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Open Access Research article

A multiplicative hazard regression model to assess the risk of disease transmission at hospital during community epidemics

Nicolas Voirin12*, Sylvain Roche34, Philippe Vanhems12, Marine Giard12, Sandra David-Tchouda34, Béatrice Barret5 and René Ecochard34

Author Affiliations

1 Hospices Civils de Lyon, Service d'Hygiène, Epidémiologie et Prévention, Unité Epidémiologie et Biomarqueurs de l'Infection, Lyon, France

2 Université de Lyon; Université Lyon I; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Epidémiologie et Santé Publique, Villeurbanne, France

3 Hospices Civils de Lyon, Service de Biostatistique, Lyon, France

4 Université de Lyon; Université Lyon I; CNRS, UMR5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistiques Santé, Villeurbanne, France

5 Independent practitioner, Lyon, F-69001, France

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BMC Medical Research Methodology 2011, 11:53  doi:10.1186/1471-2288-11-53

Published: 20 April 2011

Abstract

Background

During community epidemics, infections may be imported within hospital and transmitted to hospitalized patients. Hospital outbreaks of communicable diseases have been increasingly reported during the last decades and have had significant consequences in terms of patient morbidity, mortality, and associated costs. Quantitative studies are thus needed to estimate the risks of communicable diseases among hospital patients, taking into account the epidemiological process outside, hospital and host-related risk factors of infection and the role of other patients and healthcare workers as sources of infection.

Methods

We propose a multiplicative hazard regression model to analyze the risk of acquiring a communicable disease by patients at hospital. This model derives from epidemiological data on communicable disease epidemics in the community, hospital ward, patient susceptibility to infection, and exposure of patients to infection at hospital. The model estimates the relative effect of each of these factors on a patient's risk of communicable disease.

Results

Using individual data on patients and health care workers in a teaching hospital during the 2004-2005 influenza season in Lyon (France), we show the ability of the model to assess the risk of influenza-like illness among hospitalized patients. The significant effects on the risk of influenza-like illness were those of old age, exposure to infectious patients or health care workers, and a stay in a medical care unit.

Conclusions

The proposed multiplicative hazard regression model could be an interesting epidemiological tool to quantify the risk of communicable disease at hospital during community epidemics and the uncertainty inherent in such quantification. Furthermore, key epidemiological, environmental, host, or exposure factors that influence this risk can be identified.