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Keywords:

  • Case–hospitalization ratio;
  • emerging pathogens;
  • influenza pandemics;
  • severity;
  • surveillance

Please cite this paper as: Pelat et al. (2012) Hospitalization of influenza-like illness patients recommended by general practitioners in France between 1997 and 2010. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750-2659.2012.00356.x.

Background  The case–hospitalization ratio (CHR) is a key quantity for the management of emerging pathogens such as pandemic influenza. Yet, few running surveillance systems prospectively monitor the CHR during influenza epidemics. Here, we analyze the proportion of recommended hospitalizations (PRH) among influenza-like illness (ILI) patients attended in general practice in France and compare the PRH observed during the 2009–2010 A(H1N1) pandemic with the one of the twelve previous seasons.

Methods  ILI cases were recorded by general practitioners (GPs) involved in surveillance, who indicated for each case whether they recommended hospitalization. We stratify the analysis by age, sex, and viral subtype. We investigate the reasons why GPs recommended hospitalization and the presence of risk factors for pandemic A(H1N1) complications.

Results  The average PRH over the seasons 1997–1998 to 2008–2009 was 3·4‰ (3–3·9). It was three times higher during the 2009–2010 pandemic than during seasonal influenza epidemics (OR = 2·89, 95% CI: 2·28–3·64). The highest increase was among 20–39-year-old women: OR = 11·8 (5·04–29·59). Overall, the principal reasons for recommending hospitalization were “respiratory problems” and “bad general condition.” However, during the pandemic, “age” (mainly associated with infants), “pregnancy,” and “diagnostic” became more frequent than before (P < 0·001). Finally, pregnancy was the reported risk factor for pandemic A(H1N1) complications that had the largest impact on hospitalization recommendation during the pandemic (OR = 38·62, P < 0·001).

Conclusion  Easily implemented in surveillance systems, this protocol has the potential to reveal changes in hospitalization recommendation by GPs. Moreover, if the right data are collected alongside, it could give timely insights into epidemic severity.