The limited volume of COVID‐19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS‐CoV‐2 mutations. The Virus Outbreak Data Network (VODAN)‐Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID‐19, producing these as human‐ and machine‐readable data objects in a distributed architecture of locally governed, linked, human‐ and machine‐readable data. This architecture supports analytics at the point of care and—through data visiting, across facilities—for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.
While Internet connectivity has reached a significant part of the world's population, those living in rural areas of the developing world are still largely disconnected. Recent efforts have provided Internet connectivity to a growing number of remote locations, yet Internet traffic demands cause many of these networks to fail to deliver basic quality of service needed for simple applications. For an in-depth investigation of the problem, we gather and analyze network traces from a rural wireless network in Macha, Zambia. We supplement our analysis with on-site interviews from Macha, Zambia and Dwesa, South Africa, another rural community that hosts a local wireless network. The results reveal that Internet traffic in rural Africa differs significantly from the developed world. We observe dominance of web-based traffic, as opposed to peer-to-peer traffic common in urban areas. Application-wise, online social networks are the most popular, while the majority of bandwidth is consumed by large operating system updates. Our analysis also uncovers numerous network anomalies, such as significant malware traffic. Finally, we find a strong feedback loop between network performance and user behavior. Based on our findings, we conclude with a discussion of new directions in network design that take into account both technical and social factors.
The Internet is evolving from a system of connections between humans and machines to a new paradigm of social connection. However, it is still dominated by a hub and spoke architecture with inter-connectivity between users typically requiring connections to a common server on the Internet. This creates a large amount of traffic that must traverse an Internet gateway, even when users communicate with each other in a local network. Nowhere is this inefficiency more pronounced than in rural areas with low-bandwidth connectivity to the Internet. Our previous work in a rural village in Macha, Zambia showed that web traffic, and social networking in particular, are dominant services. In this paper we use a recent network trace, from this same village, to explore the degree of local user-to-user interaction in the village. Extraction of a social graph, using instant message interactions on Facebook, reveals that 54% of the messages are between local users. Traffic analysis highlights that the potential spare capacity of the local network is not utilized for direct local communication between users even though indirect communication between local users is routed through services on the Internet. These findings build a strong motivation for a new rural network architecture that places services that enable user-to-user interaction and file sharing in the village.
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