日至 4 月 2 日。
MMWR Morb Mortal Wkly Rep. 2020 Apr 10;69(14):422-426. doi: 10.15585/mmwr.mm6914e4.
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The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application.新型冠状病毒肺炎(COVID-19)的潜伏期来自公开报告的确诊病例:估计和应用。
Ann Intern Med. 2020 May 5;172(9):577-582. doi: 10.7326/M20-0504. Epub 2020 Mar 10.
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COVID-19 control in China during mass population movements at New Year.新年期间中国大规模人口流动情况下的新冠疫情防控
Lancet. 2020 Mar 7;395(10226):764-766. doi: 10.1016/S0140-6736(20)30421-9. Epub 2020 Feb 24.
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Using the negative binomial distribution to model overdispersion in ecological count data.使用负二项分布模型来对生态学计数数据中的过离散进行建模。
Ecology. 2011 Jul;92(7):1414-21. doi: 10.1890/10-1831.1.
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Chlamydia transmission: concurrency, reproduction number, and the epidemic trajectory.衣原体传播:同时感染、繁殖数与流行轨迹。
Am J Epidemiol. 1999 Dec 15;150(12):1331-9. doi: 10.1093/oxfordjournals.aje.a009965.

中国不同干预措施下新冠病毒传播模拟的数据驱动分析。

Data-driven analysis of the simulations of the spread of COVID-19 under different interventions of China.

作者信息

Tian Ting, Zhang Jingwen, Lin Shiyun, Jiang Yukang, Tan Jianbin, Li Zhongfei, Wang Xueqin

机构信息

School of Mathematics, Sun Yat-sen University, Guangzhou, People's Republic of China.

Center for Statistical Science, Peking University, Beijing, People's Republic of China.

出版信息

J Appl Stat. 2021 Mar 9;50(11-12):2547-2560. doi: 10.1080/02664763.2021.1895089. eCollection 2023.

DOI:10.1080/02664763.2021.1895089
PMID:37529566
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10388832/
Abstract

Since February 2020, COVID-19 has spread rapidly to more than 200 countries in the world. During the pandemic, local governments in China have implemented different interventions to efficiently control the spread of the epidemic. Characterizing transmission of COVID-19 under some typical interventions is essential to help countries develop appropriate interventions. Based on the pre-symptomatic transmission patterns of COVID-19, we established a novel compartmental model: Susceptible-Infectious-Confirmed-Removed (SICR) model, which allowed the effective reproduction number to change over time, thus the effects of policies could be reasonably estimated. Using the epidemic data of Wuhan, Wenzhou, and Shenzhen, we migrated the corresponding estimated policy modes to South Korea, Italy, and the United States and simulated the potential outcomes for these countries when they adopted similar policy strategies to China. We found that the mild interventions implemented in Shenzhen were effective in controlling the epidemic in the early stage, while more stringent policies which were implemented in Wuhan and Wenzhou were necessary if the epidemic became severe and needed to be controlled in a short time.

摘要

自2020年2月以来,新冠病毒已迅速传播至全球200多个国家。疫情期间,中国地方政府实施了不同的干预措施以有效控制疫情传播。明确新冠病毒在一些典型干预措施下的传播特征,对于帮助各国制定适当的干预措施至关重要。基于新冠病毒的症状前传播模式,我们建立了一个新的 compartmental 模型:易感-感染-确诊-康复(SICR)模型,该模型允许有效繁殖数随时间变化,从而能够合理估计政策的效果。利用武汉、温州和深圳的疫情数据,我们将相应的估计政策模式迁移至韩国、意大利和美国,并模拟了这些国家采取与中国类似政策策略时的潜在结果。我们发现,深圳实施的轻度干预措施在疫情早期对控制疫情有效,而武汉和温州实施的更严格政策在疫情变得严重且需要在短时间内控制时是必要的。