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埃博拉病毒病疫情中非药物干预和疫苗接种的综合分析:随机建模方法。

A comprehensive analysis of non-pharmaceutical interventions and vaccination on Ebolavirus disease outbreak: Stochastic modeling approach.

机构信息

Department of Mathematics, Konkuk University, Seoul, Korea.

Division of Infectious Disease, Hallym University College of Medicine, Seoul, Korea.

出版信息

PLoS Negl Trop Dis. 2024 Jun 7;18(6):e0011955. doi: 10.1371/journal.pntd.0011955. eCollection 2024 Jun.

DOI:10.1371/journal.pntd.0011955
PMID:38848434
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11189251/
Abstract

Ebolavirus disease (EVD) outbreaks have intermittently occurred since the first documented case in the 1970s. Due to its transmission characteristics, large outbreaks have not been observed outside Africa. However, within the continent, significant outbreaks have been attributed to factors such as endemic diseases with similar symptoms and inadequate medical infrastructure, which complicate timely diagnosis. In this study, we employed a stochastic modeling approach to analyze the spread of EVD during the early stages of an outbreak, with an emphasis on inherent risks. We developed a model that considers healthcare workers and unreported cases, and assessed the effect of non-pharmaceutical interventions (NPIs) using actual data. Our results indicate that the implementation of NPIs led to a decrease in the transmission rate and infectious period by 30% and 40% respectively, following the declaration of the outbreak. We also investigated the risks associated with delayed outbreak recognition. Our simulations suggest that, when accounting for NPIs and recognition delays, prompt detection could have resulted in a similar outbreak scale, with approximately 50% of the baseline NPIs effect. Finally, we discussed the potential effects of a vaccination strategy as a follow-up measure after the outbreak declaration. Our findings suggest that a vaccination strategy can reduce both the burden of NPIs and the scale of the outbreak.

摘要

埃博拉病毒病(EVD)自 20 世纪 70 年代首例确诊病例以来间歇性爆发。由于其传播特性,在非洲以外地区尚未观察到大规模爆发。然而,在非洲大陆内部,地方性疾病具有类似症状和医疗基础设施不足等因素导致了重大爆发,这使得及时诊断变得复杂。在本研究中,我们采用随机建模方法分析了埃博拉病毒病在疫情早期的传播情况,重点关注固有风险。我们开发了一个考虑医护人员和未报告病例的模型,并使用实际数据评估了非药物干预(NPI)的效果。结果表明,在宣布疫情后,实施 NPI 可使传播率和感染期分别降低 30%和 40%。我们还调查了延迟识别疫情带来的风险。我们的模拟结果表明,在考虑了 NPI 和识别延迟的情况下,及时发现可能会导致类似的疫情规模,约为基本 NPI 效果的 50%。最后,我们讨论了在宣布疫情后作为后续措施的接种策略的潜在影响。我们的研究结果表明,接种策略可以减轻 NPI 的负担和疫情的规模。

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Ann Med Surg (Lond). 2022 Jun 6;79:103958. doi: 10.1016/j.amsu.2022.103958. eCollection 2022 Jul.
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