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Close encounters in a pediatric ward: measuring face-to-face proximity and mixing patterns with wearable sensors
Lorenzo Isella1, Mariateresa Romano, Alain Barrat
1Complex Networks and Systems Group, Institute for Scientific Interchange Foundation, Torino, Italy.
Insights
Wearable RFID devices precisely tracked hospital contacts, revealing nurses are key to infection spread. This data aids in developing targeted prevention strategies for nosocomial infections.
Area of Science:
- Epidemiology
- Infectious Disease Transmission
- Healthcare Management
Background:
- Nosocomial infections are a significant public health concern, necessitating effective prevention strategies.
- Understanding contact dynamics within hospitals is crucial for predicting and controlling infection spread.
- Accurate contact data is essential for informing mathematical models of disease transmission.
Purpose of the Study:
- To measure face-to-face contact patterns among individuals in a hospital ward.
- To identify key individuals and contact types relevant to infection transmission.
- To evaluate the feasibility of using proximity-sensing technology for this purpose.
Main Methods:
- Utilized wearable active Radio-Frequency Identification Devices (RFID) to record proximity contacts.
- Achieved high spatial (1.5m) and temporal (20s) resolution in contact detection.
- Conducted a one-week study in a pediatric ward with 119 participants (HCWs, patients, caregivers).
Main Results:
- Recorded nearly 16,000 contacts, with a median of 20 contacts per participant daily.
- Identified nurses (23%) and patients (22%) as frequently involved in contacts.
- Found caregivers' contacts were primarily patient-focused, limiting broad spread potential.
- Highlighted nurses' central role in potential infection propagation paths.
Conclusions:
- Demonstrated the feasibility of accurately measuring hospital contact patterns using RFID technology.
- Results are valuable for studying respiratory infection spread and tailoring prevention strategies.
- Proximity-sensing technology is a promising tool for evaluating nosocomial infection control measures.
Background:
Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals.
Methods And Findings:
We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25% of the contacts involved a ward assistant, 23% a nurse, 22% a patient, 22% a caregiver, and 8% a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections.
Conclusions:
Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings.
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