haslemere — BBC Pandemic Haslemere proximity (2017)
- Description
Temporal network of physical proximity among residents of the town of Haslemere (Surrey, England), collected with the "BBC Pandemic" mobile phone app for the BBC Four documentary "Contagion! The BBC Four Pandemic" (2018). Volunteers installed the app, which recorded their GPS location about every five minutes during three days, from Thursday 12 to Saturday 14 October 2017. Kissler et al. kept the 469 users who logged a location in Haslemere in at least six different hours, aggregated each user's locations into five-minute time bins (filling the bins without data with the last recorded location, or with the user's home location at the start), and computed the distances between all pairs of users in each bin. To protect the users' privacy, only the bins between 07:00 and 22:55 (British Summer Time) of each day were released (576 bins), without the locations.
Nodes are users of the app, and each edge is an encounter, i.e. two users within 50 m of each other during one five-minute time bin, so that two users are connected by as many edges as the number of time bins in which they were close. The network has the following properties:
id: the anonymous identifier of the user (from 1 to 469).time(edges): the start of the five-minute time bin, in Unix time.distance(edges): the distance between the two users in that time bin, rounded to the meter.
- Tags
- Social Offline Temporal Timestamps Multigraph Unweighted Metadata
- Citation
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- S. M. Kissler, P. Klepac, M. Tang, A. J. K. Conlan, J. R. Gog, "Sparking 'The BBC Four Pandemic': Leveraging citizen science and mobile phones to model the spread of disease." bioRxiv 479154 (2018) 10.1101/479154 Sci-Hub
- P. Klepac, S. Kissler, J. Gog, "Contagion! The BBC Four Pandemic - The model behind the documentary." Epidemics 24, 49-59 (2018) 10.1016/j.epidem.2018.03.003 Sci-Hub
- Upstream URL OK
- https://github.com/skissler/haslemere
- 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
- Ridiculograms*
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