Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.
Bibliographical noteFunding Information:
The authors have no conflicts of interest to disclose. RMR, PH and RP designed the study. NP and MM carried out the data linkage. RMR was responsible for data analysis and drafted the manuscript. RMR, PH, RP and FW contributed to data analysis methodology and interpretation. All authors reviewed and edited the final manuscript. The funder had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all data in the study and had final responsibility for the decision to submit for publication. Farr Institute of Health Informatics Research (grant MR/K006584/1).
- Data linkage
- Hospital admissions
- Respiratory syncytial virus
- Respiratory tract infection