Reporting behavior from WHO COVID-19 public data

Objective Daily COVID-19 data reported by the World Health Organization
(WHO) may provide the basis for political ad hoc decisions including
travel restrictions. Data reported by countries, however, is heterogeneous
and metrics to evaluate its quality are scarce. In this work, we analyzed
COVID-19 case counts provided by WHO and developed tools to evaluate
country-specific reporting behaviors. Methods In this retrospective
cross-sectional study, COVID-19 data reported daily to WHO from 3rd
January 2020 until 14th June 2021 were analyzed. We proposed the concepts
of binary reporting rate and relative reporting behavior and performed
descriptive analyses for all countries with these metrics. We developed a
score to evaluate the consistency of incidence and binary reporting rates.
Further, we performed spectral clustering of the binary reporting rate and
relative reporting behavior to identify salient patterns in these metrics.
Results Our final analysis included 222 countries and regions. Reporting
scores varied between -0.17, indicating discrepancies between incidence
and binary reporting rate, and 1.0 suggesting high consistency of these
two metrics. Median reporting score for all countries was 0.71 (IQR 0.55
to 0.87). Descriptive analyses of the binary reporting rate and relative
reporting behavior showed constant reporting with a slight “weekend
effect” for most countries, while spectral clustering demonstrated that
some countries had even more complex reporting patterns. Conclusion The
majority of countries reported COVID-19 cases when they did have cases to
report. The identification of a slight “weekend effect” suggests that
COVID-19 case counts reported in the middle of the week may represent the
best data basis for political ad hoc decisions. A few countries, however,
showed unusual or highly irregular reporting that might require more
careful interpretation. Our score system and cluster analyses might be
applied by epidemiologists advising policymakers to consider
country-specific reporting behaviors in political ad hoc decisions.

研究背景与目标：世界卫生组织（World Health Organization, WHO）每日发布的新冠疫情数据，可作为包括旅行限制在内的临时性政治决策的依据。然而，各国上报的新冠数据异质性较强，且用于评估其数据质量的量化指标较为匮乏。本研究针对世界卫生组织发布的新冠确诊病例数开展分析，并开发了用于评估各国上报行为的分析工具。

研究方法：本研究为回顾性横断面研究，分析了2020年1月3日至2021年6月14日期间各国每日上报给世界卫生组织的新冠疫情数据。本研究提出了二元上报率（binary reporting rate）与相对上报行为（relative reporting behavior）两个概念，并基于这两项指标对所有国家开展描述性分析；同时开发了一套评分体系，用于评估发病率与二元上报率之间的一致性。此外，本研究还针对二元上报率与相对上报行为开展谱聚类（spectral clustering）分析，以识别上述指标的显著模式。

研究结果：本研究最终纳入222个国家和地区开展分析。上报评分的取值区间为-0.17至1.0：其中-0.17代表发病率与二元上报率存在显著偏差，1.0则表示两项指标高度一致；所有国家的上报评分中位数为0.71（IQR 0.55~0.87）。针对二元上报率与相对上报行为的描述性分析显示，多数国家的上报行为整体稳定，但存在轻微的"周末效应"；而谱聚类分析结果表明，部分国家的上报模式更为复杂。

研究结论：多数国家会在实际存在新冠确诊病例时上报相关数据。本次研究发现的轻微"周末效应"提示，周中上报的新冠确诊病例数可作为临时性政治决策的最优数据基础。但仍有少数国家的上报行为存在异常或高度不规律，需对其数据进行更为谨慎的解读。本研究开发的评分体系与聚类分析方法，可为向政策制定者提供咨询的流行病学家所应用，以帮助其在制定临时性政治决策时充分考虑各国差异化的上报行为。