Abstract
Background/Aim: SARS-CoV-2 infects the oral and salivary glandular epithelia, leading to release of progeny viruses to shed into saliva. This causes the persistent spread of COVID-19 since the outbreak of the Omicron variants. Viral spread may be mainly attributable to the aerosol transmission of cell-free virions in saliva droplets <5 μm in diameter. However, no data exist on how cell-free virions in the saliva change over time. We, therefore, examined temporal changes in the proportion of cell-free virions shed into saliva relative to whole saliva in individuals infected with the SARS-CoV-2 Omicron variant.
Materials and Methods: This study analyzed three indices, total viral load in whole saliva, cell-free virion load in centrifuged supernatant, and ”salivary viral load ratio”, in 14 subjects infected with SARS-CoV-2 Omicron variant on days 1, 4, and 7 after symptom onset. The “saliva viral load ratio” was calculated by dividing the number of cell-free virions in the centrifuged supernatant by the total number of viruses detected in the whole saliva.
Results: The viral load in whole saliva and in the salivary supernatant considerably decreased with time since day 1. However, unexpectedly regarding “salivary viral load ratio,” no substantial difference was observed among the collection dates.
Conclusion: Determining the chronological dynamics of salivary cell-free viral load and “salivary viral load ratio” is important for monitoring aerosol transmission. Individuals infected with Omicron variants remain potent to render aerosol transmission until COVID-19 is cured. This will alert health care providers to consider “salivary viral load ratio” as an indicative measure of the likelihood of aerosol transmission in the very early stages of viral infection outbreaks.
Introduction
Due to the high transmissibility and lethality of the coronavirus disease 2019 (COVID-19) ascribed to the high infectivity of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the daily lifestyle of humans has changed dramatically and shifted into a “new normal with COVID-19” and has long since its outbreak (1). The keeping as the dominant strains in the prevalence of progenies derived from the Omicron variants of SARS-CoV-2 is still showing the persistent spread of COVID-19. This is completely attributable to the ease of mutation conferring increased transmissibility of the SARS-CoV-2 (2). SARS-CoV-2 infects the oral and salivary glandular epithelia (3). This has caused many progeny viruses to be shed into saliva and consequently resulted in an increase in the incidence of secondary household infections and large community clusters, especially since the outbreak of the Omicron variant (4). This may have been mainly attributable to an increase in the aerosol transmission of saliva droplets <5 μm in diameter.
Upon comparison of the salivary viral load among the strains of conventional, Delta, and Omicron, we found that individuals infected with the Delta variants exhibited a 15-fold higher load than those infected with the conventional strains despite exhibiting a similar salivary viral load ratio, a quotient calculated by dividing the number of cell-free virions in the supernatant after the centrifugation by that of whole viruses detected in the whole saliva (5). We also found that Omicron variant-infected individuals exhibited a similar viral load to Delta variant-infected individuals, but exhibited an approximately four-fold higher viral load ratio (5). Another group has in parallel found that cell-free virions infect three times faster than cell-associated viruses (3); when considered in conjunction with our findings, their findings underscore the importance of freshly shed cell-free virions into saliva particularly in aerosol transmission. The amount of virus shed into saliva such as that in nasopharyngeal mucus decreases with time after the onset of infection. It could no longer be detectable by means of real-time quantitative polymerase chain reaction (real-time q-PCR) in saliva within about a week or two after the onset of infection, depending on the individual (6, 7). However, no data exist on how this viral load ratio changes over time.
Therefore, we conducted an eight-day study in order to follow the dynamics of the salivary viral load ratio of individuals infected with Omicron variants of SARS-CoV-2.
Materials and Methods
Study approval and participants. This cross-sectional study followed the STROBE reporting guidelines and was approved by the Ethics Committee of Nihon University School of Dentistry. Participants were Japanese patients who provided written consent, visited an outpatient fever clinic in Nagoya, Japan, presenting with fever, sore throat, and cough as their primary complaints, and were later determined to be positive for Omicron variants of SARS-CoV-2.
Saliva collection. Whole saliva specimens were collected from 14 patients positive for the G339D mutation in the spike protein on days 1, 4, and 7 after the onset; participants’ information is summarized in Table I. Participants were asked to refrain from eating or drinking for 60 min before and during the saliva sample collection. Just before the sample collection, they were asked to roll the saliva stored in their mouth along the walls of their oral cavity, then spit it into the collection tube.
Patient characteristics.
Cell-free supernatant separation. Cell-free supernatants were generated by centrifugation (10,000 g for 5 min) of whole saliva samples and contained only 0.5% host DNA, as determined by human chromosome-specific quantitative polymerase chain reaction (5).
Extraction of viral RNA. Viral RNA extraction and real-time quantitative polymerase chain reaction were performed according to the protocols of the National Institute of Infectious Diseases of Japan (8). Synthesized viral RNA was used to construct a standard curve for determining salivary viral load, using a combination of dilution to the limit and Poisson null distribution.
Statistical analysis. Viral load in whole saliva, in saliva supernatant, and salivary viral load ratio (the ratio of viral load in the supernatant to that in the whole saliva sample) were calculated respectively, and the Friedman–Bonferroni test was used to compare calculated values among the three dates of collection using the SPSS software, version 28.0.1.1(14) (IBM Corporation, Armonk, NY, USA). Two-sided p<0.05 indicates statistical significance.
Results
The viral load of the whole saliva was ranked and summarized with line graphs and box-and-whisker plots (Figure 1). Likewise, that of saliva supernatant is shown in Figure 2. The salivary viral load ratio was then ranked and summarized with a box-and-whisker plot (Figure 3). Consistent with preceding studies, values of viral load generally decreased as time passed. Significant decreases were found between days 1 and 7 and between days 4 and 7. However, unexpectedly regarding the viral load ratio, no significant differences were observed among the collection dates. In an incidental note, we also collected saliva 14 days after the onset of the disease and made measurements. The results showed that 7 of the 14 individuals had viral RNA below the detection limit (data not shown).
Salivary viral loads in whole saliva (n=14) were determined at days 1, 4, and 7 since the onset of COVID-19 and depicted by a line graph (A) and by a box-and-whisker plot in which significance of differences is shown between pairs (indicated with a connecting bar) (B). A Friedmann–Bonferroni test was conducted to compare the three days shown in the graph; p<0.05 was considered statistically significant.
Salivary viral loads in saliva supernatants after centrifugation (10,000 ′ g, 10 min) (n=14) of whole saliva samples were determined at days 1, 4, and 7 since the onset of COVID-19 and depicted by a line graph (A) and by a box-and-whisker plot in which significance of differences is shown between pairs (indicated with a connecting bar) (B). A Friedmann–Bonferroni test was conducted to compare the three days shown in the graph; p<0.05 was considered statistically significant.
Salivary viral load ratios are calculated by dividing the number of cell-free virions in the supernatant after centrifugation to that of whole viruses detected in the whole saliva. Salivary viral load ratios (n=14) were determined at days 1, 4, and 7 since the onset of COVID-19 and depicted by a box-and-whisker plot in which significance of differences is shown between pairs (indicated with a connecting bar, if any). A Friedmann–Bonferroni test was conducted to compare the three days shown in the graph; p<0.05 was considered statistically significant.
Discussion
The spread of COVID-19 still continues owing to the derivatives of the Omicron variants of SARS-CoV-2. The addition of substantial aerosol transmission, especially after the outbreak of the Omicron variant has created a public health problem as when, where, and from whom the transmission occurs remains unknown. Particular attention must be paid for preventing the spread of infection among individuals with underlying medical conditions or the older adults as the mortality rate still remains high in those individuals. Therefore, in addition to wearing masks and ensuring adequate ventilation (9, 10), considering alternative infection control measures remains necessary.
Since aerosol transmission mainly depends on the number of cell-free virions in released salivary droplets smaller than 5 micrometers as the diameter, the efficacy of preventing the spread of viruses, especially against the so-called “super spreaders” will continue to be a matter of concern for all healthcare professionals until those individuals can be identified. That is why, reduction of cell-free virion load in the saliva surely helps prevent the spread of SARS-CoV-2 via aerosol transmission. However, although mouth rinsing with tap water would be a simple and daily activity for an individual with normal physical functions, unfortunately its effectiveness has not been approved by World Health Organization and other health care authorities owing to the lack of evidence. Therefore, determining the chronological dynamics of the salivary cell-free viral load and salivary viral load ratio is quite important for monitoring aerosol infection. In particular, the salivary viral load ratio should be interpreted as illustrating the number of cell-free virions newly shed in a unit amount of saliva secreted per unit of time.
To the best of our knowledge, this is the first study to demonstrate the chronological dynamics of the salivary cell-free viral load coupled with the salivary viral load ratio in individuals infected with the Omicron variants of SARS-CoV-2. The viral load in whole saliva and that in the salivary supernatant decreased with time since day 1. However, although the median viral load ratio on day 4 appeared around double of that on day 1, no significant difference was observed in the salivary viral load ratio among days 1, 4, and 7 of disease onset. This indicates that although the amount of virus shed in saliva decreased, the ratio of newly released cell-free virion per unit time and unit salivary output did not change.
Our study has a limitation. Common to this type of study, it focused on a single site with a small sample size. Conducting a study with an increased sample size across multiple sites is both urgent and important. Given the correlation between SARS-CoV-2 infection onset and severity with patient age (11), patient stratification by age must also be considered. However, the productivity of newly released cell-free virions is assumed to have been constant. This could be interpreted that although with lesser transmissibility as time passes in proportion to the amount of cell-free virions shed into saliva, the individual infected with strains derived from Omicron variants is potent to render the aerosol transmission until COVID-19 is cured. Moreover, we are sure that “salivary viral load ratio” indicates whether a certain viral strain is as likely to be aerosol transmissible as the Omicron variants. Health care providers should consider this index at the very early stage in an outbreak of emerging or re-emerging viral infections spread by aerosol transmission in the future and develop infection control strategies against them.
Acknowledgements
This work was supported by JSPS KAKENHI, and Uemura Fund, Dental Research Center, Nihon University School of Dentistry, and the research grant of Nihon University.
Footnotes
Authors’ Contributions
K.I. conceived and designed the experiments. A.T., K.S., and N.T. performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures, and reviewed drafts of the article. S.S. contributed to discussion, analyzed the data, and reviewed drafts of the article. K.I. performed the experiments, analyzed the data, wrote or reviewed drafts of the article.
Conflicts of Interest
All the Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Artificial Intelligence (AI) Disclosure
No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.
- Received December 31, 2025.
- Revision received January 17, 2026.
- Accepted February 11, 2026.
- Copyright © 2026 The Author(s). Published by the International Institute of Anticancer Research.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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