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. 2018 Jul 11;3(4):e00249-18.
doi: 10.1128/mSphere.00249-18.

Asymptomatic Shedding of Respiratory Virus Among an Ambulatory Population Across Seasons

Free PMC article

Asymptomatic Shedding of Respiratory Virus Among an Ambulatory Population Across Seasons

Ruthie Birger et al. mSphere. .
Free PMC article

Erratum in


Most observation of human respiratory virus carriage is derived from medical surveillance; however, the infections documented by this surveillance represent only a symptomatic fraction of the total infected population. As the role of asymptomatic infection in respiratory virus transmission is still largely unknown and rates of asymptomatic shedding are not well constrained, it is important to obtain more-precise estimates through alternative sampling methods. We actively recruited participants from among visitors to a New York City tourist attraction. Nasopharyngeal swabs, demographics, and survey information on symptoms, medical history, and recent travel were obtained from 2,685 adults over two seasonal arms. We used multiplex PCR to test swab specimens for a selection of common respiratory viruses. A total of 6.2% of samples (168 individuals) tested positive for at least one virus, with 5.6% testing positive in the summer arm and 7.0% testing positive in the winter arm. Of these, 85 (50.6%) were positive for human rhinovirus (HRV), 65 (38.7%) for coronavirus (CoV), and 18 (10.2%) for other viruses (including adenovirus, human metapneumovirus, influenza virus, and parainfluenza virus). Depending on the definition of symptomatic infection, 65% to 97% of infections were classified as asymptomatic. The best-fit model for prediction of positivity across all viruses included a symptom severity score, Hispanic ethnicity data, and age category, though there were slight differences across the seasonal arms. Though having symptoms is predictive of virus positivity, there are high levels of asymptomatic respiratory virus shedding among the members of an ambulatory population in New York City.IMPORTANCE Respiratory viruses are common in human populations, causing significant levels of morbidity. Understanding the distribution of these viruses is critical for designing control methods. However, most data available are from medical records and thus predominantly represent symptomatic infections. Estimates for asymptomatic prevalence are sparse and span a broad range. In this study, we aimed to measure more precisely the proportion of infections that are asymptomatic in a general, ambulatory adult population. We recruited participants from a New York City tourist attraction and administered nasal swabs, testing them for adenovirus, coronavirus, human metapneumovirus, rhinovirus, influenza virus, respiratory syncytial virus, and parainfluenza virus. At recruitment, participants completed surveys on demographics and symptomology. Analysis of these data indicated that over 6% of participants tested positive for shedding of respiratory virus. While participants who tested positive were more likely to report symptoms than those who did not, over half of participants who tested positive were asymptomatic.

Keywords: asymptomatic infection; population health; respiratory viruses.


Virus breakdown among positives across seasons and by month. (a) Percentages of tests that were positive for each virus for the summer arm, the winter arm, and all participants. The numbers above each bar represent the absolute numbers of positive cases. (b) Prevalence of total positive tests by month by virus.
Symptom scores by month. This figure shows mean symptom scores by month among all participants (top) and among the participants testing positive (bottom). There were statistically significant differences in mean symptom scores by month among all participants (P < 0.001 [ANOVA]) but not among only those testing positive (P = 0.914 [ANOVA]), indicating that it is likely that higher respiratory virus prevalence during some months explains the variations in symptom scores over seasons. Note that the sampling in January did not start until near the end of the month, so the sample size was small and may not reflect the true mean symptom scores.

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