Transmissibility quantification of norovirus outbreaks in 2016-2021 in Beijing, China

The transmissibility is a crucial feature for norovirus, yet its quantitative estimation has been limited. Our objective was to estimate the basic reproduction number (R-0) of norovirus and investigate its variation characteristics. Norovirus outbreaks reported from September 2016 to August 2021 in Beijing were analyzed. The susceptible-infected-removed compartment model was established to estimate R-0. Linear regression models and logistic regression models were used to explore the factors affecting the transmissibility of norovirus. The overall median R-0 of norovirus was estimated as 2.1 (interquartile range [IQR] 1.8-2.5), with 650 norovirus outbreaks. The transmissibility of norovirus varied by year, outbreak setting and genotype. The R-0 of norovirus during September 2019 to August 2020 (median 2.1, IQR 1.8-2.4) and September 2020 to August 2021 (median 2.0, IQR 1.7-2.3) was lower than that of September 2016 to August 2017 (median 2.3, IQR 1.8-2.7) (beta = 0.94, p = 0.05; beta = 0.93, p = 0.008). The R-0 of norovirus for all other settings was lower than that for kindergarten (median 2.4, IQR 2.0-2.9) (primary school: median 2.0, IQR 1.7-2.4, beta = 0.94, p = 0.001; secondary school: median 1.7, IQR 1.5-2.0, beta = 0.87, p < 0.001; college: median 1.7, IQR 1.5-1.8, beta = 0.89, p = 0.03; other closed settings: median 1.8, IQR 1.5-2.0, beta = 0.90, p = 0.004). GII.2[P16] outbreaks had a median R-0 of 2.2 (IQR 1.8-2.7), which was higher than that for GII.6[P7] outbreaks (median 1.8, IQR: 1.8-2.0, odds ratio = 0.19, p = 0.03; GII.2[P16] as reference) and mixed-genotype outbreaks (median 1.7, IQR: 1.5-1.8, beta = 0.92, p = 0.02; mixed-genotype as reference). In kindergartens and primary schools, norovirus shows increased transmissibility, emphasizing the vulnerable population and high-risk settings. Furthermore, the transmissibility of norovirus may change over time and with virus evolution, necessitating additional research to uncover the underlying mechanisms.