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EPJ Data Sci. 2016;5:21. doi: 10.1140/epjds/s13688-016-0084-2. Epub 2016 Jun 14.

Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors.

Author information

1
KEMRI - Wellcome Trust Research Programme, Kilifi, Kenya.
2
Data Science Laboratory, ISI Foundation, Via Alassio 11/c, Torino, 10126 Italy.
3
School of Mathematics, The University of Manchester, Manchester, UK.
4
Bitmanufaktory Ltd, Cambridge, UK.
5
Aix-Marseille Université, Université de Toulon, CNRS, CPT, UMR 7332, Marseille, 13288 France.
6
School of Life Sciences and WIDER, University of Warwick, Coventry, UK.
#
Contributed equally

Abstract

Close proximity interactions between individuals influence how infections spread. Quantifying close contacts in developing world settings, where such data is sparse yet disease burden is high, can provide insights into the design of intervention strategies such as vaccination. Recent technological advances have enabled collection of time-resolved face-to-face human contact data using radio frequency proximity sensors. The acceptability and practicalities of using proximity devices within the developing country setting have not been investigated. We present and analyse data arising from a prospective study of 5 households in rural Kenya, followed through 3 consecutive days. Pre-study focus group discussions with key community groups were held. All residents of selected households carried wearable proximity sensors to collect data on their close (<1.5 metres) interactions. Data collection for residents of three of the 5 households was contemporaneous. Contact matrices and temporal networks for 75 individuals are defined and mixing patterns by age and time of day in household contacts determined. Our study demonstrates the stability of numbers and durations of contacts across days. The contact durations followed a broad distribution consistent with data from other settings. Contacts within households occur mainly among children and between children and adults, and are characterised by daily regular peaks in the morning, midday and evening. Inter-household contacts are between adults and more sporadic when measured over several days. Community feedback indicated privacy as a major concern especially regarding perceptions of non-participants, and that community acceptability required thorough explanation of study tools and procedures. Our results show for a low resource setting how wearable proximity sensors can be used to objectively collect high-resolution temporal data without direct supervision. The methodology appears acceptable in this population following adequate community engagement on study procedures. A target for future investigation is to determine the difference in contact networks within versus between households. We suggest that the results from this study may be used in the design of future studies using similar electronic devices targeting communities, including households and schools, in the developing world context.

ELECTRONIC SUPPLEMENTARY MATERIAL:

The online version of this article (doi:10.1140/epjds/s13688-016-0084-2) contains supplementary material.

KEYWORDS:

contact networks; contact patterns; households; infectious disease control; respiratory infections; wearable proximity sensors

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