Association of SARS-CoV-2 viral load distributions with individual demographics and suspected variant type: results from the Liverpool community testing pilot, England, 6 November 2020 to 8 September 2021

Abstract

Background The PCR quantification cycle (Cq) is a proxy measure of the viral load of a SARS-CoV-2-infected individual. Aim To investigate if Cq values vary according to different population characteristics, in particular demographic ones, and within the COVID-19 pandemic context, notably the SARS-CoV-2 type/variant individuals get infected with. Methods We considered all positive PCR results from Cheshire and Merseyside, England, between 6 November 2020 and 8 September 2021. Cq distributions were inspected with Kernel density estimates. Multivariable quantile regression models assessed associations between people’s features and Cq. Results We report Cq values for 188,821 SARS-CoV-2 positive individuals. Median Cqs increased with decreasing age for suspected wild-type virus and Alpha variant infections, but less so, if not, for Delta. For example, compared to 30–39-year-olds (median age group), 5–11-year-olds exhibited 1.8 (95% CI: 1.5 to 2.1), 2.2 (95% CI: 1.8 to 2.6) and 0.8 (95% CI: 0.6 to 0.9) higher median Cqs for suspected wild-type, Alpha and Delta positives, respectively, in multivariable analysis. 12–18-year-olds also had higher Cqs for wild-type and Alpha positives, however, not for Delta. Overall, in univariable analysis, suspected Delta positives reported 2.8 lower median Cqs than wild-type positives (95% CI: 2.7 to 2.8; p < 0.001). Suspected Alpha positives had 1.5 (95% CI: 1.4 to 1.5; p < 0.001) lower median Cqs than wild type. Conclusions Wild-type- or Alpha-infected school-aged children (5–11-year-olds) might transmit less than adults (> 18 years old), but have greater mixing exposures. Smaller differences in viral loads with age occurred in suspected Delta infections. Suspected-Alpha- or Delta-infections involved higher viral loads than wild type, suggesting increased transmission risk. COVID-19 control strategies should consider age and dominant variant.