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

被引：0
|
作者：
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
机构：
[1] KEMRI - Wellcome Trust Research Programme,Data Science Laboratory
[2] ISI Foundation,School of Mathematics
[3] The University of Manchester,Aix
[4] Bitmanufaktory Ltd,Marseille Université
[5] Université de Toulon,School of Life Sciences and WIDER
[6] University of Warwick,undefined
来源：
EPJ Data Science | / 5卷
关键词：
households; contact patterns; contact networks; wearable proximity sensors; respiratory infections; infectious disease control;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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