%0 Journal Article
%@ 2369-2960
%I JMIR Publications
%V 7
%N 6
%P e28265
%T Correlation of Population SARS-CoV-2 Cycle Threshold Values to Local Disease Dynamics: Exploratory Observational Study
%A Tso,Chak Foon
%A Garikipati,Anurag
%A Green-Saxena,Abigail
%A Mao,Qingqing
%A Das,Ritankar
%+ Dascena, Inc, 12333 Sowden Rd, Ste B, Private Mailbox 65148, Houston, TX, 77080-2059, United States, 1 826 9508, qmao@dascena.com
%K reverse transcription polymerase chain reaction
%K testing
%K cycle threshold
%K COVID-19
%K epidemiology
%K Rt
%K exploratory
%K correlation
%K population
%K threshold
%K disease dynamic
%K distribution
%K transmission
%D 2021
%7 3.6.2021
%9 Original Paper
%J JMIR Public Health Surveill
%G English
%X 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. 
%M 33999831
%R 10.2196/28265
%U https://publichealth.jmir.org/2021/6/e28265
%U https://doi.org/10.2196/28265
%U http://www.ncbi.nlm.nih.gov/pubmed/33999831