Epidemiology and Infection

Childhood infections

A multi-tiered time-series modelling approach to forecasting respiratory syncytial virus incidence at the local level

M. C. SPAEDERa1 c1 and J. C. FACKLERa2

a1 Division of Critical Care Medicine, Children's National Medical Center, Washington, DC, USA

a2 Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD, USA

SUMMARY

Respiratory syncytial virus (RSV) is the most common cause of documented viral respiratory infections, and the leading cause of hospitalization, in young children. We performed a retrospective time-series analysis of all patients aged <18 years with laboratory-confirmed RSV within a network of multiple affiliated academic medical institutions. Forecasting models of weekly RSV incidence for the local community, inpatient paediatric hospital and paediatric intensive-care unit (PICU) were created. Ninety-five percent confidence intervals calculated around our models' 2-week forecasts were accurate to ±9·3, ±7·5 and ±1·5 cases/week for the local community, inpatient hospital and PICU, respectively. Our results suggest that time-series models may be useful tools in forecasting the burden of RSV infection at the local and institutional levels, helping communities and institutions to optimize distribution of resources based on the changing burden and severity of illness in their respective communities.

(Accepted May 06 2011)

(Online publication June 07 2011)

Correspondence:

c1 Author for correspondence: M. C. Spaeder, M.D., M.S., Division of Critical Care Medicine, Children's National Medical Center, 111 Michigan Avenue, NW, Washington, DC 20010, USA (Email: mspaeder@cnmc.org)

Metrics