Department of Preventive Medicine, Graduate School of Public Health, Seoul National University, Seoul, Korea.
Graduate School of Public Health, Seoul National University, Seoul, Korea.
J Prev Med Public Health. 2023 Jul;56(4):377-383. doi: 10.3961/jpmph.23.056. Epub 2023 Jun 21.
Korea and Japan have managed the spread of coronavirus disease 2019 (COVID-19) using markedly different policies, referred to as the "3T" and "3C" strategies, respectively. This study examined these differences to assess the roles of active testing and contact tracing as non-pharmaceutical interventions (NPIs). We compared the proportion of unlinked cases (UCs) and test positivity rate (TPR) as indicators of tracing and testing capacities.
We outlined the evolution of NPI policies and investigated temporal trends in their correlations with UCs, confirmed cases, and TPR prior to the Omicron peak. Spearman correlation coefficients were reported between the proportion of UCs, confirmed cases, and TPR. The Fisher r-to-z transformation was employed to examine the significance of differences between correlation coefficients.
The proportion of UCs was significantly correlated with confirmed cases (r=0.995, p<0.001) and TPR (r=0.659, p<0.001) in Korea and with confirmed cases (r=0.437, p<0.001) and TPR (r=0.429, p<0.001) in Japan. The Fisher r-to-z test revealed significant differences in correlation coefficients between the proportion of UCs and confirmed cases (z=16.07, p<0.001) and between the proportion of UCs and TPR (z=2.12, p=0.034) in Korea and Japan.
Higher UCs were associated with increases in confirmed cases and TPR, indicating the importance of combining testing and contact tracing in controlling COVID-19. The implementation of stricter policies led to stronger correlations between these indicators. The proportion of UCs and TPR effectively indicated the effectiveness of NPIs. If the proportion of UCs shows an upward trend, more testing and contact tracing may be required.
韩国和日本在应对 2019 年冠状病毒病(COVID-19)的传播时采用了截然不同的政策,分别被称为“3T”和“3C”策略。本研究旨在探讨这些差异,评估主动检测和接触者追踪作为非药物干预(NPI)的作用。我们比较了未关联病例(UCs)的比例和检测阳性率(TPR),作为追踪和检测能力的指标。
我们概述了 NPI 政策的演变,并在 Omicron 高峰之前研究了它们与 UCs、确诊病例和 TPR 之间的时间趋势之间的相关性。报告了 UCs 的比例、确诊病例和 TPR 之间的 Spearman 相关系数。Fisher r-to-z 转换用于检验相关系数之间差异的显著性。
韩国 UCs 的比例与确诊病例(r=0.995,p<0.001)和 TPR(r=0.659,p<0.001)显著相关,与确诊病例(r=0.437,p<0.001)和 TPR(r=0.429,p<0.001)显著相关。Fisher r-to-z 检验显示,韩国和日本 UCs 比例与确诊病例(z=16.07,p<0.001)和 TPR(z=2.12,p=0.034)之间的相关系数存在显著差异。
较高的 UCs 与确诊病例和 TPR 的增加相关,表明在控制 COVID-19 方面,检测和接触者追踪的结合非常重要。更严格政策的实施导致这些指标之间的相关性更强。UCs 的比例和 TPR 有效表明了 NPI 的有效性。如果 UCs 的比例呈上升趋势,则可能需要更多的检测和接触者追踪。