Date of Award
1-1-2016
Document Type
Open Access Thesis
Degree Name
Master of Public Health (MPH)
Department
School of Public Health
First Advisor
Daniel M. Weinberger
Abstract
Introduction: Respiratory syncytial virus (RSV) is a primary cause of hospitalizations in children worldwide. Prophylaxis (Palivizumab) can be given to infants who are at high-risk of a severe RSV infection, but the timing of seasonal RSV epidemics need to be known in order to administer prophylaxis at the appropriate time.
Methods: This study used data from the Connecticut State Inpatient Database to identify RSV hospitalizations based on ICD-9 diagnosis codes. A harmonic regression analysis was used to evaluate RSV epidemic timing at the county level; subsequently, a hierarchical model was fit to assess RSV epidemic timing at the ZIP code level. Finally, a linear regression model was used to investigate demographic characteristics that were predictive of RSV epidemic timing.
Results: 9,740 hospitalizations coded as RSV occurred among children less than 2 years old in Connecticut between July 1, 1997 and June 30, 2013. The seasonal RSV epidemic in the earliest county (Fairfield County) peaked 2.55 weeks earlier than the latest county (Tolland County). The earliest ZIP code had a seasonal RSV epidemic that peaked 4.64 weeks earlier than the latest ZIP code. Demographic characteristics that were significantly associated with ZIP code level RSV peak-timing included population density of childrenblack.
Conclusions: Seasonal RSV epidemics in Connecticut occurred earlier in areas that were more urban, had higher population density, and larger black populations. These findings could be used to better time the administration of prophylaxis to high-risk infants.
Recommended Citation
Noveroske, Douglas Brian, "Respiratory Syncytial Virus In Connecticut: Predictors Of Seasonal Epidemic Timing" (2016). Public Health Theses. 1213.
https://elischolar.library.yale.edu/ysphtdl/1213
This Article is Open Access