Quantifying agent impacts on contact sequences in social interactions

Mark M Dekker,Debabrata Panja,Jiamin Ou,Denny Borsboom,Tessa F Blanken,Fabian Dablander

doi:10.1038/s41598-022-07384-0

Mark M Dekker, Debabrata Panja + Show 4 more

Open Access

https://doi.org/10.1038/s41598-022-07384-0

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Journal: Scientific Reports	Publication Date: Mar 3, 2022
Citations: 2	License type: open-access

Affiliation: Utrecht University, University of Amsterdam

Abstract

Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. Social interactions determine the contact network among individuals, while spreading, requiring individual-to-individual transmission, takes place on top of the network. Studying the topological aspects of a contact network, therefore, not only has the potential of leading to valuable insights into how the behavior of individuals impacts spreading phenomena, but it may also open up possibilities for devising effective behavioral interventions. Because of the temporal nature of interactions—since the topology of the network, containing who is in contact with whom, when, for how long, and in which precise sequence, varies (rapidly) in time—analyzing them requires developing network methods and metrics that respect temporal variability, in contrast to those developed for static (i.e., time-invariant) networks. Here, by means of event mapping, we propose a method to quantify how quickly agents mingle by transforming temporal network data of agent contacts. We define a novel measure called contact sequence centrality, which quantifies the impact of an individual on the contact sequences, reflecting the individual’s behavioral potential for spreading. Comparing contact sequence centrality across agents allows for ranking the impact of agents and identifying potential ‘behavioral super-spreaders’. The method is applied to social interaction data collected at an art fair in Amsterdam. We relate the measure to the existing network metrics, both temporal and static, and find that (mostly at longer time scales) traditional metrics lose their resemblance to contact sequence centrality. Our work highlights the importance of accounting for the sequential nature of contacts when analyzing social interactions.

Highlights

Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population
The advantage of using a network approach is that a general spreading process of some entity can be analyzed by means of a two-level description—the “infrastructure”, and the process on top of it: (a) a contact network, borne out of people’s behavior in social interactions that constitutes the infrastructure, and (b) a pathogen spreading process occurring within a population, which becomes a process that uses this infrastructure as pathways to transmit from an infected to a susceptible agent
To the left of the panel, we show the corresponding aggregated contact network over the entire time range, wherein two agents are connected by an edge if they have been in contact at any of the four time steps: the aggregated contact network does not distinguish any sequence between the interactions

Summary

Introduction

Human social behavior plays a crucial role in how pathogens like SARS-CoV-2 or fake news spread in a population. On the methodological side, we still lack adequate tools to assess, represent, and model the myriad ways in which human behavior generates patterns of individual-level contacts. This limits progress in many disciplines that require such information, but especially hampers progress along the behavior-epidemiology interface that is so important in improving our preparedness to deal with the current and future pandemics. On quantifying the role of each individual in the overall contact patterns, reflecting the agent’s impact on the potential of (e.g., epidemiological) spreading in a system To achieve these goals, we utilize a network approach in which patterns of contacts which are generated by individual behavior are mapped on to a contact network. Individuals who contribute greatly to the topological aspects of the network may represent potential targets of intervention. (In contrast, social distancing is a non-pharmaceutical intervention measure against SARS-CoV-2 transmission by means of globally disrupting the infrastructure)

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