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Contact patterns among high school students (1409.5318v1)

Published 18 Sep 2014 in physics.soc-ph and cs.SI

Abstract: Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. It is thus important to obtain accurate and reliable descriptions of human contact patterns occurring in various day-to-day life contexts. Recent technological advances and the development of wearable sensors able to sense proximity patterns have made it possible to gather data giving access to time-varying contact networks of individuals in specific environments. Here we present and analyze two such data sets describing with high temporal resolution the contact patterns of students in a high school. We define contact matrices describing the contact patterns between students of different classes and show the importance of the class structure. We take advantage of the fact that the two data sets were collected in the same setting during several days in two successive years to perform a longitudinal analysis on two very different timescales. We show the high stability of the contact patterns across days and across years: the statistical distributions of numbers and durations of contacts are the same in different periods, and we observe a very high similarity of the contact matrices measured in different days or different years. The rate of change of the contacts of each individual from one day to the next is also similar in different years. We discuss the interest of the present analysis and data sets for various fields, including in social sciences in order to better understand and model human behavior and interactions in different contexts, and in epidemiology in order to inform models describing the spread of infectious diseases and design targeted containment strategies.

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Authors (2)
  1. Julie Fournet (5 papers)
  2. Alain Barrat (67 papers)
Citations (273)

Summary

Analysis of High-Resolution Contact Patterns Among High School Students

The paper focuses on the exploration and analysis of high-resolution contact patterns among high school students through a detailed paper utilizing wearable sensor technology. The primary objective of the paper was to uncover patterns of social interaction within a high school setting, with particular interest in their implications for understanding human behavior and modeling the spread of infectious diseases.

Data Collection and Methodology

The paper was conducted over two distinct periods, capturing data from three classes in 2011 and five classes in 2012 at a high school in Marseilles, France. Wearable sensors were employed to collect face-to-face encounter data, offering a temporal resolution of 20 seconds, sufficient to establish a comprehensive time-varying contact network. The proximity sensors detected close physical presence, specifically capturing interactions within 1-1.5 meters, which is critical for assessing disease transmission risks.

Key Findings

  1. Contact Networks and Patterns:
    • The aggregated contact networks exhibited small diameter and high clustering coefficients, indicating densely connected sub-communities primarily defined by student classes.
    • The degree distribution of these networks was homogeneous, in contrast to the heterogeneous and heavy-tailed distributions observed for both contact durations and cumulative contact durations. This discrepancy highlights that while students tend to interact with a consistent number of individuals, the duration of these interactions varies greatly.
  2. Structural Analysis:
    • Contact matrices demonstrated strong intra-class connectedness, with a significant majority of contacts occurring within the same class. A secondary pattern emerged, grouping classes based on similar subject focus or geographical proximity within the school.
    • Interestingly, no strong gender homophily was detected, a stark contrast to similar studies conducted in primary schools, suggesting developmental or contextual variations in social behavior across educational stages.
  3. Temporal Stability and Longitudinal Insights:
    • Temporal analysis revealed remarkable stability in contact patterns over different days and even across different academic years. Although individual student contacts varied daily, the underlying structural pattern of inter-class and intra-class interactions remained robust.
    • The similarity in contact patterns over two consecutive years suggests a stable social structure in the high school environment despite the turnover in student population.

Implications and Future Directions

The dataset and subsequent analysis provide crucial insights into the dynamics of human contact patterns, emphasizing the significance of incorporating such detailed networks in epidemiological modeling. Given the concentration of contacts within and among specific class groups, strategic interventions, such as targeted class closures, could potentially enhance the effectiveness of disease control measures without resorting to full school closure.

Moreover, the robustness of contact patterns across different days and years underscores the potential for short-term data collection efforts to yield meaningful insights applicable over extended periods. The continuity and consistency observed suggest a possibility for designing models that account for both general stability and specific individual-level variability in contact behaviors.

Future research could expand on the integration of such high-resolution data with other sources, like diary-based studies or smartphone data, to achieve a comprehensive view of interaction landscapes. This holds potential not only for better understanding social dynamics in educational settings but also in workplaces and other community environments.

The paper thus contributes a pivotal understanding of high school contact networks, providing a valuable resource for ongoing research in social dynamics and public health strategy planning.