Abstract
The rapid adoption of mobile phone technologies in Africa is offering exciting opportunities for engaging with high-risk populations through mHealth programs, and the vast volumes of behavioral data being generated as people use their phones provide valuable data about human behavioral dynamics in these regions. Taking advantage of these opportunities requires an understanding of the penetration of mobile phones and phone usage patterns across the continent, but very little is known about the social and geographical heterogeneities in mobile phone ownership among African populations. Here, we analyze a survey of mobile phone ownership and usage across Kenya in 2009 and show that distinct regional, gender-related, and socioeconomic variations exist, with particularly low ownership among rural communities and poor people. We also examine patterns of phone sharing and highlight the contrasting relationships between ownership and sharing in different parts of the country. This heterogeneous penetration of mobile phones has important implications for the use of mobile technologies as a source of population data and as a public health tool in sub-Saharan Africa.
Highlights
As the adoption of mobile phones continues to rise rapidly so do the opportunities to directly engage with populations for policy purposes, as well as to study their dynamics on a scale previously impossible
The data passively generated each time a person uses their mobile phone to call and text can be used to understand large-scale patterns of individual behaviors like mobility and communication [3,4,5,6]. Studies of this kind have highlighted the consistency of travel patterns in high-income countries and shown how wealth relates to social network structure [3,4]
It is clear that mobile phone ownership and usage is not uniform across populations, and that socio-demographic characteristics of owners are not representative of the general population
Summary
As the adoption of mobile phones continues to rise rapidly so do the opportunities to directly engage with populations for policy purposes, as well as to study their dynamics on a scale previously impossible. The data passively generated each time a person uses their mobile phone to call and text can be used to understand large-scale patterns of individual behaviors like mobility and communication [3,4,5,6]. Studies of this kind have highlighted the consistency of travel patterns in high-income countries and shown how wealth relates to social network structure [3,4]. The geographic and demographic heterogeneities in mobile ownership and the details of phone sharing practices in Africa remain largely unknown [7,8]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
