Estimating RSV seasonality from pandemic disruptions: a modelling study

Abstract

Background: Respiratory syncytial virus (RSV) is a leading cause of respiratory tract infections and bronchiolitis in young children. The seasonal pattern of RSV is shaped by short-lived immunity, seasonally varying contact rates and pathogen viability. The magnitude of each of these parameters is not fully clear. The disruption of the regular seasonality of RSV during the COVID pandemic in 2020 due to control measures, and the ensuing delayed surge in RSV cases provides an opportunity to disentangle these factors and to understand the implication for vaccination strategies. A better understanding of the drivers of RSV seasonality is key for developing future vaccination strategies. Methods: We developed a mathematical model of RSV transmission, which simulates the sequential re-infection (SEIRRS4) and uses a flexible Von Mises function to model the seasonal forcing. Using MCMC we fit the model to laboratory confirmed RSV data from 2010-2022 from NSW while accounting for the reduced contact rates during the pandemic with Google mobility data. We estimated the baseline transmission rate, its amplitude and shape during RSV season as well as the duration of immunity. The resulting parameter estimates were compared to a fit to pre-pandemic data only, and to a fit with a cosine forcing function. We then simulated the expected shifts in peak timing and amplitude under two vaccination strategies: continuous and seasonal vaccination. Results: We estimate that RSV dynamics in NSW can be best explained by a high effective baseline transmission rate (2.94/d, 95% CrI 2.72-3.19) and a narrow peak with a maximum 13% increase compared to the baseline transmission rate. We also estimate the duration of post infection temporary but sterilizing immunity to be 412 days (95% CrI 391-434). A cosine forcing resulted in a similar fit and posterior estimates. Excluding the data from the pandemic period in the fit increased parameter correlation and yielded less informative posterior distributions. The continuous vaccination strategy led to more extreme seasonal incidence with a delay in the peak timing and a higher amplitude whereas seasonal vaccination flattened the incidence curves. Conclusion: Quantifying the parameters that govern RSV seasonality is key in determining potential indirect effects from immunization strategies as those are being rolled out in the next few years.

Determinants of RSV epidemiology following suppression through pandemic contact restrictions

“…In the southern hemisphere, Australia also saw a delayed ( Yeoh et al, 2020 , McNab et al, 2021 ) RSV epidemic in the summer months, starting 20 weeks later than usual and reaching a higher peak, confirmed both by surveillance testing and hospital admissions ( Foley et al, 2021 ). As we recently showed in a Bayesian model fitting study ( Krauer et al, 2022 ), the pre- and pandemic RSV data in the case of Australia (New South Wales) also support high baseline transmissibility and low seasonal forcing, similarly to our analysis here.…”

Effectiveness and efficiency of immunisation strategies to prevent RSV among infants and older adults in Germany: a modelling study

“…In the UK, seasonal administration was deemed too challenging logistically, for Germany there are no preferences yet. As observed during the COVID-19 pandemic, RSV seasonality can also be disturbed by external factors 25,26 , which potentially pose additional challenges for a seasonal RSV programme.…”

Optimal Respiratory Syncytial Virus intervention programmes using Nirsevimab in England and Wales

“…The SARS-CoV-2 pandemic has caused seasonal shifts in RSV seasonality in England and Wales, and it remains unclear if a consistent seasonal peak will return to pre-pandemic level. [18,19] If there is a substantial change in RSV incidence and seasonality over the coming year, then limited inferences can be made from the results of this study on the impact and cost-effectiveness of Nirsevimab.…”

“…The seasonality of RSV in England and Wales has been largely unpredictable between 2020 and at the time of writing due to restrictions on social mixing due to the COVID-19 pandemic. [18,19] We make the simplifying assumption in this model that once Nirsevimab is licensed the observed seasonality prior to 2020 will return.…”