Utilization of laboratory-based COVID-19 test results Article Swipe
Jungeun Park
,
Sung‐Il Cho
,
Sang-Gu Kang
,
Jee-Woun Kim
,
Sunkyung Jung
,
Sun Hwa Lee
,
Kyou Sup Han
,
Seung-Sik Hwang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22541/au.167775127.73887939/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22541/au.167775127.73887939/v1
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.
Related Topics
Concepts
Coronavirus disease 2019 (COVID-19)
Pandemic
Medicine
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Statistics
Internal medicine
Disease
Mathematics
Infectious disease (medical specialty)
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.22541/au.167775127.73887939/v1
- https://www.authorea.com/doi/pdf/10.22541/au.167775127.73887939
- OA Status
- gold
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4322770219
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4322770219Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.22541/au.167775127.73887939/v1Digital Object Identifier
- Title
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Utilization of laboratory-based COVID-19 test resultsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-03-02Full publication date if available
- Authors
-
Jungeun Park, Sung‐Il Cho, Sang-Gu Kang, Jee-Woun Kim, Sunkyung Jung, Sun Hwa Lee, Kyou Sup Han, Seung-Sik HwangList of authors in order
- Landing page
-
https://doi.org/10.22541/au.167775127.73887939/v1Publisher landing page
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https://www.authorea.com/doi/pdf/10.22541/au.167775127.73887939Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://www.authorea.com/doi/pdf/10.22541/au.167775127.73887939Direct OA link when available
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Coronavirus disease 2019 (COVID-19), Pandemic, Medicine, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Statistics, Internal medicine, Disease, Mathematics, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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17Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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