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SUMMARY:Estimating RSV seasonality from pandemic disruptions: a modelling 
 study - Fabienne Krauer\, The London School of Hygiene &amp\; Tropical Med
 icine
DTSTART:20220616T100000Z
DTEND:20220616T110000Z
UID:TALK175916@talks.cam.ac.uk
CONTACT:Dr H Ge
DESCRIPTION:Background: Respiratory syncytial virus (RSV) is a leading cau
 se of respiratory tract infections and bronchiolitis in young children. Th
 e seasonal pattern of RSV is shaped by short-lived immunity\, seasonally v
 arying contact rates and pathogen viability. The magnitude of each of thes
 e parameters is not fully clear. The disruption of the regular seasonality
  of RSV during the COVID pandemic in 2020 due to control measures\, and th
 e ensuing delayed surge in RSV cases provides an opportunity to disentangl
 e these factors and to understand the implication for vaccination strategi
 es. A better understanding of the drivers of RSV seasonality is key for de
 veloping future vaccination strategies.\nMethods: We developed a mathemati
 cal model of RSV transmission\, which simulates the sequential re-infectio
 n (SEIRRS4) and uses a flexible Von Mises function to model the seasonal f
 orcing. Using MCMC we fit the model to laboratory confirmed RSV data from 
 2010-2022 from NSW while accounting for the reduced contact rates during t
 he pandemic with Google mobility data. We estimated the baseline transmiss
 ion rate\, its amplitude and shape during RSV season as well as the durati
 on of immunity. The resulting parameter estimates were compared to a fit t
 o 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.\nResults: We
  estimate that RSV dynamics in NSW can be best explained by a high effecti
 ve baseline transmission rate (2.94/d\, 95% CrI 2.73-3.18) and a narrow pe
 ak 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 391-435). Including data from the pandem
 ic period in the fit reduced parameter correlation substantially and impro
 ved parameter identifiability. The continuous vaccination strategy led to 
 more extreme seasonal incidence with a delay in the peak timing and a high
 er amplitude whereas seasonal vaccination flattened the incidence curves.
LOCATION:Hybrid\, CBL Seminar room\, and Zoom https://eng-cam.zoom.us/j/84
 968458381?pwd=TWM5ZkF2bjdBM09jaVlJZHRUTFlFUT09
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