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

tetano

Editor, Senior Moderator
BMC Infect Dis. 2015 Dec;15(1):789. doi: 10.1186/s12879-015-0789-z. Epub 2015 Mar 1.
[h=1]Assessing the use of hospital staff influenza-like absence (ILA) for enhancing hospital preparedness and national surveillance.[/h] Drumright LN[SUP]1[/SUP], Frost SD, Elliot AJ, Catchpole M, Pebody RG, Atkins M, Harrison J, Parker P, Holmes AH.
[h=3]Author information[/h]

[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] 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.
[h=4]METHODS:[/h] 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.
[h=4]RESULTS:[/h] 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.
[h=4]CONCLUSIONS:[/h] 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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