Quantity of SARS-CoV-2 RNA copies exhaled per minute during natural breathing over the course of COVID-19 infection
Lane, G.; Zhou, G.; Hultquist, J. F.; Simons, L. M.; Lorenzo-Redondo, R.; Ozer, E. A.; McCarthy, D. M.; Ison, M. G.; Achenbach, C. J.; Wang, X.; Wai, C. M.; Wyatt, E.; Aalsburg, A.; Yang, Q.; Noto, T.; Alisoltani, A.; Ysselstein, D.; Awatramani, R.; Murphy, R.; Theron, G.; Zelano, C.
Show abstract
SARS-CoV-2 is spread through exhaled breath of infected individuals. A fundamental question in understanding transmission of SARS-CoV-2 is how much virus an individual is exhaling into the environment while they breathe, over the course of their infection. Research on viral load dynamics during COVID-19 infection has focused on internal swab specimens, which provide a measure of viral loads inside the respiratory tract, but not on breath. Therefore, the dynamics of viral shedding on exhaled breath over the course of infection are poorly understood. Here, we collected exhaled breath specimens from COVID-19 patients and used RTq-PCR to show that numbers of exhaled SARS-CoV-2 RNA copies during COVID-19 infection do not decrease significantly until day 8 from symptom-onset. COVID-19-positive participants exhaled an average of 80 SARS-CoV-2 viral RNA copies per minute during the first 8 days of infection, with significant variability both between and within individuals, including spikes over 800 copies a minute in some patients. After day 8, there was a steep drop to levels nearing the limit of detection, persisting for up to 20 days. We further found that levels of exhaled viral RNA increased with self-rated symptom-severity, though individual variation was high. Levels of exhaled viral RNA did not differ across age, sex, time of day, vaccination status or viral variant. Our data provide a fine-grained, direct measure of the number of SARS-CoV-2 viral copies exhaled per minute during natural breathing--including 312 breath specimens collected multiple times daily over the course of infection--in order to fill an important gap in our understanding of the time course of exhaled viral loads in COVID-19.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Elevated mucosal antibody responses against SARS-CoV-2 are correlated with lower viral load and faster decrease in systemic COVID-19 symptoms 95%
- Mapping the emergence of SARS-CoV-2 Omicron variants on a university campus 94%
- Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions 93%
Similar papers in this journal
- Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19 92%
- Nucleocapsid antigenemia is a marker of acute SARS-CoV-2 infection 92%
- Longitudinal assessment of diagnostic test performance over the course of acute SARS-CoV-2 infection 91%
Similar papers in this journal
- Pathogenic and transcriptomic differences of emerging SARS-CoV-2 variants in the Syrian golden hamster model 92%
- Anti-SARS-CoV-2 Antibodies Persist for up to 13 Months and Reduce Risk of Reinfection 91%
- Characterising heterogeneity and sero-reversion in antibody responses to mild SARS⍰CoV-2 infection: a cohort study using time series analysis and mechanistic modelling 91%
Similar papers in this journal
- Transient anti-interferon autoantibodies in the airways are associated with efficient recovery from COVID-19 92%
- SARS-CoV-2 infection results in lasting and systemic perturbations post recovery 91%
- COVID-19-associated olfactory dysfunction reveals SARS-CoV-2 neuroinvasion and persistence in the olfactory system 91%
Similar papers in this journal
- Airway antibodies emerge according to COVID-19 severity and wane rapidly but reappear after SARS-CoV-2 vaccination 92%
- Vaccine Breakthrough Infection with the SARS-CoV-2 Delta or Omicron (BA.1) Variant Leads to Distinct Profiles of Neutralizing Antibody Responses 92%
- Sero-monitoring of health care workers reveals complex relationships between common coronavirus antibodies and SARS-CoV-2 severity 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.