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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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References

REFERENCES

1.Eibach, D, Casalegno, JS, Bouscambert, M, et al. Routes of transmission during a nosocomial influenza A(H3N2) outbreak among geriatric patients and healthcare workers. J Hosp Infect 2014;86:188193.Google Scholar
2.Jonges, M, Rahamat-Langendoen, J, Meijer, A, Niesters, HG, Koopmans, M. Sequence-based identification and characterization of nosocomial influenza A(H1N1)pdm09 virus infections. J Hosp Infect 2012;82:187193.Google Scholar
3.Oguma, T, Saito, R, Masaki, H, et al. Molecular characteristics of outbreaks of nosocomial infection with influenza A/H3N2 virus variants. Infect Control Hosp Epidemiol 2011;32:267275.CrossRefGoogle ScholarPubMed
4.Rodriguez-Sanchez, B, Alonso, M, Catalan, P, et al. Genotyping of a nosocomial outbreak of pandemic influenza A/H1N1 2009. J Clin Virol 2011;52:129132.Google Scholar
5.Wong, BC, Lee, N, Li, Y, et al. Possible role of aerosol transmission in a hospital outbreak of influenza. Clin Infect Dis 2010;51:11761183.CrossRefGoogle Scholar
6.Barrat, A, Cattuto, C, Tozzi, AE, Vanhems, P, Voirin, N. Measuring contact patterns with wearable sensors: methods, data characteristics and applications to data-driven simulations of infectious diseases. Clin Microbiol Infect 2014;20:1016.Google Scholar
7.Read, JM, Edmunds, WJ, Riley, S, Lessler, J, Cummings, DA. Close encounters of the infectious kind: methods to measure social mixing behaviour. Epidemiol Infect 2012;140:21172130.Google Scholar
8.Cattuto, C, Van den Broeck, W, Barrat, A, Colizza, V, Pinton, JF, Vespignani, A. Dynamics of person-to-person interactions from distributed RFID sensor networks. PLoS One 2010;5:e11596.Google Scholar
9.Isella, L, Romano, M, Barrat, A, et al. Close encounters in a pediatric ward: measuring face-to-face proximity and mixing patterns with wearable sensors. PLoS One 2011;6:e17144.Google Scholar
10.Stehle, J, Voirin, N, Barrat, A, et al. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees. BMC Med 2011;9:87.CrossRefGoogle ScholarPubMed
11.Stehle, J, Voirin, N, Barrat, A, et al. High-resolution measurements of face-to-face contact patterns in a primary school. PLoS One 2011;6:e23176.Google Scholar
12.Vanhems, P, Barrat, A, Cattuto, C, et al. Estimating potential infection transmission routes in hospital wards using wearable proximity sensors. PLoS One 2013;8:e73970.CrossRefGoogle ScholarPubMed
13.Monto, AS, Gravenstein, S, Elliott, M, Colopy, M, Schweinle, J. Clinical signs and symptoms predicting influenza infection. Arch Intern Med 2000;160:32433247.Google Scholar
14.Carrat, F, Vergu, E, Ferguson, NM, et al. Time lines of infection and disease in human influenza: a review of volunteer challenge studies. Am J Epidemiol 2008;167:775785.Google Scholar
15.Régis, C, Gorain, C, Pires-Cronenberger, S, et al. La grippe nosocomiale chez les adultes à l'hôpital Edouard Herriot, Lyon (France), hivers 2004–2005, 2005–2006 et 2006–2007. BEH 2008;34:308311.Google Scholar
16.Smieszek, T, Burri, EU, Scherzinger, R, Scholz, RW. Collecting close-contact social mixing data with contact diaries: reporting errors and biases. Epidemiol Infect 2012;140:744752.CrossRefGoogle ScholarPubMed
17.Bernard, H, Fischer, R, Mikolajczyk, RT, Kretzschmar, M, Wildner, M. Nurses’ contacts and potential for infectious disease transmission. Emerg Infect Dis 2009;15:14381444.CrossRefGoogle ScholarPubMed
18.Curtis, DE, Hlady, CS, Kanade, G, Pemmaraju, SV, Polgreen, PM, Segre, AM. Healthcare worker contact networks and the prevention of hospital-acquired infections. PLoS One 2013;8:e79906.CrossRefGoogle ScholarPubMed
19.Polgreen, PM, Tassier, TL, Pemmaraju, SV, Segre, AM. Prioritizing healthcare worker vaccinations on the basis of social network analysis. Infect Control Hosp Epidemiol 2010;31:893900.CrossRefGoogle ScholarPubMed
20.Hornbeck, T, Naylor, D, Segre, AM, Thomas, G, Herman, T, Polgreen, PM. Using sensor networks to study the effect of peripatetic healthcare workers on the spread of hospital-associated infections. J Infect Dis 2012;206:15491557.CrossRefGoogle Scholar
21.Truscott, J, Fraser, C, Hinsley, W, et al. Quantifying the transmissibility of human influenza and its seasonal variation in temperate regions. PLoS Curr 2009;1:RRN1125.Google Scholar
22.Siegel, JD, Rhinehart, E, Jackson, M, Chiarello, L. 2007 Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Health Care Settings. Am J Infect Control 2007;35:S65S164.Google Scholar
23.Funk, S, Gilad, E, Watkins, C, Jansen, VA. The spread of awareness and its impact on epidemic outbreaks. Proc Natl Acad Sci U S A 2009;106:68726877.CrossRefGoogle ScholarPubMed
24.Funk, S, Salathe, M, Jansen, VA. Modelling the influence of human behaviour on the spread of infectious diseases: a review. J R Soc Interface 2010;7:12471256.CrossRefGoogle ScholarPubMed
25.Brankston, G, Gitterman, L, Hirji, Z, Lemieux, C, Gardam, M. Transmission of influenza A in human beings. Lancet Infect Dis 2007;7:257265.Google Scholar
26.Killingley, B, Enstone, JE, Greatorex, J, et al. Use of a human influenza challenge model to assess person-to-person transmission: proof-of-concept study. J Infect Dis 2012;205:3543.CrossRefGoogle ScholarPubMed
27.Vanhems, P, Voirin, N, Roche, S, et al. Risk of influenza-like illness in an acute health care setting during community influenza epidemics in 2004–2005, 2005–2006, and 2006–2007: a prospective study. Arch Intern Med 2011;171:151157.Google Scholar
28.Cauchemez, S, Bhattarai, A, Marchbanks, TL, et al. Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza. Proc Natl Acad Sci U S A 2011;108:28252830.Google Scholar
29.Gardy, JL, Johnston, JC, Ho Sui, SJ, et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med 2011;364:730739.Google Scholar