Serial Cycle Threshold to Assess the Infectious Potential of SARS-CoV-2: A Systematic Review

Journal article

We sought to assess predictive factors for SARS-CoV-2 infectiousness using a meta-analytic approach. We searched LitCovid, medRxiv, Google Scholar, and the WHO COVID-19 database until June 30 2025, including studies which cultured SARS-CoV-2, relating them to clinico-epidemiologic and laboratory variables and RT-PCR cycle threshold (Ct) values. Using linear mixed effects regression models, we tested for independent associations with Ct values with 95%CIs and adjusted p-values in a multivariable model. We used a modified QUADAS criteria to assess risk-of-bias. We included 50 studies, with 39 in quantitative synthesis. The percentage of culture-positive specimens decreased with increasing Ct values (subgroup test difference Q=96.71;p<0.001) and time since the first PCR test (Q=26.95;p=0.0026).Presence of symptoms (Q=20.1;p<0.01),gene platform used (Q=14.89;p=0.002),being a cancer patient (Q=24.9;p<0.0001)and vaccination status (Q=8.80;p=0.012)were associated with increased culture-positivity, whereas a rising Ct (adjusted Ct change -6.58[95%CI] -5.30, -7.86;p<0.001) was strongly associated with culture-negativity. Analyzing 186 immunocompetent patients with 1393 Ct values, 2 consecutive Cts 30 or a rising Ct value on serial testing demonstrated a sensitivity of 87.5% and specificity of 96.3% using culture positivity as the outcome. Serial Ct monitoring, integrated with clinico-epidemiologic data is a valuable tool for assessing infectiousness, providing objective criteria for discontinuing isolation and guiding clinical decisions.

Authors: Rosca, EC; Oke, J; Jefferson, T; Brassey, J; Onakpoya, I

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Cambridge University Press
• Journal: Epidemiology & Infection
• Pages: 1-56
• Publication date: 2026-05-06
• DOI: 10.1017/s0950268826101484
• EISSN: 1469-4409
• ISSN: 0950-2688
• Language: English
• Keywords: Detection threshold; MEDLINE; Coronavirus disease 2019 (COVID-19); Risk assessment; Infectious disease (medical specialty)