The World Health Organization added Disease X to their shortlist of blueprint priority diseases to represent a hypothetical, unknown pathogen that could cause a future epidemic. During different virus outbreaks of the past, such as COVID-19, Influenza, Lyme Disease, and Zika virus, researchers from various disciplines utilized Google Trends to mine multimodal components of web behavior to study, investigate, and analyze the global awareness, preparedness, and response associated with these respective virus outbreaks. As the world prepares for Disease X, a dataset on web behavior related to Disease X would be crucial to contribute towards the timely advancement of research in this field. Furthermore, none of the prior works in this field have focused on the development of a dataset to compile relevant web behavior data, which would help to prepare for Disease X. To address these research challenges, this work presents a dataset of web behavior related to Disease X, which emerged from different geographic regions of the world, between February 2018 and August 2023. Specifically, this dataset presents the search interests related to Disease X from 94 geographic regions. The dataset was developed by collecting data using Google Trends. The relevant search interests for all these regions for each month in this time range are available in this dataset. This paper also discusses the compliance of this dataset with the FAIR principles of scientific data management. Finally, an analysis of this dataset is presented to uphold the applicability, relevance, and usefulness of this dataset for the investigation of different research questions in the interrelated fields of Big Data, Data Mining, Healthcare, Epidemiology, and Data Analysis with a specific focus on Disease X.

翻译：世界卫生组织将“X疾病”列入其蓝图重点疾病候选名单，以代表一种可能导致未来大流行的假想未知病原体。在过去的疫情暴发中，例如COVID-19、流感、莱姆病和寨卡病毒，来自不同学科的研究人员利用Google Trends挖掘网络行为的多模态成分，以研究、调查和分析与这些病毒暴发相关的全球意识、准备和应对。随着世界为X疾病做准备，关于X疾病网络行为的数据集对于推动该领域的及时研究至关重要。此外，该领域的前期工作均未关注开发用于汇编相关网络行为数据的数据集，而这将有助于为X疾病做准备。为解决这些研究挑战，本研究提出了一个与X疾病相关的网络行为数据集，该数据来源于2018年2月至2023年8月间世界不同地理区域。具体而言，该数据集呈现了来自94个地理区域的X疾病相关搜索兴趣。该数据集通过使用Google Trends收集数据而构建。数据集中包含了这段时间内所有区域每月的相关搜索兴趣。本文还讨论了该数据集对科学数据管理FAIR原则的遵循情况。最后，对该数据集进行了分析，以证明其在关注X疾病的大数据、数据挖掘、医疗健康、流行病学和数据分析等相互关联领域中用于研究不同研究问题的适用性、相关性和有用性。