@Article{info:doi/10.2196/28265,
author="Tso, Chak Foon
and Garikipati, Anurag
and Green-Saxena, Abigail
and Mao, Qingqing
and Das, Ritankar",
title="Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study",
journal="JMIR Public Health Surveill",
year="2021",
month="Jun",
day="3",
volume="7",
number="6",
pages="e28265",
keywords="reverse transcription polymerase chain reaction; testing; cycle threshold; COVID-19; epidemiology; Rt; exploratory; correlation; population; threshold; disease dynamic; distribution; transmission",
abstract="Background: Despite the limitations in the use of cycle threshold (CT) values for individual patient care, population distributions of CT values may be useful indicators of local outbreaks. Objective: We aimed to conduct an exploratory analysis of potential correlations between the population distribution of cycle threshold (CT) values and COVID-19 dynamics, which were operationalized as percent positivity, transmission rate (Rt), and COVID-19 hospitalization count. Methods: In total, 148,410 specimens collected between September 15, 2020, and January 11, 2021, from the greater El Paso area were processed in the Dascena COVID-19 Laboratory. The daily median CT value, daily Rt, daily count of COVID-19 hospitalizations, daily change in percent positivity, and rolling averages of these features were plotted over time. Two-way scatterplots and linear regression were used to evaluate possible associations between daily median CT values and outbreak measures. Cross-correlation plots were used to determine whether a time delay existed between changes in daily median CT values and measures of community disease dynamics. Results: Daily median CT values negatively correlated with the daily Rt values (P<.001), the daily COVID-19 hospitalization counts (with a 33-day time delay; P<.001), and the daily changes in percent positivity among testing samples (P<.001). Despite visual trends suggesting time delays in the plots for median CT values and outbreak measures, a statistically significant delay was only detected between changes in median CT values and COVID-19 hospitalization counts (P<.001). Conclusions: This study adds to the literature by analyzing samples collected from an entire geographical area and contextualizing the results with other research investigating population CT values. ",
issn="2369-2960",
doi="10.2196/28265",
url="https://publichealth.jmir.org/2021/6/e28265",
url="https://doi.org/10.2196/28265",
url="http://www.ncbi.nlm.nih.gov/pubmed/33999831"
}