Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors

Contacts between patients, patients and health care workers (HCWs) and among HCWs represent one of the important routes of transmission of hospital-acquired infections (HAI). A detailed description and quantification of contacts in hospitals provides key information for HAIs epidemiology and for the design and validation of control measures. We used wearable sensors to detect close-range interactions ("contacts") between individuals in the geriatric unit of a university hospital. Contact events were measured with a spatial resolution of about 1.5 meters and a temporal resolution of 20 seconds. The study included 46 HCWs and 29 patients and lasted for 4 days and 4 nights. 14037 contacts were recorded. The number and duration of contacts varied between mornings, afternoons and nights, and contact matrices describing the mixing patterns between HCW and patients were built for each time period. Contact patterns were qualitatively similar from one day to the next. 38% of the contacts occurred between pairs of HCWs and 6 HCWs accounted for 42% of all the contacts including at least one patient, suggesting a population of individuals who could potentially act as super-spreaders. Wearable sensors represent a novel tool for the measurement of contact patterns in hospitals. The collected data provides information on important aspects that impact the spreading patterns of infectious diseases, such as the strong heterogeneity of contact numbers and durations across individuals, the variability in the number of contacts during a day, and the fraction of repeated contacts across days. This variability is associated with a marked statistical stability of contact and mixing patterns across days. Our results highlight the need for such measurement efforts in order to correctly inform mathematical models of HAIs and use them to inform the design and evaluation of prevention strategies

La problématique du cannabis en médecine générale (une enquête d'opinion auprès des médecins généralistes du Rhône)

LYON1-BU Santé (693882101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Five years of hospital based surveillance of influenza-like illness and influenza in a short-stay geriatric unit

International audienceBackgroundData on influenza in the healthcare setting are often based on retrospective investigations of outbreaks and a few studies described influenza during several consecutive seasons.The aim of the present work is to report data on influenza like illness (ILI) and influenza from 5-year prospective surveillance in a short-stay geriatrics unit.FindingsA short stay geriatrics unit underwent 5 years of ILI surveillance from November 2004 to March 2009, with the aim of describing ILI in a non-outbreak context. The study was proposed to patients who presented ILI, defined as fever >37.8°C or cough or sore throat. Among 1,353 admitted patients, 115 presented an ILI, and 34 had hospital-acquired ILI (HA-ILI). Influenza was confirmed in 23 patients, 13 of whom had been vaccinated. Overall attack rates were 2.78% and 0.02% for HA-ILI and HA-confirmed influenza respectively, during the 5 seasons.ConclusionsThis 5-year surveillance study supports the notion that influenza infections are common in hospitals, mostly impacting the elderly hospitalized in short-stay units. It highlights the need for appropriate control measures to prevent HA-ILI in geriatric units and protect elderly patients

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

International audienceobjective. 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

RCP dédiée à l’onco-gériatrie : décisions et suivi à quatre mois

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Number of distinct patients contacted, number and cumulative duration (in seconds) of contacts with at least one patient for each HCW (NURs and MEDs).

<p>“Super-contactors” are defined as individuals with the highest number of contacts. Here for instance, six HCWs account for more than 40% of the cumulative total of contact numbers and durations. Abbreviations: HCW, healthcare worker; NUR, paramedical staff (nurses and nurses’ aides); MED, Medical doctor.</p

Contacts matrices giving the numbers (left column) and cumulated durations in seconds (right column) of the contacts between classes of individuals.

<p>In the first line, the matrix entry at row X and column Y gives the total number (resp. duration) of all contacts between all individuals of class with all individuals of class Y. In the second line, the matrix entry at row X and column Y gives the average number (resp. duration) of contacts of an individual of class X with individuals of class Y, during the whole study. In the third line, we normalize each matrix element of the second line matrices by the duration of the study, in days, to obtain average daily numbers and durations of the contacts of an individual of class X with any individual of class Y. The asymmetry of the matrices in the second and third lines is due to the different numbers of individuals populating each class. Abbreviations: NUR, paramedical staff (nurses and nurses’ aides); PAT, Patient; MED, Medical doctor; ADM, administrative staff.</p