ArticleEmerging infectious diseases2009
Nurses' contacts and potential for infectious disease transmission.
Article in Emerging infectious diseases, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.Epidemiology (Cambridge, Mass.) · 2019Pooled it
- Pooled it
- Social contact patterns in South Korea: an analysis of a survey conducted in 2023-2024.BMC infectious diseases · 2025Article
- Characterization and assessment of exposure risks of healthcare personnel during the COVID-19 pandemic.Journal of family medicine and primary care · 2024Article
- The influence of COVID-19-related resilience on depression, job stress, sleep quality, and burnout among intensive care unit nurses.Frontiers in psychology · 2023Article
- Perceived Causes of Work-Related Sick Leave Among Hospital Nurses in Norway: A Prepandemic Study.Safety and health at work · 2022Article
- Interventions to control nosocomial transmission of SARS-CoV-2: a modelling study.BMC medicine · 2021Article
- Reorganization of nurse scheduling reduces the risk of healthcare associated infections.Scientific reports · 2021Article
- Topical exposure to triclosan inhibits Th1 immune responses and reduces T cells responding to influenza infection in mice.PloS one · 2020Article
- Quantifying heterogeneous contact patterns in Japan: a social contact survey.Theoretical biology & medical modelling · 2019Article
- Molecular characterization of a nosocomial outbreak of influenza B virus in an acute care hospital setting.The Journal of hospital infection · 2019Article
- Disease persistence on temporal contact networks accounting for heterogeneous infectious periods.Royal Society open science · 2019Article
- An evaluation of the effectiveness of nursing students' hand hygiene compliance: A cross-sectional study.Nurse education today · 2018Article
- Contact among healthcare workers in the hospital setting: developing the evidence base for innovative approaches to infection control.BMC infectious diseases · 2018Article
- Infectious disease transmission: survey of contacts between hospital-based healthcare workers and working adults from the general population.The Journal of hospital infection · 2018Article
- Contacts of healthcare workers, patients and visitors in general wards in Singapore.Epidemiology and infection · 2017Article
- Essentials of infection prevention in the pediatric population.International journal of pediatrics & adolescent medicine · 2016Review
- How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?PLoS computational biology · 2016Article
- Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys.PloS one · 2015Article
- Healthcare worker contact networks and the prevention of hospital-acquired infections.PloS one · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nurses' contacts with potentially infectious persons probably place them at higher risk than the general population for infectious diseases. During an influenza pandemic, illness among nurses might result in staff shortage. We aimed to show the value of individual data from the healthcare sector for mathematical modeling of infectious disease transmission. Using a paper diary approach, we compared nurses' daily contacts (2-way conversation with >2 words or skin-to-skin contact) with those of matched controls from a representative population survey. Nurses (n = 129) reported a median of 40 contacts (85% work related), and controls (n = 129) reported 12 contacts (33% work related). For nurses, 51% of work-related contacts were with patients (74% involving skin-to-skin contact, and 63% lasted < or =15 minutes); 40% were with staff members (29% and 36%, respectively). Our data, used with simulation models, can help predict staff availability and provide information for pandemic preparedness planning.
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