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利用新型冠状病毒病(COVID-19)暴发与过去的 SARS 和 MERS 疫情进行比较,测试传染病探寻者(IDS)未知暴发的识别效果。

Testing the identification effectiveness of an unknown outbreak of the Infectious Diseases Seeker (IDS) using and comparing the novel coronavirus disease (COVID-19) outbreak with the past SARS and MERS epidemics.

机构信息

Department of Industrial Engineering, University of Rome "Tor Vergata", Italy.

International CBRNe Master Courses, University of Rome "Tor Vergata", Italy.

出版信息

J Infect Public Health. 2021 Jan;14(1):123-130. doi: 10.1016/j.jiph.2020.11.014. Epub 2020 Dec 9.

Abstract

BACKGROUND

The aim of this research is to assess the predictive accuracy of the Infectious Diseases Seeker (IDS) - an innovative tool for prompt identification of the causative agent of infectious diseases during outbreaks - when field epidemiological data collected from a novel outbreak of unknown origin are analysed by the tool. For this reason, it has been taken into account the novel coronavirus disease (COVID-19) outbreak, which began in China at the end of December 2019, has rapidly spread around the globe, and it has led to a public health emergency of international concern (PHEIC), declared to the 30th of January 2020 by the World Health Organization (WHO).

METHODS

The IDS takes advantage of an off-line database, built before the COVID-19 pandemic, which represents a pivotal characteristic for working without an internet connection. The software has been tested using the epidemiological data available in different and progressive stages of the COVID-19 outbreak. As a comparison, the results of the tests performed using the epidemiological data from the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) epidemic in 2002 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) epidemic in 2012, are shown.

RESULTS

The overall outcomes provided by the software are comforting, as a matter of the fact that IDS has identified with a good accuracy the SARS and MERS epidemics (over 90%), while, as expected, it has not provided erroneous and equivocal readings after the elaboration COVID-19 epidemic data.

CONCLUSIONS

Even though IDS has not recognized the COVID-19 epidemic, it has not given to the end user a false result and wrong interpretation, as expected by the developers. For this reason, IDS reveals itself as useful software to identify a possible epidemic or outbreak. Thus, the intention of developers is to plan, once the software will be released, dedicated updates and upgrades of the database (e.g., SARS-CoV-2) in order to keep this tool increasingly useful and applicable to reality.

摘要

背景

本研究旨在评估传染病搜索者(IDS)的预测准确性,IDS 是一种创新工具,可在暴发期间快速识别传染病的病原体。为此,我们考虑了一种新型不明来源暴发的情况,即 2019 年 12 月底在中国开始的新型冠状病毒病(COVID-19)暴发,该疾病迅速在全球范围内传播,并导致世界卫生组织(WHO)于 2020 年 1 月 30 日宣布的国际关注的突发公共卫生事件(PHEIC)。

方法

IDS 利用在 COVID-19 大流行之前建立的离线数据库,这是其无需连接互联网即可工作的关键特征。该软件已使用 COVID-19 暴发的不同和逐步阶段的可用流行病学数据进行了测试。作为比较,还展示了使用 2002 年严重急性呼吸综合征冠状病毒(SARS-CoV)流行和 2012 年中东呼吸综合征冠状病毒(MERS-CoV)流行的流行病学数据进行的测试结果。

结果

软件提供的总体结果令人欣慰,因为事实上 IDS 已经非常准确地识别了 SARS 和 MERS 流行(超过 90%),而正如预期的那样,在处理 COVID-19 流行数据后,它没有提供错误和模棱两可的结果。

结论

即使 IDS 尚未识别出 COVID-19 流行,它也没有像开发人员预期的那样向最终用户提供错误的结果和错误的解释。因此,IDS 证明是一种有用的软件,可以识别可能的流行或暴发。因此,开发人员的意图是计划一旦发布该软件,就对数据库(例如 SARS-CoV-2)进行专门的更新和升级,以使该工具更加有用并适用于现实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/21a4/7725062/a2573d842d84/gr1_lrg.jpg

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