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Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance

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  • Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance

    BMC Infect Dis. 2015 Dec;15(1):789. doi: 10.1186/s12879-015-0789-z. Epub 2015 Mar 1.
    Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance.

    Drumright LN1, Frost SD, Elliot AJ, Catchpole M, Pebody RG, Atkins M, Harrison J, Parker P, Holmes AH.
    Author information

    Abstract

    BACKGROUND:

    Early warning and robust estimation of influenza burden are critical to inform hospital preparedness and operational, treatment, and vaccination policies. Methods to enhance influenza-like illness (ILI) surveillance are regularly reviewed. We investigated the use of hospital staff 'influenza-like absences' (hospital staff-ILA), i.e. absence attributed to colds and influenza, to improve capture of influenza dynamics and provide resilience for hospitals.
    METHODS:

    Numbers and rates of hospital staff-ILA were compared to regional surveillance data on ILI primary-care presentations (15-64 years) and to counts of laboratory confirmed cases among hospitalised patients from April 2008 to April 2013 inclusive. Analyses were used to determine comparability of the ILI and hospital-ILA and how systems compared in early warning and estimating the burden of disease.
    RESULTS:

    Among 20,021 reported hospital-ILA and 4661 community ILI cases, correlations in counts were high and consistency in illness measurements was observed. In time series analyses, both hospital-ILA and ILI showed similar timing of the seasonal component. Hospital-ILA data often commenced and peaked earlier than ILI according to a Bayesian prospective alarm algorithm. Hospital-ILA rates were more comparable to model-based estimates of 'true' influenza burden than ILI.
    CONCLUSIONS:

    Hospital-ILA appears to have the potential to be a robust, yet simple syndromic surveillance method that could be used to enhance estimates of disease burden and early warning, and assist with local hospital preparedness.


    PMID: 25783070 [PubMed - in process] Free full text
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