Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

TL;DR

This study uses high-resolution RFID data of conference attendees' face-to-face interactions to simulate epidemic spread with an SEIR model, highlighting the importance of temporal contact data for accurate modeling.

Contribution

It demonstrates that aggregated contact data with duration is sufficient for epidemic modeling, whereas homogeneous networks are inadequate, emphasizing the role of temporal contact patterns.

Findings

Aggregated contact networks with duration closely approximate full-resolution data.

Homogeneous contact networks fail to accurately predict epidemic size.

Temporal contact data significantly improves epidemic simulation accuracy.

Abstract

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that provide estimates of the number and duration of contacts among social groups. Moreover, their space and time resolution are limited, so that data is not explicit at the person-to-person level, and the dynamical aspect of the contacts is disregarded. Here, we want to assess the role of data-driven dynamic contact patterns among individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population. We consider high resolution data of face-to-face interactions between the attendees of a conference, obtained from the deployment of an infrastructure based on Radio Frequency Identification (RFID) devices that assess mutual face-to-face proximity. The spread of epidemics along these interactions is simulated through an SEIR model, using both the dynamical network of contacts defined by the collected data, and two aggregated versions of such network, in order to assess the role of the data temporal aspects. We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation which retains only the topology of the contact network fails in reproducing the size of the epidemic. These results have important implications in understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics.