Observations of human respiratory virus infection burden are typically derived from medical surveillance. Clinical cases documented by medical surveillance, however, only represent the symptomatic fraction of the total infected population. The role of asymptomatic infection in respiratory virus transmission and rates of asymptomatic shedding are largely unknown. It is therefore important to obtain more precise estimates through novel sampling methods. In big cities, asymptomatic or mildly symptomatic individuals have many opportunities to mix with uninfected individuals. Estimating the prevalence of infection in an urban population is crucial for understanding the transmission ecology of respiratory viruses. To better understand the urban ecology of respiratory viruses, we carried out a study to sample a healthy urban population by recruiting participants from a New York City tourist attraction. Nasopharyngeal swabs, demographics, and survey information on symptoms, medical history, and recent travel were obtained from 2865 adults over two seasonal arms (summer and winter). We used multiplex PCR to test swab specimens for a selection of common respiratory viruses, and performed statistical analyses to test for associations between various demographic factors, symptomology and viral positivity.
Results/Conclusions
6.2% of samples (168 individuals) tested positive for at least one virus, with 5.6% testing positive in the summer, and 7.0% testing positive in the winter. Of these, 85 (50.6%) were positive for human rhinovirus, 65 (38.7%) for coronavirus, and 18 (10.2%) for other viruses (including adenovirus, human metapneumovirus, influenza, and parainfluenza). Depending on the definition of symptomatic infection, 65%-97% of infections were classified as asymptomatic. The best-fit model for prediction of positivity across all viruses included symptom severity score, though there were slight differences across seasons. Our results from this study indicate that that there is a significant level of infection and viral shedding in this apparently healthy urban population in both summer and winter. These results illuminate respiratory infection ecology, and could help improve estimates of infection incidence and inform transmission modeling and disease forecasts, both important tools for control efforts. We demonstrate that the quantification of respiratory virus prevalence outside of the clinic can help with the design of control measures in real-world settings where most transmission occurs.