Close encounters of the infectious kind: methods to measure social mixing behaviour

Abstract

A central tenet of close-contact or respiratory infection epidemiology is that infection patterns within human populations are related to underlying patterns of social interaction. Until recently, few researchers had attempted to quantify potentially infectious encounters made between people. Now, however, several studies have quantified social mixing behaviour, using a variety of methods. Here, we review the methodologies employed, suggest other appropriate methods and technologies, and outline future research challenges for this rapidly advancing field of research.

Fig. 1.

A stylized illustration of the abilities of different methodologies to capture contact network structures. Individuals are represented as small circles and interactions which permit transmission are links between them. Larger circles represent particular environments or locations in which enclosed individuals are present at the same time. Individuals participating in hypothetical studies are coloured. (a) The true network of contacts between individuals which are viable transmission opportunities for a particular pathogen. (b) The network as measured by anonymous contact diaries, where contacts are not named. Egocentric contact diaries can be used to capture some information on the clustering of contacts, but cannot easily identify links between participants. As the information is subjective it can contain inaccuracies, both missing and erroneous contacts. (c) The network as measured by proximity sensors. Here, clustering may be inferred by the co-location of contacts, and some information on higher-order network structure (longer range links) between participants can be captured. (d) The network inferred by location-based network modelling, where modelled locations are depicted by larger circles. This method is critically dependent on accurate location description, and may lead to overestimation of both the number of contacts made and the local level of clustering.

Fig. 2.

The daily variation in number of contacts reported by participants in the study by Read et al. [24]. Participants are ranked by their average number of contacts (red crosses); the size of circles denotes the number of days where a participant encounters the same number of contacts. There is much day-to-day variation in participants' reported number of contacts.