Abstract
Background
In Taiwan, the prevalence of COVID-19 was low before April 2022. The low SARS-CoV-2 seroprevalence in the population of Taiwan provides an opportunity for comparison with fewer confounding factors than other populations globally. Cycle threshold (Ct) value is an easily accessible method for modeling SARS-CoV-2 dynamics. In this study, we used clinical samples collected from hospitalized patients to explore the Ct value dynamics of the Omicron variant infection.
Methods
From Jan 2022 to May 2022, we retrospectively included hospitalized patients tested positive by nasopharyngeal SARS-CoV-2 PCR. We categorized the test-positive subjects into different groups according to age, vaccination status, and use of antiviral agents. To investigate the nonlinear relationship between symptom onset days and Ct value, a fractional polynomial model was applied to draw a regression line.
Results
We collected 1718 SARS-CoV-2 viral samples from 812 individuals. The Ct values of unvaccinated individuals were lower than those of vaccinated persons from Day 4 to Day 10 after symptom onset. The Ct value increased more rapidly in those individuals with antiviral drug treatment from Day 2 to Day 7. In elderly individuals, the Ct values increased slowly from Day 5 to Day 10, and the increasing trend was unique compared with that in children and adults.
Conclusion
Our study demonstrated the primary viral infection dynamics of the Omicron variant in hospitalized patients. Vaccination significantly affected viral dynamics, and antiviral agents modified viral dynamics irrespective of vaccination status. In elderly individuals, viral clearance is slower than that in adults and children.
Keywords: Age, Ct value, Omicron variant, SARS-CoV-2, Vaccination
Introduction
Evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome will cause the emergence of new variants. Newly emerging SARS-CoV-2 variants with higher infectivity and various mutations of the spike protein have been found since late 2020. The Omicron variant (B.1.1.529) is currently predominant and associated with the risk of reinfection, immune escape, and high transmissibility.1 , 2
New emerging SARS-CoV-2 variants with increased adaptation and fitness to the host might potentially influence viral transmission.3 In an aerosol transmission model, a higher viral load substantially increased the risk of transmission of the Omicron variant.4 In contrast, one study investigating health care workers with COVID-19 showed a lower viral load among Omicron variant cases than delta variant infections.5 Another study conducted in the US, with 792 delta and 1935 Omicron samples, found that the Omicron variant does not present higher nasopharyngeal viral loads than the delta variant in both symptomatic and asymptomatic cases.6 However, the major limitation of these reports was the lack of stratification by the specific day of symptom onset. Some controversies with respect to the viral dynamics of the Omicron variants still exist.
Currently, most quantitative PCR tests use the cycle threshold (Ct) value to reflect viral load. The Ct value is a basic and easily accessible method for both predicting and modeling viral dynamics. Low Ct values (high viral concentration) more likely indicate acute disease and a highly contagious state. The clinical context of a high Ct value is complex. The presymptomatic stage, asymptomatic infections with unknown disease status, and convalescent phase might reveal high Ct values (low viral concentration).7 However, various platforms, variability in specimen collection, and different types of samples might affect the use of the Ct value as a surrogate for clinical use.8 Determining the risk of transmission in high Ct value patients requires serial tests.
In Taiwan, the prevalence of COVID-19 was low before April 2022.9 , 10 In one population-based seroprevalence study, there was an approximately 0.05% seroprevalence of COVID-19 in 2020.11 The seroprevalence was also as low as 0.4% in symptomatic patients with epidemiological risk and negative RT-PCR tests in 2021.12 In two cross-sectional serology studies performed in 2021, no health care workers had a positive antibody response to SARS-CoV-2.12 , 13 The low SARS-CoV-2 seroprevalence in the population of Taiwan provides an opportunity for comparison with fewer confounding factors than other populations globally. The viral kinetic and Ct value trajectory in hospitalized individuals has not been well established. In addition, vaccination status, COVID-directed treatments, and preexisting medical comorbidities make this issue more complicated. Therefore, we used clinical samples collected during the hospital course to explore the Ct value trajectories of Omicron variant infection.
Methods
From Jan 2022 to May 2022, we retrospectively reviewed SARS-CoV-2 PCR positive samples and identified hospitalized patients from two medical centers. During the study period, all patients underwent nasopharyngeal swabbing at admission. The swabs were transported via prepared media at 2–8 °C (Remel, Inc., Lenexa, Kansas, USA; Copan Diagnostics, Murrieta, CA, USA) and tested for SARS-CoV-2 RNA at the central laboratory of each site via reverse transcription-PCR (RT-PCR). Because a variety of platforms, reagents, or different combinations will cause potential bias, we select a major use PCR platform in our study. RT-PCR was performed by a Roche cobas SARS-CoV-2 assay (Roche Molecular Systems, Branchburg, NJ, USA) with unique TaqMan probes targeting conserved regions within the ORF 1a/b and E genes.14 If the assay showed positive results either for both ORF1 and E genes or for the ORF1 gene only, a tested specimen was considered positive. If specimens tested positive only for the E gene, the result was considered presumptive positive. Ct values are provided by the testing platform based on manufacturer-provided interpretation criteria. A Ct value above 40 is considered undetectable for the virus. The medical records were reviewed to collect relevant demographic data and identify the day of disease onset. The institutional review boards of the two study sites approved the medical, scientific, and ethical aspects of our study (Approval No: 202206036RINA in National Taiwan University Hospital, and 11106-004 in Chi Mei Medical Center).
We categorized the test-positive subjects into different groups according to age, vaccination status, and the use of antiviral agents. According to age, we divided patients into three groups: children, adults, and elderly individuals. Children were defined by age less than 18 years old. Adults were aged between 18 and 65 years old. The elderly group was the population whose age was above 65 years. Individuals who received any kind of vaccine for more than 14 days with approval by the World Health Organization (WHO) or licensure by the Taiwan Food and Drug Administration (TFDA) were categorized as vaccinated. Antiviral agents in our analysis included remdesivir, ritonavir-boosted nirmatrelvir and molnupiravir.
Statistics
The Mann–Whitney U test was used to compare Ct values among two independent groups. The Kruskal–Wallis test and Bonferroni correction were used for multiple comparisons. A two-sided p < 0.05 was considered to indicate statistical significance. The consecutive Ct values of each day after symptom onset were calculated as the median and illustrated in a box plot. To investigate the nonlinear relationship between symptom onset days and Ct value, a fractional polynomial model was applied to draw a regression line with 95% confidence intervals. As a previous study described, multiple specimens from the same individuals fitted in a random intercept regression model showed no substantial difference, suggesting that there was no evidence for dependencies within samples.15 Each individual sample was considered independent. All analyses were performed using Stata, version 15.0 (StataCorp LP, College Station, TX).
Results
Demography
We collected 1718 SARS-CoV-2 viral samples from 812 individuals. There were 384, 699 and 635 samples from children, adults, and elderly individuals, respectively. The median first sampling time after symptom onset was on Day 1 [interquartile range (IQR): 0–2]. The median Ct value of all samples was 20.73 (IQR: 15.87–27.69). In Fig. 1 , we provide a flow chart of the categorization and sample size of each group. In Table 1 , we summarize the demographic data among different age groups with SARS-CoV-2 infection in the study. Most of the children were previously healthy and without comorbidities. A total of 7.7% required oxygen supplementation, and 3.3% needed ventilator support. However, only 2.8% of children were vaccinated with at least one dose of vaccine. In contrast, 56.1% of the elderly were vaccinated, 70.8% also received remdesivir treatment, and 14.4% needed ventilator support during hospitalization. Overall, the vaccinated adult population showed a lower tendency toward severe disease with oxygen (vaccinated vs. unvaccinated: 25.6% vs. 50.8%, p < 0.01) or ventilator use (vaccinated vs. unvaccinated: 5.7% vs. 16.6%, p < 0.01). Detailed data of vaccinated and unvaccinated adults are provided in Table S1.
Fig. 1.
Flow chart of categorization and sample size of each group.
Table 1.
Demographic data among different age groups with SARS-CoV-2 Omicron variant infection in the study.
| Total (N = 812) | Children (N = 246) | Adult (N = 265) | Elderly (N = 301) | |
|---|---|---|---|---|
| Sex (female ratio) | 389 (47.9%) | 107 (43.5%) | 136 (51.3%) | 146 (48.5%) |
| Age | 45.3 (9.4–74.5) | 2.9 (0.6–7.1) | 41.3 (32.5–53.6) | 80.0 (72.6–87.0) |
| Previous SARS-CoV-2 infection history | 0 (0%) | 0 (0%) | 0 (0%) | 0 (0%) |
| Comorbidities | ||||
| Diabetes mellitus | 127 (15.6%) | 0 (0%) | 33 (12.5%) | 94 (31.2%) |
| Hypertension | 241 (29.7%) | 3 (1.2%) | 54 (20.4) | 184 (61.1%) |
| Hyperlipidemia | 101 (12.4%) | 1 (0.4%) | 32 (12.1%) | 68 (22.6%) |
| Cardiovascular disease | 166 (20.4%) | 14 (5.7%) | 25 (9.4%) | 127 (42.2%) |
| Chronic kidney disease | 90 (11.1%) | 1 (0.4%) | 30 (11.3%) | 59 (19.6%) |
| Cirrhosis or hepatic disease | 54 (6.7%) | 3 (1.2%) | 26 (9.8%) | 25 (8.3%) |
| Pulmonary disease | 32 (3.9%) | 7 (2.8%) | 4 (1.5%) | 21 (7.0%) |
| Autoimmune disease | 31 (3.8%) | 1 (0.4%) | 19 (7.2%) | 11 (3.7%) |
| Malignancy | 159 (19.6%) | 5 (2.0%) | 52 (19.6%) | 102 (33.9%) |
| Obesity or overweight | 11 (1.4%) | 2 (0.8%) | 9 (3.4%) | 0 (0%) |
| Medication | ||||
| Corticosteroid | 154 (19.0%) | 13 (5.3%) | 42 (15.8%) | 99 (32.9%) |
| Immunosuppressants | 59 (7.3%) | 7 (2.8%) | 24 (9.1%) | 28 (9.3%) |
| Vaccination status | ||||
| Unvaccinated | 438 (53.9%) | 239 (97.2%) | 67 (25.3%) | 132 (43.9%) |
| 1 dose | 46 (5.7%) | 2 (0.8%) | 19 (7.2%) | 25 (8.3%) |
| 2 doses | 104 (12.8%) | 4 (1.6%) | 60 (22.6%) | 40 (13.3%) |
| ≥3 doses | 224 (27.5%) | 1 (0.4%) | 119 (44.9%) | 104 (34.6%) |
| Treatment | ||||
| Oxygen supplement | 214 (26.4%) | 19 (7.7%) | 43 (16.2%) | 152 (50.5%) |
| Ventilator support | 62 (7.6%) | 8 (3.3%) | 11 (4.2%) | 43 (14.3%) |
| Antiviral agents | ||||
| Remdesivir | 365 (45.0%) | 42 (17.1%) | 110 (41.5%) | 213 (70.8%) |
| Ritonavir/nirmatrelvir or molnupiravir | 151 (18.6%) | 4 (1.6%) | 65 (24.5%) | 82 (27.2%) |
Viral dynamics according to vaccination status
To further investigate the dynamics of Ct value change, we explored the differences among groups on each consecutive day. As shown in Table S2, the Ct values of unvaccinated individuals were lower than those of vaccinated individuals on Day 4 (19.4 vs. 21.0, p = 0.01), Day 6 (20.7 vs. 25.1, p < 0.01), and Day 9 (24.9 vs. 27.6, p = 0.02). The trend of daily change is depicted as a box plot in Fig. 2 A. The data were limited owing to an unequal distribution of sample size each day. Therefore, we used a fractional polynomial model to draw a nonlinear curve to better represent viral kinetics. In Fig. 2B, we depict the 95% confidence interval Ct values of each group. At the beginning of symptom onset, both the vaccinated and unvaccinated groups showed steadily increasing Ct values. However, the Ct values of unvaccinated individuals were much lower than those of vaccinated persons from Day 4 to Day 10, which was compatible with Fig. 2A.
Fig. 2.
SARS-CoV-2 cycle threshold (Ct) values of 1718 nasopharyngeal samples from 812 hospitalized individuals in consecutive days after symptom onset. Samples were divided into vaccinated and unvaccinated groups. The dynamic trends are presented as box plots (Panel A) and polynomial regression models (Panel B). Panel A. In the box plots, the boundary of the box at the bottom indicates the 25th percentile, a line within the box marks the median, and the boundary of the box at the top indicates the 75th percentile. Whiskers above and below the box indicate maximum and minimum. Points above and below the whiskers indicate outliers. Asterisks (∗) denote significant differences between labeled groups by the Mann–Whitney U test with a p-value< 0.05. Panel B. The blue dots indicate the Ct value for vaccinated individuals. In the polynomial regression model, the blue line and surrounding dark gray area represent the predicted Ct values and 95% confidence intervals (CIs) for vaccinated individuals. The dark red dots indicate the Ct value for unvaccinated individuals. The red line and light gray area represent predicted Ct values and 95% CIs for the unvaccinated group.
We performed further analysis on vaccinated individuals. The vaccination combinations among different age groups are provided in Table S3. In vaccinated individuals without antiviral therapies, we compared different vaccination schedules and doses. Within 2 weeks of symptom onset, there was no difference between Ct values among individuals who received boosted mRNA vaccine or 3 doses (Fig. S1, Fig. S2). Only 3 patients received nucleic acid testing from Day 16 to Day 18. The Ct value of the patient tested on Day 18 was extremely low (Ct value: 19.8). Therefore, the 95% CIs are wide.
The effect of antiviral agents on viral dynamics
Next, we explored the effect of antiviral agents on viral dynamics. Vaccinated individuals with antiviral treatment had a more rapid increase in Ct value in the first week than individuals who did not receive any kind of antiviral agent (Fig. S3). Furthermore, we extracted 788 specimens from 438 individuals without COVID-19 vaccination. In 269 samples, patients were exposed to at least one antiviral agent (remdesivir, ritonavir/nirmatrelvir or molnupiravir) with a potential effect on viral replication. In Fig. 3 , we illustrate the predicted Ct values of unvaccinated people with and without antiviral therapies. After symptom onset for 1 day, the Ct values increased more rapidly in the individuals with antiviral drug treatment from Day 2 to Day 7. The two groups intersected with Ct values above 25 after Day 8, with a steady increase in Ct values in the unvaccinated group without antiviral agent use. The Ct value remained below 30 even after two weeks of symptom onset in the unvaccinated group with antiviral agent use. In between groups analysis, individuals with antiviral drug treatment showed a higher proportion of oxygen (53.4% vs. 14.0%, p < 0.01) and a higher proportion of ventilator use (19.9% vs. 4.1%, p < 0.01). They also had more chronic diseases and medication use, which included diabetes mellitus (26.7% vs. 6.5%, p < 0.01), hypertension (47.3% vs. 11.3%, p < 0.01), cardiovascular disease (36.3% vs. 9.6%, p < 0.01), malignancy (32.2% vs. 7.2%, p < 0.01), and corticosteroid use (37.7% vs. 8.9%, p < 0.01).
Fig. 3.
SARS-CoV-2 cycle threshold (Ct) values of unvaccinated hospitalized individuals in consecutive days after symptom onset. Samples were divided into two groups, with or without antiviral agent exposure. In the figure generated via polynomial regression models, the blue line and surrounding dark gray area represent the predicted Ct values and 95% confidence intervals (CIs) for unvaccinated individuals with any kind of antiviral agent treatment (including remdesivir, nirmatrelvir/ritonavir, or molnupiravir). The red line and light gray area represent predicted Ct values and 95% CIs for unvaccinated individuals without any antiviral agent use.
Viral dynamics in different age groups
Finally, we investigated the daily Ct value trend among different age groups. All the specimens were selected from unvaccinated individuals without antiviral agent exposure. There were 348 samples collected from 228 children, 70 samples from 26 adults, and 101 samples from 38 elderly individuals. We present the results in Fig. 4 . From Day 8 to Day 14, there was a trend of higher Ct values in unvaccinated adults than in children. However, the 95% CI areas of children and adults overlapped within two weeks of disease onset. In elderly individuals, the Ct values increased slowly from Day 5 to Day 10, which is unique compared with children and adults.
Fig. 4.
SARS-CoV-2 cycle threshold (Ct) values of unvaccinated hospitalized individuals without antiviral therapies in consecutive days after symptom onset. In the figure generated via polynomial regression models, the red line and light gray area represent predicted Ct values and 95% confidence intervals (CIs) for children. The blue line and surrounding dark gray area represent the predicted Ct values and 95% CIs for adults. The green line and surrounding pink area represent the predicted Ct values and 95% CIs for elderly individuals.
Discussion
The major strength of our study is the low prevalence of previous SARS-CoV-2 infection in general population before April 2022. During our study period, the Omicron BA.2.3.7 variant was a predominant lineage with persistent circulation.16 , 17 Therefore, our study presents the primary viral infection dynamics of the Omicron variant without interference of previous infections from other strains. Three major factors (age, vaccination status, and use of antiviral agents), which may potentially affect viral kinetics, were also explored separately.
Vaccination significantly changed viral kinetics in COVID-19. Broad vaccine coverage could shorten the duration of live virus shedding and substantially reduce the severity of disease.18 In our study, vaccinated individuals showed higher Ct values than unvaccinated individuals within 10 days of symptom onset. Although no viral culture was performed in our institutes, this result appears to imply a reduced infectious viral load in vaccinated individuals. The Ct values were greater than 30 on Days 11 and 13 in the vaccinated and unvaccinated groups, respectively. This finding is different from two recently published studies conducted in the US and Germany, which revealed Ct values above 30 within 7 days in participants with breakthrough infection.19 , 20 In these studies, it is possible that some individuals had been previously infected with SARS-CoV-2, but had not been diagnosed due to mild or asymptomatic disease. The observed patterns of viral dynamics in reinfected individuals differed from those with primary infections. A higher mean nadir Ct value and shorter period from reinfection to viral clearance indicated reduced viral replication.21 Therefore, the previous SARS-CoV-2 infection status could not be adjusted properly.
Our study also provided some evidence regarding boosted vaccines on viral dynamics. There was no difference in the SARS-CoV-2 Ct value among individuals who received a third COVID-19 vaccine dose compared to those that did not (Figs. S2 and S3). This result is comparable with the study conducted by Kandel et al.22 However, the protective effect of the BNT162b2 or mRNA-1273 booster vaccine dose waned over time. The time from the last vaccination to infection and neutralizing antibody concentration waning were not adjusted in our cohort due to limited case numbers, which deserves further investigation.
Some patients received antiviral treatment during hospitalization, which may potentially affect viral kinetics. As a previous modeling study stated, remdesivir can lead to a median reduction of 0.7 days in the time to viral clearance compared with the standard of care, especially in patients with a high viral load.23 Irrespective of vaccination status in our study, the Ct values showed a more rapid increase in patients with antiviral therapies compared with patients without any antiviral drug during the first 10 days of illness. This finding suggested the positive effect of SARS-CoV-2-directed therapies on inhibiting viral RNA replication. However, we observed slow viral clearance post Day 10 in patients who received antiviral agents (Fig. 3). More severe disease in the antiviral treatment group, individuals with relatively common comorbidities or immunocompromised status, and a high possibility of concomitantly prescribed corticosteroids were all known risk factors for prolonged viral shedding in clinical samples.24 Another consideration is the use of ritonavir-boosted nirmatrelvir. In a recently published article, culturable virus was identified in some patients who completed ritonavir/nirmatrelvir treatment for up to 2 weeks.25 However, this issue is currently controversial and beyond the scope of our study. Therefore, we did not perform further analysis.
In our study, we demonstrated different viral trajectories among distinct age groups on consecutive days. In hospitalized children, we found a lower Ct value during the first week of illness than that in adults (not present). In Taiwan, children under 12 years of age did not receive any vaccinations before June 2022. After adjusting for vaccination status and antiviral agent effects, the viral trajectories of children were similar to those of adults. Although children often present with mild disease, our study highlights the necessity of pediatric COVID-19 vaccine implementation to reduce transmission in school and household settings.26 Another finding in our study was prolonged viral shedding in elderly individuals. The major drawback of PCR is that it fails to determine virus infectivity. Although SARS-CoV-2 may persist in respiratory or fecal samples for 2–3 months, viable virus tends to be short-lived.27 Therefore, we could not conclude that a lower Ct value in the elderly individuals was correlated with higher infectivity during the late disease phase.
In our analysis, all the patients enrolled are inpatients. Therefore, the study results could not be extrapolated to outpatients. Besides, some confounding factors were not adjusted. First, due to the small sample size, each patient's viral dynamics were based on 1–2 samples only. Second, because of various vaccination combinations, we did not perform further analysis on different vaccine types and the effect of these vaccine types on viral dynamics. Third, underlying comorbidities were complex factors that could not be adjusted for. Finally, we obtained virological data from diagnostic samples only, and samples were not prospectively collected at predefined timepoints. Lack of consistency on the day of testing, driven by the retrospective nature of the study, might create some biases during interpretation.
Conclusion
Our study demonstrated the primary viral infection dynamics of the Omicron variant in hospitalized patients. Different patient groups may present with distinct Ct value trajectories. Vaccination significantly affected viral dynamics, and antiviral agents also modified viral dynamics irrespective of vaccination status. In elderly individuals, viral clearance is slower than that in adults and children.
Funding statement
This research was supported in part by research grants from Chi Mei Medical Center (CMOR11202, CMNCKU11101, CMFHR11181, CMFHT11001, CCFHR11202), the National Science and Technology Council (NSTC 111-2321-B-002-017 and NSTC 112-2321-B-002-013) and National Taiwan University Hospital (NTUH W1_112-03). The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Declaration of competing interest
The authors have no conflicts of interest relevant to this article.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jfma.2023.04.023.
Appendix A. Supplementary data
The following are the Supplementary data to this article.
figs1.
figs2.
figs3.
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