Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: A retrospective cohort study
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eLife assessment
This manuscript provides a valuable and policy-relevant contribution to our understanding of SARS-CoV-2 viral kinetics in the Omicron era. The authors exploit a rich and unique dataset from the National Basketball Association to describe post-infection viral kinetics and explore evidence for differential kinetics by immune history and demographics. The authors show (as others have) that most people remain with high viral loads 5 days post positive test (though less so in groups who are tested in a more realistic manner), and that older individuals and those who were boosted (but had a poor initial response to the primary vaccine series) were more likely to remain with high viral loads longer after an Omicron infection, while also describing rebound frequencies after Omicron infections.
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Abstract
The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.
Methods:
We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.
Results:
Among individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.3–53.6%) remained potentially infectious (Ct <30) 5 days post detection, with small differences across variants and vaccination status. Only seven viral rebounds (0.7%; N=999) were observed, with rebound defined as 3+days with Ct <30 following an initial clearance of 3+days with Ct ≥30. High antibody titers against the founder SARS-CoV-2 strain predicted lower peak viral loads and shorter durations of infection. Among Omicron BA.1 infections, boosted individuals had lower pre-booster antibody titers and longer clearance times than non-boosted individuals.
Conclusions:
SARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.
Funding:
Supported in part by CDC contract #200-2016-91779, a sponsored research agreement to Yale University from the National Basketball Association contract #21-003529, and the National Basketball Players Association.
Article activity feed
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eLife assessment
This manuscript provides a valuable and policy-relevant contribution to our understanding of SARS-CoV-2 viral kinetics in the Omicron era. The authors exploit a rich and unique dataset from the National Basketball Association to describe post-infection viral kinetics and explore evidence for differential kinetics by immune history and demographics. The authors show (as others have) that most people remain with high viral loads 5 days post positive test (though less so in groups who are tested in a more realistic manner), and that older individuals and those who were boosted (but had a poor initial response to the primary vaccine series) were more likely to remain with high viral loads longer after an Omicron infection, while also describing rebound frequencies after Omicron infections.
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Reviewer #1 (Public Review):
The authors seek to quantify SARS-CoV-2 viral kinetics and address the question of whether this varies with variant, vaccination status, previous exposure, symptom status or age. The results are supported by two independent analyses. A first analysis based on a logistic regression that models the probability of having a cycle threshold (Ct) value <= 30 on each day post-detection. A second analysis that uses a semi-mechanistic model that describes viral proliferation and clearance (using Ct value as a proxy) with a 2-piece linear function.
The authors find small, but clear differences in SARS-CoV-2 clearance times related to several factors. They show that for Omicron infections, boosted individuals have longer clearance times than non-boosted individuals. When further stratifying by pre-booster antibody …
Reviewer #1 (Public Review):
The authors seek to quantify SARS-CoV-2 viral kinetics and address the question of whether this varies with variant, vaccination status, previous exposure, symptom status or age. The results are supported by two independent analyses. A first analysis based on a logistic regression that models the probability of having a cycle threshold (Ct) value <= 30 on each day post-detection. A second analysis that uses a semi-mechanistic model that describes viral proliferation and clearance (using Ct value as a proxy) with a 2-piece linear function.
The authors find small, but clear differences in SARS-CoV-2 clearance times related to several factors. They show that for Omicron infections, boosted individuals have longer clearance times than non-boosted individuals. When further stratifying by pre-booster antibody titer, they found that boosted individuals with low antibody titers had a slowest clearance, and non-boosted individuals with high antibody titers had a quickest clearance. These results are slightly confounded by age, given that boosted individuals were generally older than non-boosted ones, and younger Omicron-infected individuals had higher antibody titers than older Omicron-infected individuals, but the trends were consistent in the sensitivity and subgroup analysis. Overall, the conclusions are supported by the data analysis.
Given the changing epidemiology of SARS-CoV-2, it is important to continue to estimate viral kinetics and clearance times to adapt isolation policies accordingly. I agree with the claim of the authors that these results may support a change from time-based policies of isolation to test-based ones.
The strengths of the manuscript are the quality of the data, with a high sampling frequency, the choice of the statistical models, and the sensitivity analysis conducted. An inevitable weakness is that the population is not representative of the whole population (acknowledged in the manuscript). In this regard, a bit more information about the population of the study in the introduction would be appreciated.
I very much liked the results for the viral kinetics model. The viral kinetics model allows to differentiate the duration of the two phases (proliferation and clearance) as well as the peak viral RNA, thus giving a more precise picture of the attributes of the viral trajectory that vary as a function of different factors. I found the procedure and the results for this model easier to interpret than the results from the logistic regression.
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Reviewer #2 (Public Review):
This manuscript provides a detailed and useful account of post-infection viral trajectories during the early SARS-CoV-2 Omicron era. Data in these analyses come from a unique cohort individuals from the National Basketball Association including players who, while they may not be representative of the general population, were sampled densely throughout the pandemic. The authors describe the duration of (presumptive) infectiousness, using CT values as a proxy, and explore how time to non-infectiousness differs by immune history and demographics. The authors used logistic regression models to estimate the probability of having a Ct value < 30 by day since detection and various other factors including lineage, age, post-primary vaccination antibody levels and exposure history. They then used previously published …
Reviewer #2 (Public Review):
This manuscript provides a detailed and useful account of post-infection viral trajectories during the early SARS-CoV-2 Omicron era. Data in these analyses come from a unique cohort individuals from the National Basketball Association including players who, while they may not be representative of the general population, were sampled densely throughout the pandemic. The authors describe the duration of (presumptive) infectiousness, using CT values as a proxy, and explore how time to non-infectiousness differs by immune history and demographics. The authors used logistic regression models to estimate the probability of having a Ct value < 30 by day since detection and various other factors including lineage, age, post-primary vaccination antibody levels and exposure history. They then used previously published semi-mechanistic models to post infection kinetics, allowing for variability in kinetics by similar factors.
The authors make several important observations:
1. That most people continue to have a Ct value < 30 on the 5th day post detection. While not a novel observation, even for Omicron infections, it further adds to the importance of isolation strategies that include a testing component.
2. That rebounds do happen but even with relaxed definitions it is usually less than 1% (as high as perhaps 3%). If these are indeed in individuals that did not take anti-virals, these data are important for quantifying changes in the risk of rebound infections after antiviral treatment.
3. That boosted individuals were less likely to have an Omicron infection but among those that were infected, they were more likely to have a longer period with an elevated viral load. While this may be partly due to an age effect (and other factors), the authors suggest that even after controlling for age, this difference persists. Through looking at post-primary vaccination antibody levels (to the prototypical SARS-CoV-2) in a subset of the cohort, the authors show that this booster effect may be due to the fact that breakthrough infections in boosted individuals tended to occur in those who had a lower initial antibody response.
The authors do a great job of trying to disentangle lineage, age and exposure history, in primary and sensitivity analyses but there is no way to do this perfectly. I believe the conclusions are well justified by the results of the analyses and the authors sufficiently discuss the limitations of the data and results.
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SciScore for 10.1101/2022.01.13.22269257: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There are a number of limitations to these data and analyses. First, Ct values report viral RNA copies and do not necessarily capture infectiousness. While we chose a Ct value cutoff of 30 as a proxy for infectiousness13–17, this threshold should not be considered a perfect predictor of infectiousness. Second, the Ct values reported here are from samples that each combined anterior nares and oropharyngeal swabs and were performed on …
SciScore for 10.1101/2022.01.13.22269257: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There are a number of limitations to these data and analyses. First, Ct values report viral RNA copies and do not necessarily capture infectiousness. While we chose a Ct value cutoff of 30 as a proxy for infectiousness13–17, this threshold should not be considered a perfect predictor of infectiousness. Second, the Ct values reported here are from samples that each combined anterior nares and oropharyngeal swabs and were performed on the Roche Cobas platform; results may differ by anatomical site and by PCR platform24–27. Third, this relatively small sample set was obtained in a population that is not representative of the general population. The study population of working individuals is younger and generally healthier, with high vaccination coverage, than to the general population, thus infections in this group may have a shorter clearance phase on average than in the general population. Furthermore, this cohort is under intensive testing, behavior protocols, and case-finding efforts; individuals detected due to symptom onset or concern for contacts may be detected earlier in infection than would be typical in the community. While results from a Japanese study suggest similar viral kinetics in a distinct population21, additional analyses from larger cohorts and across additional demographic groups are urgently needed. Finally, not all infected individuals were serially tested until obtaining a negative test result. As some of the trajectories reported here are right censored...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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