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

作者：Moses C. Kiti, Michele Tizzoni, Timothy Kinyanjui, Dorothy Koech, Patrick K. Munywoki, Milosch Meriac, Luca Cappa, André Panisson, Alain Barrat, Ciro Cattuto, D. James Nokes · 发表于：EPJ Data Science · 年份：2016 · DOI：10.1140/epjds/s13688-016-0084-2 · 被引用次数：104 · 研究领域：ICT in Developing Communities、COVID-19 Digital Contact Tracing、Human Mobility and Location-Based Analysis

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 ad...