Discussion

We have documented respiratory viral replication dynamics for influenza, RSV, and other non–SARS-CoV-2 respiratory viruses, using Ct values as proxy measures for viral burden, from the day of symptom onset through the following 3 weeks. In general, we found that viral burden was intermediate on the day of symptom onset, increased to peak levels (low Ct values) over the next 1–3 days, and then steadily declined thereafter (rising Ct values). Ct values were typically >30 by ∼1 week after symptom onset. We noted substantial variability between patients, however, in Ct values relative to days since symptom onset. We observed generally higher Ct values (less virus) and less day-to-day variability for HMPV and parainfluenza, and we observed generally high and steady Ct values for rhinovirus. We did not find a clear association between immunosuppression and viral dynamics, although our study had limited statistical power for subgroup analyses.

The general pattern of low Ct values near symptom onset followed by a steady increase over the ensuing days with substantial patient-to-patient variability broadly mirrors the viral dynamics seen with the SARS-CoV-2 omicron variant. With the original SARS-CoV-2 strain, Ct values tended to peak around the time of symptom onset or even slightly before. ^{Reference He, Lau and Wu14} However, the pattern right-shifted with the omicron variant; viral burden now tends to peak 1–3 days after symptom onset, ^{Reference Zhou, Hu and Zhao15,Reference Frediani, Parsons and McLendon16} which is consistent with our findings.

The potential parallels between Ct dynamics for SARS-CoV-2 and other respiratory viruses is helpful insofar as many clinicians and infection control practitioners have learned how to integrate Ct values into their decision making for patients with positive SARS-CoV-2 tests with regard to treatment (eg, does this patient require an antiviral medication such as remdesivir?) and necessity and duration of isolation (eg, does this patient have an acute infection or residual viral RNA alone from a prior resolved infection? does this patient need to remain on precautions or have they reached a less contagious point and isolation can be lifted?). Ct values do need to be interpreted cautiously; they are proxy measures alone, prone to intersample and interassay variability. They are best interpreted in conjunction with patients’ prior histories, clinical trajectories, and serial Ct values. Nonetheless, notwithstanding these caveats, Ct values have generally provided helpful collateral data to inform the care and management of patients with SARS-CoV-2–positive tests.

Our findings suggest the possibility that Ct values may prove similarly helpful in the interpretation of positive PCRs for influenza, RSV, and other respiratory viruses. Further data and experience are needed, however, to aid in their evaluation. The interpretation of SARS-CoV-2 Ct values are bolstered by viral culture studies correlating Ct values with the probability of recovering culture-viable virus. ^{Reference Wolfel, Corman and Guggemos7,Reference Singanayagam, Patel and Charlett8} They are further aided by studies documenting correlation between patients’ Ct values and the frequency of secondary transmission. ^{Reference Eyre, Futschik and Tunkel12,Reference Bjorkman, Saldi and Lasda17} Few published data are available regarding viral dynamics for non–SARS-CoV-2 respiratory viruses, and few data are available that correlate non–SARS-CoV-2 respiratory virus Ct values with viral culture. ^{Reference Cohen, Kleynhans and Moyes}

The limited existing data on influenza, RSV, and rhinovirus do, however, mirror our findings. Influenza A Ct values tend to be lower with less time since symptom onset, ^{Reference Spencer, Chung and Thompson18,Reference Brittain-Long, Westin, Olofsson, Lindh and Andersson19} and titers of infectious virus tend to peak 24–72 hours after symptom onset and remain elevated until about day 5 after symptom onset. ^{Reference Frediani, Parsons and McLendon16,Reference Bell, Nicoll and Fukuda20} A small viral culture-based study showed a 1 log decrease in the viral load of H1N1 influenza A at 3 days after symptom onset. ^{Reference To, Chan and Li21} Other studies have suggested that H1N1 influenza A levels may be highest on the day of symptom onset rather than the day after, as in our study. ^{Reference To, Chan and Li21,Reference Duchamp, Casalegno and Gillet22}

To our knowledge, only 1 study has correlated non–SARS-CoV-2 Ct values with probability of transmission, and this study showed that household transmission of influenza was correlated with Ct values <30. Indeed, investigators in this study found that household transmission of influenza was 7-fold higher from people with Ct values <30 versus ≥30. ^{Reference Cohen, Kleynhans and Moyes11} Fuller et al ^{Reference Fuller, Njenga and Bigogo23} did not find a correlation between days since symptom onset and Ct values in a cohort of RSV-infected adults in Kenya, but they did find a correlation among infected children.

Others have observed the relatively weak association between symptom duration and Ct values for rhinovirus. Generally high and steady Ct values suggest that RNA of the virus is present but that the virus is not replicating, possibly indicating colonization rather than acute infection. Others have hypothesized that this finding may be due to the genetic variability of the rhinovirus to increase sample–target mismatch, which diminishes rhinovirus detection. ^{Reference Brittain-Long, Westin, Olofsson, Lindh and Andersson19} The interpretations of all these findings, however, are limited by small sample sizes and substantial patient-to-patient variability.

The high rate of variability between patients, across time, between assays, and between viruses suggest the importance of measuring serial Ct values in patients to clarify likely stage of infection and current viral burden rather than relying on time alone to estimate these parameters.

Our study had several limitations. We used patients’ self-reported intervals since symptom onset garnered through retrospective chart reviews. These may have been subject to recall bias, imprecision, and documentation errors. We excluded asymptomatic patients, which precluded us from describing viral burden before symptom onset, a period that is increasingly recognized as an important contributor to transmission. ^{Reference Cohen, Kleynhans and Moyes11,Reference Huff and Singh24} We created rules to infer concrete time intervals from nonspecific language. We drew Ct values from different molecular assays, which may vary in their amplification characteristics and yield different Ct values for the same sample. We did not detect significant differences between the Cepheid and Panther platforms in a limited set of samples. Patients were not serially sampled in a prospective fashion; rather, we inferred Ct value dynamics based on distributions of Ct values in different patients who tested positive at various time intervals relative to symptom onset. As such, some of the differences in Ct values across different time intervals may have been affected by patient-level variations in viral dynamics. Additionally, we were not able to control for possible confounders, such as personnel collecting the specimen, specimen type, and the adequacy of sampling. Our sample sizes for different intervals varied and in some cases were small, particularly for the day of symptom onset, which increased the variability and uncertainty of our estimates. The immunocompromised patient population was heterogeneous; respiratory virus dynamics among more severely immunocompromised patients may differ more clearly from nonimmunocompromised patients. Finally, we assessed each virus independently, and we presumed that patient symptoms were due to the virus under evaluation without accounting for coinfections or other diagnoses, which may have led to misattribution of some symptoms.

We documented distributions of Ct values as a proxy for respiratory viral burden for influenza, RSV, and other non–SARS-CoV-2 respiratory viruses relative to date of symptom onset. Patterns generally mirrored the dynamics of SARS-CoV-2. Ct values were intermediate on the day of symptom onset, lower on the subsequent few days, and then higher again, generally reaching Ct values >30 after about a week from symptom onset. Results varied widely between patients and between viruses, however, suggesting the importance of measuring serial Ct values to estimate viral burden rather than presuming viral burden based on time since symptom onset alone. These results suggest that Ct values in particular, and quantitative tests in general, may provide valuable information to aid in understanding phase of illness and potential contagiousness for non–SARS-CoV-2 respiratory viruses just as they have for SARS-CoV-2. More data are needed, however, to correlate non–SARS-CoV-2 respiratory virus Ct values with viral culture, contagiousness, and response to therapy.