A systematic literature review of time series methods applied to epidemic prediction

Q1 Medicine
Apollinaire Batoure Bamana , Mahdi Shafiee Kamalabad , Daniel L. Oberski
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引用次数: 0

Abstract

While time series are extensively utilized in economics, finance and meteorology, their application in epidemics has been comparatively limited. To facilitate a comprehensive research endeavor on this matter, we deemed it necessary to commence with a systematic literature review (SLR). This Systematic Literature Review aims to assess, based on a sample of relevant papers, the use of Time Series Methods (TSM) in epidemic prediction, with a special focus on African issues and the impact of COVID-19. The SLR was conducted using databases such as ACM, IEEE, PubMed and Science Direct. Open access published papers in English, in a pear reviewed Journals, from 2014 to 2023, containing keywords such as Time Series, Epidemic and Prediction were selected. The findings were summarized in an adapted PRISMA flow diagram. We end up with a sample of 36 papers. As conclusion, TSM are not so used in epidemic prediction as in some other domains, even though epidemic data are collected as time series. Just very few works address African issues regarding diseases and countries. COVID-19 is the pandemic that revealed and enhanced the used of TSM to forecast epidemics. This work paves ways for R&D on epidemiology, based on TSM.

关于应用于流行病预测的时间序列方法的系统文献综述
时间序列在经济学、金融学和气象学中得到广泛应用,但在流行病学中的应用却相对有限。为了促进对这一问题的全面研究,我们认为有必要从系统文献综述(SLR)开始。本系统文献综述旨在根据相关论文的样本,评估时间序列方法(TSM)在流行病预测中的应用,特别关注非洲问题和 COVID-19 的影响。SLR 使用 ACM、IEEE、PubMed 和 Science Direct 等数据库进行。选取了 2014 年至 2023 年期间在经梨审查的期刊上发表的公开获取英文论文,其中包含时间序列、流行病和预测等关键词。研究结果汇总在改编的 PRISMA 流程图中。我们最终获得了 36 篇论文样本。结论是,尽管流行病数据是以时间序列的形式收集的,但在流行病预测中,时间序列模型的应用并不像在其他领域那样广泛。只有极少数作品涉及非洲的疾病和国家问题。COVID-19 大流行揭示并加强了 TSM 在流行病预测中的应用。这项工作为基于 TSM 的流行病学研发铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Informatics in Medicine Unlocked
Informatics in Medicine Unlocked Medicine-Health Informatics
CiteScore
9.50
自引率
0.00%
发文量
282
审稿时长
39 days
期刊介绍: Informatics in Medicine Unlocked (IMU) is an international gold open access journal covering a broad spectrum of topics within medical informatics, including (but not limited to) papers focusing on imaging, pathology, teledermatology, public health, ophthalmological, nursing and translational medicine informatics. The full papers that are published in the journal are accessible to all who visit the website.
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