R M Reeves1, P Hardelid2, N Panagiotopoulos3, M Minaji3, F Warburton3, R Pebody4. 1. Farr Institute of Health Informatics Research, London, UK; Institute of Child Health, University College London, London, UK; Respiratory Diseases Department, Public Health England, Colindale, London, UK. Electronic address: rachel.reeves@ed.ac.uk. 2. Farr Institute of Health Informatics Research, London, UK; Institute of Child Health, University College London, London, UK. 3. Statistics and Modelling Economics Department, Public Health England, Colindale, London, UK. 4. Respiratory Diseases Department, Public Health England, Colindale, London, UK.
Abstract
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.
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.
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