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通过社交媒体数据创新传染病爆发检测中的健康预防模式:证据的综合评价

Innovating health prevention models in detecting infectious disease outbreaks through social media data: an umbrella review of the evidence.

作者信息

Giancotti Monica, Lopreite Milena, Mauro Marianna, Puliga Michelangelo

机构信息

Department of Law, Economics and Social Sciences, Magna Graecia University, Catanzaro, Italy.

Department of Economics, Statistics and Finance, University of Calabria, Cosenza, Italy.

出版信息

Front Public Health. 2024 Nov 22;12:1435724. doi: 10.3389/fpubh.2024.1435724. eCollection 2024.

Abstract

INTRODUCTION AND OBJECTIVE

The number of literature reviews examining the use of social media in detecting emerging infectious diseases has recently experienced an unprecedented growth. Yet, a higher-level integration of the evidence is still lacking. This study aimed to synthesize existing systematic literature reviews published on this topic, offering an overview that can help policymakers and public health authorities to select appropriate policies and guidelines.

METHODS

We conducted an umbrella review: a review of systematic reviews published between 2011 and 2023 following the PRISMA statement guidelines. The review protocol was registered in the PROSPERO database (CRD42021254568). As part of the search strategy, three database searches were conducted, specifically in PubMed, Web of Science, and Google Scholar. The quality of the included reviews was determined using A Measurement Tool to Assess Systematic Reviews 2.

RESULTS

Synthesis included 32 systematic reviews and 3,704 primary studies that investigated how the social media listening could improve the healthcare system's efficiency in terms of a timely response to treat epidemic situations. Most of the included systematic reviews concluded showing positive outcomes when using social media data for infectious disease surveillance.

CONCLUSION

Systematic reviews showed the important role of social media in predicting and detecting disease outbreaks, potentially reducing morbidity and mortality through swift public health action. The policy interventions strongly benefit from the continued use of online data in public health surveillance systems because they can help in recognizing important patterns for disease surveillance and significantly improve the disease prediction abilities of the traditional surveillance systems.

SYSTEMATIC REVIEW REGISTRATION

http://www.crd.york.ac.uk/PROSPERO, identifier [CRD42021254568].

摘要

引言与目的

近年来,审视社交媒体在发现新发传染病方面应用的文献综述数量空前增长。然而,仍缺乏对证据的更高层次整合。本研究旨在综合已发表的关于该主题的系统性文献综述,提供一个概述,以帮助政策制定者和公共卫生当局选择合适的政策和指南。

方法

我们进行了一项伞状综述:按照PRISMA声明指南,对2011年至2023年间发表的系统性综述进行回顾。该综述方案已在PROSPERO数据库(CRD42021254568)中注册。作为检索策略的一部分,我们进行了三次数据库检索,具体是在PubMed、科学网和谷歌学术中进行。使用《系统性综述评估测量工具2》来确定纳入综述的质量。

结果

综合分析纳入了32篇系统性综述和3704项初步研究,这些研究探讨了社交媒体监测如何在及时应对疫情方面提高医疗系统的效率。大多数纳入的系统性综述得出结论,在将社交媒体数据用于传染病监测时显示出积极结果。

结论

系统性综述表明社交媒体在预测和发现疾病暴发方面具有重要作用,通过迅速的公共卫生行动有可能降低发病率和死亡率。政策干预措施因在公共卫生监测系统中持续使用在线数据而受益匪浅,因为这些数据有助于识别疾病监测的重要模式,并显著提高传统监测系统的疾病预测能力。

系统性综述注册

http://www.crd.york.ac.uk/PROSPERO,标识符[CRD42021254568]

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/714b/11621043/763a04585e4b/fpubh-12-1435724-g001.jpg

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