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

Overview of attention for article published in EPJ Data Science, June 2016
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Average Attention Score compared to outputs of the same age and source

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62 X users

Citations

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115 Mendeley
Title
Quantifying social contacts in a household setting of rural Kenya using wearable proximity sensors
Published in
EPJ Data Science, June 2016
DOI 10.1140/epjds/s13688-016-0084-2
Pubmed ID
Authors

Moses C Kiti, Michele Tizzoni, Timothy M Kinyanjui, Dorothy C Koech, Patrick K Munywoki, Milosch Meriac, Luca Cappa, André Panisson, Alain Barrat, Ciro Cattuto, D James Nokes

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

X Demographics

X Demographics

The data shown below were collected from the profiles of 62 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 2%
United States 1 <1%
Australia 1 <1%
Unknown 111 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 24%
Researcher 27 23%
Student > Master 10 9%
Professor > Associate Professor 5 4%
Student > Doctoral Student 4 3%
Other 15 13%
Unknown 26 23%
Readers by discipline Count As %
Medicine and Dentistry 19 17%
Social Sciences 12 10%
Computer Science 11 10%
Physics and Astronomy 8 7%
Agricultural and Biological Sciences 6 5%
Other 21 18%
Unknown 38 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 May 2020.
All research outputs
#1,074,137
of 25,193,883 outputs
Outputs from EPJ Data Science
#88
of 432 outputs
Outputs of similar age
#20,373
of 361,244 outputs
Outputs of similar age from EPJ Data Science
#5
of 8 outputs
Altmetric has tracked 25,193,883 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 432 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.4. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,244 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.