Burden of hospital admissions caused by respiratory syncytial virus (RSV) in infants in England: A data linkage modelling study

Abstract

Current national estimates of respiratory syncytial virus (RSV)-associated hospital admissions are insufficiently detailed to determine optimal vaccination strategies for RSV. We employ novel methodology to estimate the burden of RSV-associated hospital admissions in infants in England, with detailed stratification by patient and clinical characteristics. We used linked, routinely collected laboratory and hospital data to identify laboratory-confirmed RSV-positive and RSV-negative respiratory hospital admissions in infants in England, then generate a predictive logistic regression model for RSV-associated admissions. We applied this model to all respiratory hospital admissions in infants in England, to estimate the national burden of RSV-associated admissions by calendar week, age in weeks and months, clinical risk group and birth month. We estimated an annual average of 20,359 (95% CI 19,236-22,028) RSV-associated admissions in infants in England from mid-2010 to mid-2012. These admissions accounted for 57,907 (95% CI 55,391-61,637) annual bed days. 55% of RSV-associated bed days and 45% of RSV-associated admissions were in infants <3 months old. RSV-associated admissions peaked in infants aged 6 weeks, and those born September to November. We employed novel methodology using linked datasets to produce detailed estimates of RSV-associated admissions in infants. Our results provide essential baseline epidemiological data to inform future vaccine policy.