portland_contacts — Synthetic contact network of Portland, Oregon
- Description
A synthetic network of the physical contacts between the inhabitants of Portland, Oregon (USA), during a typical day, generated by the Network Dynamics and Simulation Science Laboratory (NDSSL, Virginia Tech, formerly at Los Alamos National Laboratory) with the TRANSIMS and EpiSims simulations from census data, land use data and activity surveys: synthetic individuals, with the demographics of the census, are assigned daily activities (home, work, school, shopping, ...) at real locations, and two persons are in contact if they are at the same location (sub-location) at the same time. Each node is a person, and an undirected edge means that the two persons were in contact during the day. This network was widely used to model the spread of infectious diseases in cities.
The data are those redistributed by Yang et al. for their study of pandemic containment, who give the network without the durations and activity types of the contacts of the original NDSSL data, which is no longer available from its source. The node and edge lists of this redistribution are used as they are; the centrality scores (eigenvector and local-flow betweenness centralities) computed by Yang et al., and given in the same record, are not included.
The network has the following properties:
- (Node)
id: the identifier of the person in the data.
- (Node)
- Tags
- Social Offline Public Health Unweighted
- Added
- 2026-10-28
- Citation
-
- S. Eubank, H. Guclu, V. S. A. Kumar, M. V. Marathe, A. Srinivasan, Z. Toroczkai, N. Wang, "Modelling disease outbreaks in realistic urban social networks." Nature 429, 180-184 (2004) 10.1038/nature02541 Sci-Hub
- S. Yang, P. Senapati, D. Wang, C. T. Bauch, K. Fountoulakis, "Targeted pandemic containment through identifying local contact network bottlenecks." PLOS Computational Biology 17(8), e1009351 (2021) 10.1371/journal.pcbi.1009351 Sci-Hub
- Upstream URL 403
- https://doi.org/10.6084/m9.figshare.13166507.v1
- Upstream license
- CC0, https://creativecommons.org/publicdomain/zero/1.0/
- Networks
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Tip: hover over a column header for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties