摘要
科学识别和解释不同COVID-19数据间一致性和周期性特征是准确了解COVID-19流行规律与制定防控措施的基础.本研究通过系统检索和梳理相关研究文献发现:(1)现有一致性研究集中于WHO、约翰霍普金斯大学等机构发布的全球COVID-19疫情数据,而且不同数据来源在数据收集、统计指标与数据共享、同一指标数值等方面不尽相同;(2)COVID-19疫情数据存在明显的周期性,现有的相关研究集中在发达国家,不同国家与地区间的疫情周期长短存在较大差异,有3.5 d、5.0 d、7.0 d和62.0 d等不同模式.关于周期性产生原因目前有样本检测和数据报告、生物学因素、社会因素、环境因素多种解释.综合来看,当前缺乏不同COVID-19数据来源间一致性的定量研究,暂未有研究评估数据一致性在不同时间和不同国家间的差异,也缺乏研究探讨全球不同国家的COVID-19疫情周期性差异.
Abstract
Using rigorous methods to identify and interpret the consistency and periodicity of multi-source COVID-19 epidemic data is the basis of properly interpreting the epidemic characteristics of the COVID-19 epidemic and developing prevention and control measures.By conducting a systematic review,we found that:(1)the existing literature on consistency studies mainly focused on global COVID-19 epidemic data released by the WHO and Johns Hopkins University,revealing inconsistent across various aspects of data collection,statistical indicators,data sharing,as well as the value of the same indicators;(2)each kind COVID-19 epidemic data had typical periodicity.Existing studies about periodicity of COVID-19 epidemic data were primarily from developed countries.The length of epidemic periodicity varied greatly across countries and regions,with a varying periodicity of 3.5 days,5.0 days,7.0 days,and 62.0 days.Researchers linked the periodicity of COVID-19 epidemic to multiple factors,including sample testing,data reporting,biological,social,and environmental factors.To summarize,there were no studies that quantified the consistency across major COVID-19 data sources,examined differences in data consistency over time and across countries,and explored the periodicity variations of COVID-19 epidemic across countries around the world currently.
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万方数据