Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers (1409.7017v2)

Abstract: Empirical data on contacts between individuals in social contexts play an important role in providing information for models describing human behavior and how epidemics spread in populations. Here, we analyze data on face-to-face contacts collected in an office building. The statistical properties of contacts are similar to other social situations, but important differences are observed in the contact network structure. In particular, the contact network is strongly shaped by the organization of the offices in departments, which has consequences in the design of accurate agent-based models of epidemic spread. We consider the contact network as a potential substrate for infectious disease spread and show that its sparsity tends to prevent outbreaks of rapidly spreading epidemics. Moreover, we define three typical behaviors according to the fraction $f$ of links each individual shares outside its own department: residents, wanderers and linkers. Linkers ($f\sim 50\%$) act as bridges in the network and have large betweenness centralities. Thus, a vaccination strategy targeting linkers efficiently prevents large outbreaks. As such a behavior may be spotted a priori in the offices' organization or from surveys, without the full knowledge of the time-resolved contact network, this result may help the design of efficient, low-cost vaccination or social-distancing strategies.

Data on Face-to-Face Contacts in an Office Building and Implications for Vaccination Strategies

The paper of human interactions in closed environments, such as office buildings, is crucial for understanding the dynamics of epidemic spread and designing effective vaccination strategies. The paper "Data on face-to-face contacts in an office building suggest a low-cost vaccination strategy based on community linkers" presents an empirical analysis of face-to-face contact data collected in an office building. The analysis reveals significant structural properties of the contact network and proposes a targeted vaccination strategy that could efficiently prevent epidemic outbreaks.

Key Findings

The data were collected using wearable sensors, capturing close-proximity interactions in an office setting over two weeks. This rich dataset enabled the construction of both aggregated and temporal contact networks. Several noteworthy findings emerged:

1. Network Structure and Sparsity: The contact network was found to be sparse, with individuals interacting with only a fraction of the total office population. This sparsity is expected to inhibit the rapid spread of infectious diseases, a hypothesis supported by simulation results of Susceptible-Infected-Recovered (SIR) models.
2. Community Organization: The office is organized into distinct departments, which form communities in the contact network. Internal contacts dominate, with significantly fewer interactions occurring between departments. This community structure is crucial as it dictates potential pathways for epidemic spread.
3. Linkers as Vaccination Targets: Individuals who act as "linkers," with approximately 50% of their contacts outside their department, were identified as key nodes in the network due to their high betweenness centrality. Targeting these linkers for vaccination could effectively bridge the departmental boundaries and limit epidemic spread.
4. Temporal Stability: The paper assessed the stability of the network's daily structure and found it stable across days, although individuals' specific contacts varied. This stability suggests that identifying linkers requires only short-term data, making the strategy feasible with limited information.

Implications and Speculations

The identification of linkers modifies the traditional approach to vaccination strategies in office-like settings. By focusing on these strategically important individuals, public health strategies can be both cost-effective and operationally efficient. This vaccination strategy does not require comprehensive data about every individual's contacts, which is typically challenging to gather. Instead, it can utilize easily observable metrics or organizational knowledge, such as job roles or inter-departmental responsibilities.

The methodological approach demonstrated here can be generalized beyond office buildings to other community-based contact networks like schools or hospitals. Future studies could explore applying this strategy in larger, more complex networks or during different temporal phases of an epidemic to assess the robustness of linker-based strategies across various settings and outbreak scenarios.

Concluding Remarks

This paper sheds light on the potential of analyzing contact patterns within closed environments to inform health interventions. It underscores the need for comprehensive, yet simplified, strategies in mitigating epidemic spread and highlights the intricate interplay between network structure and epidemic dynamics. The implications of these findings offer a promising avenue for reducing disease spread through informed, targeted interventions amid limited resource availability.