Measuring contact patterns with wearable sensors: Methods, data characteristics and applications to data-driven simulations of infectious diseases

A. Barrat, C. Cattuto, A. E. Tozzi, P. Vanhems, N. Voirin

Research output: Contribution to journalArticlepeer-review

Abstract

Thanks to recent technological advances, measuring real-world interactions by the use of mobile devices and wearable sensors has become possible, allowing researchers to gather data on human social interactions in a variety of contexts with high spatial and temporal resolution. Empirical data describing contact networks have thus acquired a high level of detail that may yield new insights into the dynamics of infection transmission between individuals. At the same time, such data bring forth new challenges related to their statistical description and analysis, and to their use in mathematical models. In particular, the integration of highly detailed empirical data in computational frameworks designed to model the spread of infectious diseases raises the issue of assessing which representations of the raw data work best to inform the models. There is an emerging need to strike a balance between simplicity and detail in order to ensure both generalizability and accuracy of predictions. Here, we review recent work on the collection and analysis of highly detailed data on temporal networks of face-to-face human proximity, carried out in the context of the SocioPatterns collaboration. We discuss the various levels of coarse-graining that can be used to represent the data in order to inform models of infectious disease transmission. We also discuss several limitations of the data and future avenues for data collection and modelling efforts in the field of infectious diseases.

Original languageEnglish
Pages (from-to)10-16
Number of pages7
JournalClinical Microbiology and Infection
Volume20
Issue number1
DOIs
Publication statusPublished - Jan 2014

Keywords

  • Contact patterns
  • Data-driven
  • Infectious diseases
  • Modelling
  • Numerical simulations
  • Wearable sensors

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

Fingerprint Dive into the research topics of 'Measuring contact patterns with wearable sensors: Methods, data characteristics and applications to data-driven simulations of infectious diseases'. Together they form a unique fingerprint.

Cite this