Respiratory syncytial virus (RSV) causes a large burden of morbidity in young children and the elderly. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving its transmission, including factors that influence epidemic seeding and growth rates. Using hospitalization data from Connecticut, New Jersey, and New York, we estimated epidemic timing at the ZIP code level using harmonic regression and then used a Bayesian meta-regression model to evaluate correlates of epidemic timing. Earlier epidemics were associated with larger household size and greater population density. Nearby localities had similar epidemic timing. Our results suggest that RSV epidemics grow faster in areas with more local contact opportunities, and that epidemic spread follows a spatial diffusion process based on geographic proximity. Our findings can inform the timing of delivery of RSV extended half-life prophylaxis and maternal vaccines and guide future studies on the transmission dynamics of RSV.
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