ArticleScientific reports2018
Measuring dynamic social contacts in a rehabilitation hospital: effect of wards, patient and staff characteristics.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 23 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
23 citing papers in PubMed, 53 citations in OpenAlex.
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- Comparison of contact diaries and wearable proximity sensors in measuring household contacts in low- and middle-income countries.medRxiv : the preprint server for health sciences · 2025Article
- Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review.Infectious Disease Modelling · 2025Review
- Evolution of social contacts patterns in France over the SARS-CoV-2 pandemic: results from the SocialCov survey.BMC infectious diseases · 2025Article
- Using contact network dynamics to implement efficient interventions against pathogen spread in hospital settings: A modelling study.PLoS medicine · 2024Article
- An algorithm to build synthetic temporal contact networks based on close-proximity interactions data.PLoS computational biology · 2024Article
- Assessing respiratory epidemic potential in French hospitals through collection of close contact data (April-June 2020).Scientific reports · 2024Article
- Influenza transmissibility among patients and health-care professionals in a geriatric short-stay unit using individual contact data.Scientific reports · 2023Article
- Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic.Communications medicine · 2022Article
- Longitudinal data collection to follow social network and language development dynamics at preschool.Scientific data · 2022Article
- Epidemic management and control through risk-dependent individual contact interventions.PLoS computational biology · 2022Article
- Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach.International journal of environmental research and public health · 2022Article
- Measuring close proximity interactions in summer camps during the COVID-19 pandemic.EPJ data science · 2022Article
- Reorganization of nurse scheduling reduces the risk of healthcare associated infections.Scientific reports · 2021Article
- Sensor-based proximity metrics for team research. A validation study across three organizational contexts.Behavior research methods · 2021Article
- Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project.Journal of clinical medicine · 2021Article
- A Conceptual Discussion About the Basic Reproduction Number of Severe Acute Respiratory Syndrome Coronavirus 2 in Healthcare Settings.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Efficient SARS-CoV-2 surveillance strategies to prevent deadly outbreaks in vulnerable populations.BMC medicine · 2021Article
- What containment strategy leads us through the pandemic crisis? An empirical analysis of the measures against the COVID-19 pandemic.PloS one · 2021Article
- Optimizing COVID-19 surveillance in long-term care facilities: a modelling study.BMC medicine · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 11 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding transmission routes of hospital-acquired infections (HAI) is key to improve their control. In this context, describing and analyzing dynamic inter-individual contact patterns in hospitals is essential. In this study, we used wearable sensors to detect Close Proximity Interactions (CPIs) among patients and hospital staff in a 200-bed long-term care facility over 4 months. First, the dynamic CPI data was described in terms of contact frequency and duration per individual status or activity and per ward. Second, we investigated the individual factors associated with high contact frequency or duration using generalized linear mixed-effect models to account for inter-ward heterogeneity. Hospital porters and physicians had the highest daily number of distinct contacts, making them more likely to disseminate HAI among individuals. Conversely, contact duration was highest between patients, with potential implications in terms of HAI acquisition risk. Contact patterns differed among hospital wards, reflecting varying care patterns depending on reason for hospitalization, with more frequent contacts in neurologic wards and fewer, longer contacts in geriatric wards. This study is the first to report proximity-sensing data informing on inter-individual contacts in long-term care settings. Our results should help better understand HAI spread, parameterize future mathematical models, and propose efficient control strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.