High-resolution measurements of face-to-face contact patterns in a primary school (1109.1015v1)

Abstract: Little quantitative information is available on the mixing patterns of children in school environments. Describing and understanding contacts between children at school would help quantify the transmission opportunities of respiratory infections and identify situations within schools where the risk of transmission is higher. We report on measurements carried out in a French school (6-12 years children), where we collected data on the time-resolved face-to-face proximity of children and teachers using a proximity-sensing infrastructure based on radio frequency identification devices. Data on face-to-face interactions were collected on October 1st and 2nd, 2009. We recorded 77,602 contact events between 242 individuals. Each child has on average 323 contacts per day with 47 other children, leading to an average daily interaction time of 176 minutes. Most contacts are brief, but long contacts are also observed. Contacts occur mostly within each class, and each child spends on average three times more time in contact with classmates than with children of other classes. We describe the temporal evolution of the contact network and the trajectories followed by the children in the school, which constrain the contact patterns. We determine an exposure matrix aimed at informing mathematical models. This matrix exhibits a class and age structure which is very different from the homogeneous mixing hypothesis. The observed properties of the contact patterns between school children are relevant for modeling the propagation of diseases and for evaluating control measures. We discuss public health implications related to the management of schools in case of epidemics and pandemics. Our results can help define a prioritization of control measures based on preventive measures, case isolation, classes and school closures, that could reduce the disruption to education during epidemics.

• The paper quantifies over 77,000 RFID-recorded face-to-face contacts among 242 participants, offering high-resolution insights into daily interactions.
• The study reveals that contact patterns are strongly structured by class and age, with most interactions occurring within the same groups and during breaks.
• Findings challenge homogeneous mixing assumptions by highlighting heterogeneous temporal and spatial dynamics, informing targeted strategies for epidemic control.

High-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School: Implications for Epidemiological Models

This paper, authored by Juliette Stehlé and collaborators, provides comprehensive quantitative data on face-to-face interactions within a primary school setting. The researchers employed a sophisticated proximity-sensing infrastructure based on radio-frequency identification (RFID) devices to capture time-resolved contact data among children and teachers. The data collected is highly significant for modeling the spread of respiratory infections and evaluating potential control measures within school environments.

Methodology and Data Collection

The paper took place over two days in October 2009, involving 242 individuals (232 children and 10 teachers) from a primary school in Lyon, France. Each participant wore an RFID badge capable of detecting face-to-face proximity within a range of approximately 1 to 1.5 meters. The infrastructure captured a remarkable 77,602 contact events, allowing for a granular analysis of interaction patterns.

Key details of the methodology include:

• RFID Infrastructure: The RFID devices exchanged radio packets every 20 seconds when in proximity, providing a detailed temporal resolution of interactions.
• Study Duration: Data were collected continuously during school hours from 8:30 AM to 4:30 PM, excluding lunch and short breaks.
• Coverage: The paper achieved a high participation rate, with RFID coverage for 96% of children and 100% of teachers.

Results and Observations

The research provides several critical insights:

1. Contact Frequency and Duration:
   • Each child had an average of 323 contacts per day with others, amounting to a daily interaction time of 176 minutes.
   • Contacts were predominantly brief but heterogeneous in duration, with approximately 88% lasting less than one minute. However, a significant number of interactions extended beyond five minutes.
2. Class and Age Structures:
   • The majority of contacts occurred within the same class, and each child spent on average three times more time in contact with classmates than with children from other classes.
   • Contact matrices revealed a hierarchical structure, with strong interactions within the same grade and fewer interactions between different grades, visibly structured by the school's schedule.
3. Temporal Dynamics:
   • Analysis of 20-minute aggregated networks showed that contact rates peaked during breaks and lunchtime, indicating moments of high interaction activity.
   • The temporal evolution of contact patterns revealed that intra-class interactions saturated quickly, while inter-class contacts built up primarily during breaks.

Implications for Epidemiological Models

The detailed contact data holds substantial implications for the development of more accurate epidemiological models. Notable considerations include:

• Non-Homogeneous Mixing:
  • The paper challenges the homogeneous mixing hypothesis often used in epidemiological models, emphasizing the need for models incorporating age and class structures to capture real-world dynamics more accurately.
• Prioritization of Control Measures:
  • The results support targeted interventions, such as selective class closures over entire school closures, which could mitigate epidemic spread while minimizing disruption.
  • Temporal data can inform the timing of interventions, such as staggered break times to limit cross-class interactions.

Future Research Directions

Future studies could extend this research by:

• Longitudinal Data Collection: Conducting long-term deployments to observe how interaction patterns evolve over weeks or months.
• Diverse Settings: Expanding the paper to various schools with different structures and socio-economic contexts to generalize findings.
• Integration with Household Data: Coupling school interaction data with household data to understand the broader transmission networks involving children.

Conclusion

The research by Stehlé et al. represents a critical step towards understanding primary school contact patterns' complexity and heterogeneity. By providing high-resolution data, this paper enhances our capacity to model infectious disease transmission more accurately and suggests efficient, targeted public health interventions. The findings underscore the importance of considering detailed contact structures and temporal dynamics in epidemiological models.