Community factors associated with local RSV epidemic patterns: a spatiotemporal modeling study
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This study found that early RSV epidemic timing in New York, New Jersey, and Connecticut was associated with larger household sizes and higher population density, with epidemic spread primarily driven by geographic proximity.
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Abstract
ABSTRACT Background Respiratory syncytial virus (RSV) causes a large burden of morbidity in infants, young children, and the elderly. The timing of RSV seasonal epidemics exhibits strong spatial patterns within the United States. Spatial variability in the timing of RSV epidemics provides an opportunity to probe the factors driving transmission of the virus. Methods We evaluated competing hypotheses about the associations between RSV epidemic timing at the ZIP-code level and household size, population density, school district boundaries, commuting patterns, and geographic proximity. We used hierarchical Bayesian models with monthly ZIP-code level hospitalization data from New York, New Jersey, and Connecticut between July 1997 and June 2014 to investigate these hypotheses. Results Early epidemic timing across ZIP codes was associated with large household sizes and high population density, and nearby ZIP codes shared similar epidemic timing. Variations in epidemic timing attributed to commuting patterns or school district boundaries are negligible. Conclusion Our results suggest RSV epidemics take off faster in areas with more household crowding and higher population density, and that epidemic spread follows a spatial diffusion process based on geographic proximity. With several vaccines against RSV under development, it is important to understand the drivers of RSV transmission and disease in order to maximize population protection of a vaccine program. Our findings can inform more effective control measures against RSV, such as vaccine programs and household infection control, and guide future studies on the transmission dynamics of RSV.
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