PDF(Sci-hub)
Abstract：
The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers.
We viewed \"infectious disease*\" and \"prediction\" or \"forecasting\" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis.
1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases.
Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.
We viewed \"infectious disease*\" and \"prediction\" or \"forecasting\" as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis.
1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases.
Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses.
摘要：
传染病的爆发对公众健康和经济都有负面影响。对传染病的预测可以有效控制大规模暴发疫情,减少疫情的传播,对严重公共卫生事件做出快速反应。因此,专家和学者越来越关注传染病的预测。然而,使用严格的文献计量学工具对有关传染病预测的文献进行知识图谱分析，它们应该提供进一步的知识结构和分布，很少进行。因此,我们对传染病预测进行了文献计量分析，以客观地分析现状和研究热点，以期为相关研究人员提供参考。
从成立到2020年5月1日，我们将“传染病*”和“预测”或“预测”视为WebofScience核心集合中的搜索主题。我们使用了两种有效的文献计量工具，即，CiteSpace（德雷克塞尔大学，费城,PA,美国)和VOSviewer(莱顿大学，莱顿,荷兰）根据相关出版物对传染病领域的预测数据进行客观分析，可以从WebofScience的核心集合下载。然后，确定了传染病预测的主要出版物，以基于合作分析来检测历史进展，共引分析,和共现分析。
在这项研究中，从WebofScience中提取了1880篇符合纳入标准的文献。文件数量呈现增长趋势,可以表示，越来越多的专家学者逐年关注该领域。这些出版物发表在427种不同的期刊上，有11种不同的文件类型，最常研究的类型是第1618条(83%)。此外,作为生产力最高的国家，美国在传染病领域提供了大量的科研成果。
我们的研究提供了该领域的系统和客观的观点，这对于读者评估涉及传染病预测的出版物的特征以及决策者及时采取科学对策是有用的。
从成立到2020年5月1日，我们将“传染病*”和“预测”或“预测”视为WebofScience核心集合中的搜索主题。我们使用了两种有效的文献计量工具，即，CiteSpace（德雷克塞尔大学，费城,PA,美国)和VOSviewer(莱顿大学，莱顿,荷兰）根据相关出版物对传染病领域的预测数据进行客观分析，可以从WebofScience的核心集合下载。然后，确定了传染病预测的主要出版物，以基于合作分析来检测历史进展，共引分析,和共现分析。
在这项研究中，从WebofScience中提取了1880篇符合纳入标准的文献。文件数量呈现增长趋势,可以表示，越来越多的专家学者逐年关注该领域。这些出版物发表在427种不同的期刊上，有11种不同的文件类型，最常研究的类型是第1618条(83%)。此外,作为生产力最高的国家，美国在传染病领域提供了大量的科研成果。
我们的研究提供了该领域的系统和客观的观点，这对于读者评估涉及传染病预测的出版物的特征以及决策者及时采取科学对策是有用的。
