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Influenza Other Respir Viruses . Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010

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  • Influenza Other Respir Viruses . Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010


    Influenza Other Respir Viruses


    . 2021 May 4.
    doi: 10.1111/irv.12863. Online ahead of print.
    Changes in characteristics and case-severity in patients hospitalised with influenza A (H1N1) pdm09 infection between two epidemic waves-England, 2009-2010


    Ian D Plumb 1 2 , Ross Harris 1 , Helen K Green 1 , Joanna Ellis 1 , Kathy Baisley 2 , Richard G Pebody 1



    Affiliations

    Abstract

    Background: During 2009-2010, pandemic influenza A (H1N1) pdm09 virus (pH1N1) infections in England occurred in two epidemic waves. Reasons for a reported increase in case-severity during the second wave are unclear.
    Methods: We analysed hospital-based surveillance for patients with pH1N1 infections in England during 2009-2010 and linked national data sets to estimate ethnicity, socio-economic status and death within 28 days of admission. We used multivariable logistic regression to assess whether changes in demographic, clinical and management characteristics of patients could explain an increase in ICU admission or death, and accounted for missing values using multiple imputation.
    Results: During the first wave, 54/960 (6%) hospitalised patients required intensive care and 21/960 (2%) died; during the second wave 143/1420 (10%) required intensive care and 55/1420 (4%) died. In a multivariable model, during the second wave patients were less likely to be from an ethnic minority (OR 0.33, 95% CI 0.26-0.42), have an elevated deprivation score (OR 0.75, 95% CI 0.68-0.83), have known comorbidity (OR 0.78, 95% CI 0.63-0.97) or receive antiviral therapy ?2 days before onset (OR 0.72, 95% CI 0.56-0.92). Increased case-severity during the second wave was not explained by changes in demographic, clinical or management characteristics.
    Conclusions: Monitoring changes in patient characteristics could help target interventions during multiple waves of COVID-19 or a future influenza pandemic. To understand and respond to changes in case-severity, surveillance is needed that includes additional factors such as admission thresholds and seasonal coinfections.

    Keywords: comorbidity; hospitalisation; influenza A virus; pandemics; risk factors; socio-economic factors.

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