Estimating the burden of respiratory syncytial virus (RSV) on respiratory hospital admissions in children less than five years of age in England, 2007‐2012. Issue 2 (21st January 2017) - Reeves, Rachel Melanie; Hardelid, Pia; Gilbert, Ruth; Warburton, Fiona; Ellis, Joanna; Pebody, Richard G.
Abstract : Background: Respiratory syncytial virus (RSV) is a leading cause of hospital admission in young children. With several RSV vaccines candidates undergoing clinical trials, recent estimates of RSV burden are required to provide a baseline for vaccine impact studies. Objectives: To estimate the number of RSV‐associated hospital admissions in children aged <5 years in England over a 5‐year period from 2007 using ecological time series modelling of national hospital administrative data. Patients/Methods: Multiple linear regression modelling of weekly time series of laboratory surveillance data and Hospital Episode Statistics (HES) data was used to estimate the number of hospital admissions due to major respiratory pathogens including RSV in children <5 years of age in England from mid‐2007 to mid‐2012, stratified by age group (<6 months, 6‐11 months, 1‐4 years) and primary diagnosis: bronchiolitis, pneumonia, unspecified lower respiratory tract infection (LRTI), bronchitis and upper respiratory tract infection (URTI). Results: On average, 33 561 (95% confidence interval 30 429‐38 489) RSV‐associated hospital admissions in children <5 years of age occurred annually from 2007 to 2012. Average annual admission rates were 35.1 (95% CI: 32.9‐38.9) per 1000 children aged <1 year and 5.31 (95% CI: 4.5‐6.6) per 1000 children aged 1‐4 years. About 84% (95% CI: 81‐91%) of RSV‐associated admissions were for LRTI. The diagnosis‐specific burden of RSV‐associated admissions differed significantly by age group. Conclusions: RSV remains a significant cause of hospital admissions in young children in England. Individual‐level analysis of RSV‐associated admissions is required to fully describe the burden by age and risk group and identify optimal prevention strategies.