JMIR Publications

ABSTRACT

Background:

Distribution of population-level cycle threshold (Ct) values as a proxy of viral load may be useful indicators for predicting COVID-19 dynamics.

Objective:

This study aimed to determine the relationship between the daily trend of average Ct value and the COVID-19 dynamics, and also, to determine the lag between these series.

Methods:

The samples included in this study were collected from March 21, 2021, to December 1, 2021. Daily Ct values of all patients who referred to the Molecular Diagnostic Laboratory of Iran University of Medical Sciences in Tehran, Iran for RT-PCR tests were recorded. The daily number of positive people and the number of hospitalized people by age group were extracted from the COVID-19 patient information registration system related to Tehran province, Iran. First, the ARIMA model was done to the time series of variables. Second, cross-correlation analysis was done to determine the best lag and correlation between average daily Ct value and other COVID-19 dynamics variables. Finally, the best-selected lag of Ct through cross-correlation was incorporated as covariates into the ARIMAX model to find the coefficient.

Results:

Daily average Ct values have a significant negative correlation (a 30-day time delay) with the new daily number of positive tests (P=0.015) and daily number of COVID-19 death (P=0.016). Daily average Ct value with a 30-day delay could impact the daily number of the positive test for COVID-19 (β =-16.87, 95 % CI: -28.93, -4.815), and on the daily number of death from COVID-19 (β= -1.52, 95 % CI: -2.86, -0.183). There is significant coefficient between CT lag (23 days) and the number of COVID 19 hospitalization (β =-24.12, 95 % CI: -41.08, -7.16). Despite cross-correlation analysis that suggested time delays in the average Ct values and the number of daily hospitalized patients under 5 and 5-17 years old, no statistically significant coefficient was detected.

Conclusions:

It is important for surveillance of COVID-19 disease to find a good indicator that can predict epidemic surges in the community. It seems that the average daily Ct value with a difference of 30 days delay can predict increases in the number of positive confirmed COVID-19 cases, so it may be a useful indicator for the health system.