The analysis of a large dataset of PCR-test results in the community reveals the impact of age, variants and vaccination status on SARS-CoV-2 viral dynamics

Abstract

The COVID-19 pandemic has shown the value of large-scale community PCR tests for epidemic surveillance, but the viral load measurements they provide have seldom been exploited to reconstruct within-host trajectories. Because these data are collected for diagnostic rather than research purposes, they are characterized by sparse longitudinal follow-up, heterogeneous sampling, and missing metadata, raising uncertainty about their usefulness to reconstruct with-host viral dynamics. We first conducted a simulation study to assess the feasibility of estimating the viral dynamics patterns from such datasets. Across multiple scenarios replicating realistic sampling patterns, we found that peak viral load and clearance time could be estimated with good accuracy, although uncertainty tended to be underestimated. Parameters driving early viral kinetics, e.g. incubation and proliferation time, were mostly estimated with poor precision, as most community tests are conducted after symptom onset, later in infection. We then applied this framework to a large dataset of 322,218 PCR tests associated with symptomatic SARS-CoV-2 infections in France between July 2021 and March 2022, encompassing both Delta-variant circulation and the emergence of first Omicron variants. We quantified the effects of age, vaccination, and variants on viral load trajectories. Age [≥]65 years was consistently associated with longer clearance time, extending the duration of detectable viral load by 2 to 6 days. Vaccination shortened the clearance time by 2 to 4 days but had minimal impact on peak viral load. Infections by Omicron-variants were associated with a lower peak viral load and shorter clearance times compared with pre-Omicron (Delta) infections. Thus, community PCR tests can be leveraged to identify key parameters of viral dynamics. As multiplex PCR testing becomes increasingly widespread, establishing robust frameworks for data collection, sharing, and privacy protection will be essential to support the use of these data. Author SummaryIn this study, we explored whether viral load data collected routinely in community laboratories can help us understand how factors like age, vaccination, and viral variant influence the course of infection. These data, collected for diagnostic purposes rather than research, are large but often incomplete, with most individuals tested only after the time of symptoms onset. We first used simulations to assess whether, despite these limitations, key aspects of viral dynamics can be reliably estimated. We then applied our approach to millions of test results collected in France during periods dominated by Delta and Omicron variants. We found that older age was consistently associated with longer infection duration, while vaccination reduced the time the virus remained detectable without affecting peak viral levels. Omicron infections were generally associated with lower peak viral load and somewhat faster clearance than pre-Omicron infections. Overall, our work demonstrates that community testing data, can provide valuable insights into viral dynamics and help monitor the effects of new variants or interventions. As multiplex tests become more common, facilitating and improving data collection, sharing, and privacy protection will be essential to make the most of these resources in future outbreaks.