loading page

Utilization of laboratory-based COVID-19 test results
  • +5
  • Jungeun Park,
  • Sung-Il Cho,
  • Sang-Gu Kang,
  • Jee-Woun Kim,
  • Sunkyung Jung,
  • Sun-Hwa Lee,
  • Kyou-Sup Han,
  • Seung-Sik Hwang
Jungeun Park
Seoul National University Graduate School of Public Health
Author Profile
Sung-Il Cho
Seoul National University Graduate School of Public Health
Author Profile
Sang-Gu Kang
Seoul National University Graduate School of Public Health
Author Profile
Jee-Woun Kim
Seoul National University Graduate School of Public Health
Author Profile
Sunkyung Jung
Seegene Medical Foundation
Author Profile
Sun-Hwa Lee
Seegene Medical Foundation
Author Profile
Kyou-Sup Han
Seegene Medical Foundation
Author Profile
Seung-Sik Hwang
Seoul National University Graduate School of Public Health

Corresponding Author:[email protected]

Author Profile

Abstract

During the coronavirus disease 2019 (COVID-19) pandemic, COVID-19 testing is crucial, as it enables early detection and halting the spread of infection throughout the community. Real-time reverse-transcriptase polymerase chain reaction (Real-time RT-PCR) testing is the predominant method for COVID-19 testing, and the cycle threshold value (Ct value) is used to determine COVID-19 positivity. There are many ongoing studies using Ct value, and the present study aims to examine time series distribution during the pandemic using Ct values at the national level and analyze the association with time-varying reproduction number (Rt) to discuss the utilization of laboratory-based COVID-19 test results. We used Real-time RT-PC results collected by Seegene Medical Foundation from the index case in Korea in February 2020 to January 2022 in Korea. The distribution of daily Ct value ( RdRp/S target) was examined, and it was compared with the daily count of newly diagnosed cases and Rt to determine the usability of Ct values. Moreover, time lag was applied to the daily count of newly diagnosed cases to analyze the association between Ct values and Rt. During the COVID-19 pandemic, Ct values declined in general, while viral load increased progressively. After Ct values dropped markedly, the number of newly diagnosed cases rose substantially, and the association analysis also confirmed that the daily count of newly diagnosed cases declined with increasing Ct values. The time series trend of the Ct values was also similar to that of Rt, a classic marker used as a predictor of the trends of the pandemic, and when compared to the actual count of newly diagnosed cases, Ct values can be used to predict new diagnoses earlier than Rt. The fact that the Ct values were more sensitive to a substantial rise of new COVID-19 cases than Rt was in the early days of the pandemic also support this. We examined the potential of Ct values as a predictor of new COVID-19 cases in real-time using nationally collected Ct value data. Further, we proposed the use of Ct values as an index reflecting the degree of viral load, so the findings of this study can be used as valuable evidence to support public health decisions for response and resource distribution.