sp_kenyan_households — Kenyan households contacts (2012)

Description

Network of face-to-face proximity contacts among members of 5 households in rural Kenya (in the Kilifi Health and Demographic Surveillance System area), measured with wearable proximity sensors between 24 April and 12 May 2012 as part of a SocioPatterns study. The members of each household wore the sensors for three consecutive days. Nodes are household members and each edge is a contact event between two members, either of the same household or of different households, recorded during the daytime (between 7:00 and 20:00). Two members can be connected by multiple edges, one per contact event.

The network has the following properties:

id: the anonymous identifier of the member, unique only within its household (members are identified by the pair house, id).
house: the household of the member (L, F, E, B or H).
age: the age category of the member, coded from 0 to 4 (see Kiti et al. for the definition of the categories).
sex: the sex of the member (F or M).
duration: the duration of the contact event in seconds.
day: the day of the experiment in which the contact took place (1, 2 or 3).
hour: the hour of the day in which the contact took place (7 to 20).

Tags

Social Offline Unweighted Temporal Metadata

Citation

M. Kiti et al., "Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors." EPJ Data Science 5, 21 (2016) 10.1140/epjds/s13688-016-0084-2 Sci-Hub

Upstream URL OK

https://sociopatterns.org/datasets/kenyan-households-contact-network/

Upstream license

Creative Commons CC0 1.0 Universal (Public Domain Dedication), https://creativecommons.org/publicdomain/zero/1.0/

Networks

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

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
sp_kenyan_households	47	32,643	1389.06	1229.28	22.98	5.12	0.27	0.74	3	1.00	Undirected	Unipartite	id house age sex	duration day hour	28 KiB	107 KiB	94 KiB	49 KiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.