Detection of influenza and other respiratory viruses in air sampled from a university campus: a longitudinal study

Abstract

BACKGROUND: Respiratory virus-laden particles are commonly detected in the exhaled breath of symptomatic patients or in air sampled from healthcare settings. However, the temporal relationship of detecting virus-laden particles at non-healthcare locations versus surveillance data obtained by conventional means has not been fully assessed. METHODS: From October 2016 to June 2018, air was sampled weekly from a university campus in Hong Kong. Viral genomes were detected and quantified by real-time RT-PCR. Logistic regression models were fitted to examine the adjusted odds ratios (aORs) of ecological and environmental factors associated with the detection of virus-laden airborne particles. RESULTS: Influenza A (16.9%, 117/694) and B (4.6%, 31/694) viruses were detected at higher frequencies in air than rhinovirus (2.2%, 6/270), respiratory syncytial virus (0.4%, 1/270), or human coronaviruses (0%, 0/270). Multivariate analyses showed that increased crowdedness (aOR = 2.3, 95% confidence interval, 1.5 - 3.8, P < 0.001) and higher indoor temperature (1.2, 1.1 - 1.3, P < 0.001) were associated with detection of influenza airborne particles, but absolute humidity was not (0.9, 0.7 - 1.1, P = 0.213). Higher copies of influenza viral genome were detected from airborne particles > 4 mum in spring and < 1 mum in autumn. Influenza A(H3N2) and influenza B viruses that caused epidemics during the study period were detected in air prior to observing increased influenza activities in the community. CONCLUSIONS: Air sampling as a surveillance tool for monitoring influenza activity at public locations may provide early detection signals on influenza viruses that circulate in the community.