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模拟综合干预措施对埃博拉病毒传播的影响。

Modeling the effect of comprehensive interventions on Ebola virus transmission.

作者信息

Shen Mingwang, Xiao Yanni, Rong Libin

机构信息

School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China.

Department of Mathematics and Statistics, Oakland University, Rochester, Michigan 48309, USA.

出版信息

Sci Rep. 2015 Oct 30;5:15818. doi: 10.1038/srep15818.

DOI:10.1038/srep15818
PMID:26515898
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4626779/
Abstract

Since the re-emergence of Ebola in West Africa in 2014, comprehensive and stringent interventions have been implemented to decelerate the spread of the disease. The effectiveness of interventions still remains unclear. In this paper, we develop an epidemiological model that includes various controlling measures to systematically evaluate their effects on the disease transmission dynamics. By fitting the model to reported cumulative cases and deaths in Guinea, Sierra Leone and Liberia until March 22, 2015, we estimate the basic reproduction number in these countries as 1.2552, 1.6093 and 1.7994, respectively. Model analysis shows that there exists a threshold of the effectiveness of isolation, below which increasing the fraction of latent individuals diagnosed prior to symptoms onset or shortening the duration between symptoms onset and isolation may lead to more Ebola infection. This challenges an existing view. Media coverage plays a substantial role in reducing the final epidemic size. The response to reported cumulative infected cases and deaths may have a different effect on the epidemic spread in different countries. Among all the interventions, we find that shortening the duration between death and burial and improving the effectiveness of isolation are two effective interventions for controlling the outbreak of Ebola virus infection.

摘要

自2014年埃博拉病毒在西非再次出现以来,已实施了全面而严格的干预措施以减缓该疾病的传播。干预措施的有效性仍不明确。在本文中,我们建立了一个包含各种控制措施的流行病学模型,以系统评估它们对疾病传播动态的影响。通过将该模型拟合到几内亚、塞拉利昂和利比里亚截至2015年3月22日报告的累计病例和死亡人数,我们估计这些国家的基本繁殖数分别为1.2552、1.6093和1.7994。模型分析表明,隔离有效性存在一个阈值,低于该阈值时,增加在症状出现前被诊断出的潜伏个体比例或缩短症状出现与隔离之间的持续时间可能会导致更多埃博拉感染。这对现有观点提出了挑战。媒体报道在减少最终疫情规模方面发挥着重要作用。对报告的累计感染病例和死亡人数的反应可能在不同国家对疫情传播产生不同影响。在所有干预措施中,我们发现缩短死亡与埋葬之间的持续时间以及提高隔离有效性是控制埃博拉病毒感染爆发的两项有效干预措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/e23d5a0aed7b/srep15818-f11.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/bf8bbb338008/srep15818-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/2bef6202596a/srep15818-f10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/e23d5a0aed7b/srep15818-f11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/5e8492542390/srep15818-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/b812510c160e/srep15818-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/6406a38cf8b6/srep15818-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/c790ad8f0355/srep15818-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/bf8bbb338008/srep15818-f9.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/331d/4626779/e23d5a0aed7b/srep15818-f11.jpg

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