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- W2917963204 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." @default.
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- W2917963204 date "2019-06-01" @default.
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- W2917963204 title "Burden of hospital admissions caused by respiratory syncytial virus (RSV) in infants in England: A data linkage modelling study" @default.
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- W2917963204 doi "https://doi.org/10.1016/j.jinf.2019.02.012" @default.
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