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.
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.
Authors: Stefan Hagel; Katrin Ludewig; Anne Moeser; Michael Baier; Bettina Löffler; Benjamin Schleenvoigt; Christina Forstner; Mathias W Pletz Journal: Infection Date: 2016-07-05 Impact factor: 3.553
Authors: Andrew Anglemyer; Theresa Hm Moore; Lisa Parker; Timothy Chambers; Alice Grady; Kellia Chiu; Matthew Parry; Magdalena Wilczynska; Ella Flemyng; Lisa Bero Journal: Cochrane Database Syst Rev Date: 2020-08-18
Authors: Moses C Kiti; Michele Tizzoni; Timothy M Kinyanjui; Dorothy C Koech; Patrick K Munywoki; Milosch Meriac; Luca Cappa; André Panisson; Alain Barrat; Ciro Cattuto; D James Nokes Journal: EPJ Data Sci Date: 2016-06-14 Impact factor: 3.184