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预测 2014 年西非埃博拉疫情爆发

Forecasting the 2014 West African Ebola Outbreak.

出版信息

Epidemiol Rev. 2019 Jan 31;41(1):34-50. doi: 10.1093/epirev/mxz013.

Abstract

In 2014-2015, a large Ebola outbreak afflicted Liberia, Guinea, and Sierra Leone. We performed a systematic review of 26 manuscripts, published between 2014 and April 2015, that forecasted the West African Ebola outbreak while it was occurring, and we derived implications for how results could be interpreted by policymakers. Forecasted case counts varied widely. An important determinant of forecast accuracy for case counts was how far into the future predictions were made. Generally, forecasts for less than 2 months into the future tended to be more accurate than those made for more than 10 weeks into the future. The exceptions were parsimonious statistical models in which the decay of the rate of spread of the pathogen among susceptible individuals was dealt with explicitly. The most important lessons for policymakers regarding future outbreaks, when using similar modeling results, are: 1) uncertainty of forecasts will be greater in the beginning of the outbreak; 2) when data are limited, forecasts produced by models designed to inform specific decisions should be used complementarily for robust decision-making (e.g., 2 statistical models produced the most reliable case-counts forecasts for the studied Ebola outbreak but did not enable understanding of interventions' impact, whereas several compartmental models could estimate interventions' impact but required unavailable data); and 3) timely collection of essential data is necessary for optimal model use.

摘要

2014 年至 2015 年,一场大规模埃博拉疫情袭击了利比里亚、几内亚和塞拉利昂。我们对 26 篇于 2014 年至 2015 年 4 月间发表的、针对疫情爆发时进行预测的文献进行了系统性回顾,从中得出了一些关于预测结果如何为政策制定者提供参考的结论。预测的病例数量差异很大。预测病例数量准确性的一个重要决定因素是预测未来的时间长度。一般来说,对未来 2 个月内的预测往往比对未来 10 周以上的预测更准确。但也有例外,例如那些对病原体在易感人群中的传播速度衰减进行了明确处理的简单统计模型。对于未来疫情爆发时的政策制定者来说,最重要的经验教训是:1)在疫情开始时,预测的不确定性将会更大;2)当数据有限时,为特定决策提供信息的模型所产生的预测应互补使用,以做出稳健的决策(例如,在研究的埃博拉疫情中,2 个统计模型提供了最可靠的病例数量预测,但无法了解干预措施的影响,而几个房室模型可以估计干预措施的影响,但需要使用不可用的数据);3)及时收集必要的数据对于最优模型的使用是必要的。

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