Distribution of Transmission Potential During Nonsevere COVID-19 Illness

Abstract

Background: Patients recovering from coronavirus disease 2019 (COVID-19) often continue to test positive for the causative virus by polymerase chain reaction (PCR) even after clinical recovery, thereby complicating return-to-work plans. The purpose of this study was to evaluate transmission potential of COVID-19 by examining viral load with respect to time.

Methods: Health care personnel (HCP) at Cleveland Clinic diagnosed with COVID-19, who recovered without needing hospitalization, were identified. Threshold cycles (Ct) for positive PCR tests were obtained and viral loads calculated. The association of viral load with days since symptom onset was examined in a multivariable regression model, which was reduced by stepwise backward selection to only keep variables significant at a level of .05. Viral loads by day since symptom onset were predicted using the model and transmission potential evaluated by examination of a viral load-time curve.

Results: Over 6 weeks, 230 HCP had 528 tests performed. Viral loads declined by orders of magnitude within a few days of symptom onset. The only variable significantly associated with viral load was time since onset of symptoms. Of the area under the curve (AUC) spanning symptom onset to 30 days, 96.9% lay within the first 7 days, and 99.7% within 10 days. Findings were very similar when validated using split-sample and 10-fold cross-validation.

Conclusions: Among patients with nonsevere COVID-19, viral loads in upper respiratory specimens peak by 2 or 3 days from symptom onset and decrease rapidly thereafter. The vast majority of the viral load-time AUC lies within 10 days of symptom onset.

Keywords: SARS virus; area under curve; disease transmission; infectious; viral load.

© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Figures

Figure 1.

Scatterplot of viral load versus days since onset of symptoms. Points on the scatterplot represent individual tests. The y-axis is on a logarithmic scale. Viral load is represented as number of times the minimum detectable viral load. Negative tests are assigned a viral load of 1 to avoid a log(0) error. The shape of each point corresponds to the gender of the patient tested. Points are jittered along the x-axis to unmask overlap.

Figure 2.

Relationship between days since onset of symptoms and the log10 viral load in a restricted cubic splines regression model with 4 degrees of freedom. The boxplots show the distribution of the log10 of the actual viral load each day after onset of symptoms. Viral load is represented as number of times the minimum detectable viral load. The black circles and fitted line represent the predicted log10 viral loads for each day.

Figure 3.

Viral load-time curve showing the proportion of the 30-day AUC that lies within various intervals. Viral loads were predicted from the final restricted cubic spline regression model. The predicted viral load for each day was plotted against days since onset of symptoms. Viral load is represented as number of times the minimum detectable viral load. The area under the viral load-time curve was calculated by integration of the function representing the relationship between the predicted viral load and days since onset of symptoms. Abbreviations: d, days; AUC, area under the curve.