a1 Service d’Hygiène, Epidémiologie et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
a2 Université de Lyon, Université Lyon 1, Lyon, France
a3 Université Aix Marseille, Université de Toulon, CNRS, CPT UMR 7332, 13288 Marseille, France
a4 Data Science Laboratory, ISI Foundation, Turin, Italy
a5 Service de gériatrie, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
a6 Laboratoire de Virologie, Centre National de Référence des Virus Influenzae, Hospices Civils de Lyon, Lyon, France
a7 Virpath, EA4610, Faculté de Médecine Lyon Est (site Laennec), Université Claude Bernard Lyon 1, 69372 Lyon Cedex 08, France
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
(Received August 12 2014)
(Accepted October 26 2014)
(Online publication January 13 2015)
Correspondence
c1 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).