4.4 Article

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

Journal

INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY
Volume 36, Issue 3, Pages 254-260

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/ice.2014.53

Keywords

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Funding

  1. FINOVI Foundation (Lyon)
  2. INSERM IMI Pandemic Program
  3. French ANR project HarMS-flu [ANR-12-MONU-0018]
  4. EU FET project [317532]

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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.

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