SARS-CoV-2 cycle threshold (Ct) values predict future COVID-19 cases

Systematic Review on the Correlation Between SARS-CoV-2 Real-Time PCR Cycle Threshold Values and Epidemiological Trends

“…[ 17 ] Hospital 342 Abbott M2000 SARS-CoV-2 assay, Abbott Park, IL, USA N, RdRp Nasopharyngeal NR NR Epidemiological trends and anticipating the next phase of the pandemic using median weekly incident hospitalizations due to SARS-CoV-2 infection in Massachusetts, obtained from the Massachusetts Department of Public Health NR NR No predictive modeling used in this study A strong inverse correlation (Pearson's correlation r = −0.76 ( P < 0.05)) was observed between the median Ct value and median weekly incident hospitalizations due to SARS-CoV-2 infection in Massachusetts, obtained from the Massachusetts Department of Public Health Phillips et al. [ 13 ] Hospital 2114 Lowest Ct value associated > 0 for E and N2 region for Xpert Xpress SARSCoV-2 assay OR a single Ct value that corresponds to the lowest Ct value > 0 for the Xpert Xpress SARS-CoV-2/Flu/RSV assay Xpert Xpress SARS-CoV-2 Assay, Cepheid, Sunnyvale CA, USA Xpert Xpress SARS-CoV-2/Flu/RSV assay, Cepheid, Sunnyvale CA, USA Both run on Infinity and XVI systems E, N2 Nasopharyngeal or anterior nasal NR NR Future changes in institutional COVID-19 cases NR 2 weeks When compared temporally, the average weekly Ct values for all tests performed negatively correlated with the number of cases occurring 2 weeks after specimen collection (Pearson’s correlation r = –0.75, P < 0.0001) Predictive modeling using Ct values from the epidemic surge October 2020–March 2021 correctly predicted whether cases would increase or decrease 65% of the time for a subsequent surge (May–July 2021) Stevens et al. [ 23 ] Hospital and public ~ 26,388 Five testing platforms used: BD Max; Liat, Roche Diagnostics; Cobas, Roche Diagnostics; GeneSig, Primerdesign; Seegene, Korea E, M, N, N1, N2, ORF1a ORF1a and N gene RdRp and N gene NR NR Omicron strain (B.1.1.529) and Omicron BA.2 sub-variant Community prevalence …”

“…[ 17 ] 2022 USA To examine the association between Ct values from patients in a tertiary care ER department with the weekly state hospitalizations to evaluate the utility of using Ct values to estimate epidemiological trends and anticipate the next phase of the pandemic Retrospective Single unit Local There was a significant inverse correlation between median weekly Ct values and weekly incident hospitalizations for SARS-CoV-2 infections in Massachusetts Phillips et al. [ 13 ] 2022 USA To determine if temporal trends in SARS-CoV-2 Ct values from clinical testing were predictive of future cases to aid hospital-level surge planning Prospective Single unit Single unit Temporal trends in SARS-CoV-2 Ct values were predictive of future admission case numbers of COVID-19 at a specific hospital Stevens et al. [ 23 ] 2022 Australia Analyzing SARS-CoV-2 real-time PCR test Ct values across a population to determine the usefulness in assisting public health efforts and adding refinement to epidemiological models Observational Local Local Ct values across a population demonstrated potential to predict community transmission, owing to the increased proportion of high Ct values as case numbers declined and the increased proportion of low Ct values as the case numbers increased in the community Tso et al.…”

“…The studies were conducted in the USA [ 2 , 13 – 17 ], Europe [ 18 – 21 ], Africa [ 22 ], Australia [ 23 ], China [ 24 ], India [ 25 ], the Kingdom of Bahrain [ 3 ], and Lebanon [ 26 ]. RT–PCR Ct values were measured from public samples only (national or local), or from hospital and public samples in ten studies [ 3 , 14 , 18 – 25 ], and from hospital only or hospital and care home samples only in six studies [ 2 , 13 , 15 – 17 , 26 ]. Eleven studies included nasopharyngeal swabs [ 2 , 3 , 13 – 18 , 20 – 22 ], one study used nose and throat swabs [ 19 ], and four studies did not record the sample type [ 23 – 26 ].…”

Temporal Series Analysis of Population Cycle Threshold Counts as a Predictor of Surge in Cases and Hospitalizations during the SARS-CoV-2 Pandemic

“…A good number of previous studies have shown that CT values, either taken at a given time or analyzing its temporal evolution, may help predict the posterior occurrence of new incident cases or hospitalizations caused by the SARS-CoV-2 infection [ 11 , 17 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ]. To our knowledge, this is the first study to investigate the utility of measuring CT values to predict the evolution of the pandemic using the Granger causality approach, i.e., an analysis of temporal series.…”

Using Genome Sequence Data to Predict SARS-CoV-2 Detection Cycle Threshold Values

“…For example, Ct values for cross-sectional samples collected from patient populations over a given time period are often indicative of the state of the epidemic, with lower average Ct values indicating a growing pandemic (12)(13)(14). Similar studies have also found that crosssectional trends in Ct values can act as indicators of the future trajectory of the pandemic (15,16). At the patient level, Ct values have been shown to provide a good estimate of how long a patient will remain contagious (10,17,18), and several studies have shown that lower Ct values (i.e., higher viral loads) can be correlated with symptomatic infection, morbidity, and mortality (9,14,19,20).…”