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.

Highlights

  • Reliable detailed information on the contact patterns occurring between individuals in day-to-day life contexts carries a great value in fields such as social sciences or epidemiology of infectious diseases, in which human interactions are of primary importance

  • We study the evolution of the contact patterns on two widely distinct different timescales: on the one hand, we examine the stability of the contact networks and mixing patterns in a given population of students from one day to the ; on the other hand, we take advantage of the fact that the two data sets were collected in the same environment to study the long term stability of contact patterns in the high school

  • We have presented an analysis of two highresolution contact data sets collected in a French high school using wearable sensors, respectively for three classes during four school days in December 2011 and for five classes during seven school days in November 2012

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Summary

Introduction

Reliable detailed information on the contact patterns occurring between individuals in day-to-day life contexts carries a great value in fields such as social sciences or epidemiology of infectious diseases, in which human interactions are of primary importance. The strong mixing of school children favors the spread of infectious diseases in school environmentx and makes them an important source of infection into households from where infections can spread further [1,2]. In such contexts, a precise description of human contacts can help identify possible contagion pathways, design realistic models of epidemic spread and design and evaluate containment strategies such as targeted vaccination, social distancing or school or workplace closures. Biases due to self-reporting are avoided [10,13] and high-resolution data can be collected in an objective way, allowing to parametrize and inform datadriven models describing human behavior [26,27,28] and epidemic spread in specific settings [21]

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