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Combining High-Resolution Contact Data with Virological Data to Investigate Influenza Transmission in a Tertiary Care Hospital

Published online by Cambridge University Press:  13 January 2015

Nicolas Voirin*
Affiliation:
Service d’Hygiène, Epidémiologie et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France Université de Lyon, Université Lyon 1, Lyon, France
Cécile Payet
Affiliation:
Service d’Hygiène, Epidémiologie et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France Université de Lyon, Université Lyon 1, Lyon, France
Alain Barrat
Affiliation:
Université Aix Marseille, Université de Toulon, CNRS, CPT UMR 7332, 13288 Marseille, France Data Science Laboratory, ISI Foundation, Turin, Italy
Ciro Cattuto
Affiliation:
Data Science Laboratory, ISI Foundation, Turin, Italy
Nagham Khanafer
Affiliation:
Service d’Hygiène, Epidémiologie et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France Université de Lyon, Université Lyon 1, Lyon, France
Corinne Régis
Affiliation:
Université de Lyon, Université Lyon 1, Lyon, France
Byeul-a Kim
Affiliation:
Service de gériatrie, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
Brigitte Comte
Affiliation:
Service de gériatrie, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
Jean-Sébastien Casalegno
Affiliation:
Université de Lyon, Université Lyon 1, Lyon, France Laboratoire de Virologie, Centre National de Référence des Virus Influenzae, Hospices Civils de Lyon, Lyon, France Virpath, EA4610, Faculté de Médecine Lyon Est (site Laennec), Université Claude Bernard Lyon 1, 69372 Lyon Cedex 08, France
Bruno Lina
Affiliation:
Université de Lyon, Université Lyon 1, Lyon, France Laboratoire de Virologie, Centre National de Référence des Virus Influenzae, Hospices Civils de Lyon, Lyon, France Virpath, EA4610, Faculté de Médecine Lyon Est (site Laennec), Université Claude Bernard Lyon 1, 69372 Lyon Cedex 08, France
Philippe Vanhems
Affiliation:
Service d’Hygiène, Epidémiologie et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France Université de Lyon, Université Lyon 1, Lyon, France
*
Address correspondence to Dr. Nicolas Voirin, Service d’Hygiène, Epidémiologie et Prévention, Unité Epidémiologie et Biomarqueurs de l'Infection, Hôpital Edouard Herriot, Hospices Civils de Lyon; Equipe Epidémiologie et Santé Publique, Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon; Université Lyon 1; CNRS, UMR 5558, 5, place d'Arsonval, 69437 Lyon cedex 03 (nicolas.voirin@chu-lyon.fr).

Abstract

OBJECTIVE

Contact patterns and microbiological data contribute to a detailed understanding of infectious disease transmission. We explored the automated collection of high-resolution contact data by wearable sensors combined with virological data to investigate influenza transmission among patients and healthcare workers in a geriatric unit.

DESIGN

Proof-of-concept observational study. Detailed information on contact patterns were collected by wearable sensors over 12 days. Systematic nasopharyngeal swabs were taken, analyzed for influenza A and B viruses by real-time polymerase chain reaction, and cultured for phylogenetic analysis.

SETTING

An acute-care geriatric unit in a tertiary care hospital.

PARTICIPANTS

Patients, nurses, and medical doctors.

RESULTS

A total of 18,765 contacts were recorded among 37 patients, 32 nurses, and 15 medical doctors. Most contacts occurred between nurses or between a nurse and a patient. Fifteen individuals had influenza A (H3N2). Among these, 11 study participants were positive at the beginning of the study or at admission, and 3 patients and 1 nurse acquired laboratory-confirmed influenza during the study. Infectious medical doctors and nurses were identified as potential sources of hospital-acquired influenza (HA-Flu) for patients, and infectious patients were identified as likely sources for nurses. Only 1 potential transmission between nurses was observed.

CONCLUSIONS

Combining high-resolution contact data and virological data allowed us to identify a potential transmission route in each possible case of HA-Flu. This promising method should be applied for longer periods in larger populations, with more complete use of phylogenetic analyses, for a better understanding of influenza transmission dynamics in a hospital setting.

Infect Control Hosp Epidemiol 2015;00(0): 1–7

Type
Original Articles
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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