Viral Diseases Branch, Walter Reed Army Institute of Research, MD, USA.
Division of Vector-Borne Diseases, Centers for Disease Control & Prevention, San Juan, Puerto Rico, USA.
Epidemics. 2020 Dec;33:100400. doi: 10.1016/j.epidem.2020.100400. Epub 2020 Jul 9.
High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications.
We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors.
A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies.
This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health.
高质量的疫情预测对于支持应对地方、区域和全球传染病威胁至关重要。其他生物医学研究领域使用共识报告指南，以确保研究人员之间的研究实践标准化和高质量，并为最终用户提供解释研究结果有效性的框架。本研究旨在确定是否存在专门针对疫情预测出版物的指南。
我们进行了一项正式的系统评价，以确定和评估任何已发表的传染病疫情预测报告指南。该审查利用了来自美国政府和学术界的 18 名调查人员组成的团队。
截至 2019 年 5 月 26 日，通过文献数据库搜索（MEDLINE n=584，EMBASE n=883）确定了 1467 篇出版物，通过灰色文献审查又确定了 407 篇出版物，总共确定了 1777 篇独特的出版物。经过两位审查员系统筛选出 25 篇可能符合条件的出版物，其中有 2 篇最终被认为符合条件。对这两项已发表的报告指南进行定性审查表明，这两项指南都不是专门针对疫情预测的，尽管它们描述了可能与疫情预测研究相关的报告项目。
这项系统评价证实，尚无专门的指南来规范疫情预测研究的报告。这些发现强调需要制定此类报告指南，以提高疫情预测研究在公共卫生实践中的透明度、质量和实施。
