Coronavirus disease 2019 (COVID-19) was identified in January 2020 and since this time has been the cause of global human-to-human transmission (1, 2). Five variants of concern (VOC) have been identified so far, namely Alpha, Beta, Gamma, Delta, and Omicron as designated by the World Health Organization (WHO) (3, 4). The rapid spread of the omicron variant was first identified on 24 November 2021, and it has since become the predominant variant, posing a threat worldwide (5, 6). Compared to DNA viruses, RNA viruses have a higher rate of mutation (7), and Researchers have found that the variant of omicron is the most mutated strain (8, 9) of SARS-CoV-2 variants, which may help the virus evade infection-blocking antibodies (7). These mutations affect the characteristics of SARS-CoV-2 omicron such as infectivity, immune escape, viral shedding time, and outcome. Data have shown that the infectivity of SARS-CoV-2 omicron variants is 10-fold higher than that of alpha, but omicron patients were less likely to be admitted to the hospital and require ICU-level care (10). In addition, reinfection has been observed approximately 10 times more frequently than with the Delta variant (11, 12). Therefore, omicron is expected to impact the therapeutic effect of COVID-19 drugs significantly, as well as immunity secondary to vaccination or prior infection, infectivity, and outcome (13).

In 2022, a wave of COVID-19 rapidly appeared in Shanghai, China, and after comparing the genomes of viruses, researchers found that the genomes of the infected viruses in Shanghai belonged to the Omicron BA.2.2 strain (14, 15). During this period, Zhang et al. found that the total number of patients in Shanghai was much higher than before and that the ratio of severity and mortality was much lower (5). In addition, studies on people infected with omicron variants have shown that age is positively correlated with severity (16, 17).

Understanding the kinetics of infectious viral shedding to possible transmission risk is crucial to guiding infection prevention and control strategies (18). Therefore, it is essential to understand the shedding time of the omicron variant since it is a crucial factor in the guidance of decisions about isolation precautions and antiviral treatment (19, 20). Through a retrospective cohort study that included 59 hospitalized patients with COVID-19, old age was independently associated with long-term virus shedding (21), and another study demonstrated that sex, corticosteroid use, and delayed admission were independent risk factors for prolonged virus shedding time (22) (non-omicron variants). However, whether these findings are also applicable to the omicron variants is still unclear. To attempt to answer this question, we used the search terms (“Omicron”) and (“shedding time”) and (“prolonged”) to search PubMed up until 24 June 2022 and found no relevant articles. In short, the relationship between omicron viral shedding time and risk factors has not been fully clarified. Hence, this study aims to evaluate the characteristics of viral shedding time with older patients infected with omicron in order to identify risk factors that influence the duration of viral shedding.

Few studies have been conducted for the viral shedding time of the omicron variant. To the best of our knowledge, this retrospective research is the first of its kind. We found that age, methylprednisolone therapy, longer time from onset of diagnosis to admission, and D-dimer were associated with prolonged viral shedding. Moreover, our results indicated that the time from onset of diagnosis to hospitalization, lack of treatment with Paxlovid, and lack of vaccination were independent risk factors in patients infected with omicron (Table 2).

Many mutation changes have been found in the omicron variant, significantly impacting both immunities secondary to vaccination or prior infection and the efficacy of therapeutic drugs (13). Unvaccinated patients had a longer viral shedding time than vaccinated patients in our study [38 (43.18%) vs. 18 (19.57%)], and this observation may demonstrate that the vaccine plays a role in accelerating the virus shedding of elderly patients infected with omicron. These findings are also consistent with one prospective, observational study that indicated that the vaccine, especially the booster vaccine, remains effective in preventing severe-stage progression and improving prognosis in patients infected with omicron (25). Similarly, Fan et al. (26) proposed that the vaccine can provide effective protection against omicron, although there will still be breakthrough infections. However, our results only show that the vaccine can shorten the viral shedding time in our population. We cannot determine whether it can decrease disease severity or reduce infection rates.

In addition, a study to observe the factors associated with viral shedding among a cohort of COVID-19 patients indicated that male participants had longer viral shedding and more severe symptoms than females infected with COVID-19 (27). Different from these results, we found no difference between the genders and viral shedding time in elderly patients with omicron, and our result is consistent with Bennasrallah et al. (28), who found no significant difference in time to the viral clearance between genders. Among our 180 patients, the mean age was 77.02 years, and we found that older age prolonged the duration of viral shedding (29). In our analysis of complications, we found differences in the Charlson comorbidity index between the early and late viral clearance groups, but there was no significant difference in hypertension, diabetes, or chronic lung disease between them. We speculate that the reason for this phenomenon is that the patients we included were older, and most of them had multiple complications. We also found that a long time from the onset of diagnosis to admission could prolong the duration of viral shedding. In addition, there was no difference in the disease severity and outcome between patients with early vs. late viral shedding. Future prospective studies are needed to confirm whether elderly patients with prolonged viral shedding are not at risk of severe COVID-19 disease and poor outcomes. From the epidemiological perspective, elderly patients with prolonged viral shedding are mainly contributing to the community spread of COVID-19 infection.

The surprising immune evasion ability of the omicron variant may bring many challenges to specific drug treatments (30). Paxlovid, an oral drug, has received the emergency use authorization from the Food and Drug Administration Agency for treating patients with COVID-19, though the efficacy of Paxlovid in elderly patients infected with the omicron variant is still unclear. By analyzing the usage of Paxlovid between the two groups in this study, we found that the early viral clearance group had been treated with Paxlovid more frequently than the late group. Our results also suggest that Paxlovid can reduce the nucleic acid shedding time. Therefore, in the era of omicron variants, our results suggest that Paxlovid can improve the viral shedding time in elderly patients. In summary, the viral shedding time of elderly patients without vaccination is longer than that of the vaccinated patients. In consequence, the results of this study proposed that unvaccinated elderly patients not receiving Paxlovid are contributing to the transmission of Omicron variants in the community as they are expected to have prolonged viral shedding. In the era of Omicron variants, vaccination is still conducive to reducing the risk of virus transmission.

Treatment with methylprednisolone was found to prolong viral shedding time as well, but it was not an independent risk factor. Previous studies have also demonstrated that corticosteroids prolonged viral shedding time in patients with SARS-CoV-2 (31), and one study reported that treatment with low-dose corticosteroids does not reduce viral shedding time (32). Therefore, the immunosuppressive effect of methylprednisolone may indeed lead to the prolonging of viral shedding time. However, this does not contravene the therapeutic effect of methylprednisolone for COVID-19.

There are several limitations of this study. First, this retrospective study is a single-center study with a small sample size that may cause biases in clinical observations. Second, we attempted to explore the risk factors associated with the viral shedding time, but not everyone was diagnosed on the first day. Third, there is no specific distinction in this article as to whether vaccine-vaccinated patients had been induced with a booster, therefore, future studies should aim to resolve this deficiency. Fourth, participants were only patients aged 60 years and above, which could result in potential bias. Thus, the results presented herein only represent this cohort of patients but not all patients infected with omicron. Finally, the best way to confirm viral shedding would have been through viral cultures. In our study, the laboratory of our hospital did not meet the standards of 3 Laboratory of Biological Safety, so the laboratory was unable to cultivate the SARS-CoV-2 Omicron.

In conclusion, viral shedding time was defined as the time from the first positive nucleic acid test to the date of the first negative test (in two consecutive days) in our study. This study found that time from onset of diagnosis to hospitalization, lack of treatment with Paxlovid, and lack of vaccination were independent risk factors in elderly Chinese patients infected with SARS-CoV-2 omicron for prolonged viral shedding.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

This trial received approval from the Ethics Committee of the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine (No. SH9H-2022-T112-2) and registered at the Chinese Clinical Trial Registry (ChiCTR2200060700). The patients/participants provided their written informed consent to participate in this study.

WZho, XJ, XYa, ZD, WW, ZS, WZha, JC, XYu, and YL collected the epidemiological and clinical data. XJ and YL were responsible for enrollment and clinical monitoring. XYa, WC, ZD, XJ, and YL were responsible for the distribution and storage of medicines. WZho, JC, WC, XYu, YL, and XJ were responsible for statistical data. XYa, WZha, XJ, XYu, JC, JX, and YL drafted the manuscript. JC and YL were responsible for funding, study conception, design, revising, and submitting the final manuscript. All authors contributed to the article and approved the submitted version.