In 2000, the whole of Africa had less international internet bandwidth than Luxembourg (a country the size of the state of Rhode Island). Two decades later, despite some progress, much of Africa is still unconnected and large populations cannot fully realize the benefits of connectivity.
A new report calling for urgent action to close the internet access gap suggests that around $ 100 billion would be needed to achieve universal access to broadband connectivity in Africa by 2030. This is a formidable challenge, as about a third of the population remains out of reach of mobile broadband signal in Sub-Saharan Africa. The report estimates that nearly 250,000 new 4G base stations and at least 250,000 kilometers of new fiber across the region would be required to achieve the goal. Furthermore, innovative approaches are also needed, the report notes, to connect the unconnected in remote, rural areas currently out of reach of traditional cellular mobile networks. The aerospace manufacturer SpaceX is betting on satellite internet and has just announced its intention to offer the Starlink satellite broadband service starting in 2020 – with eventual plans to expand to Africa, while other players are testing drones and balloons to expand access.
And there is heightened interest in mapping Africa’s digital infrastructure for the simple reason that maps tell compelling stories. To reach universal access, it is critical to assess the specific connectivity gaps and monitor the progress of digital infrastructure on the continent. Visually representing locations in Africa that are on the terrestrial “backbone” network of fiber optic internet cables is a vital step towards understanding the connectivity landscape. By overlaying open population data from the EU Joint Research Center with fiber optic network data from the Network Startup Resource Center, we can begin to conceptualize the needs and progress of universal access (see map). We can also estimate that approximately 45% of Africa’s population is further than 10 km from fiber network infrastructure, which is a higher percentage than on any other continent.
Though this visual representation does not necessarily communicate the exact status of connectivity, or present real-time data on cable status, it’s a very useful start. Furthermore, proximity to digital infrastructure is not a guaranteed indicator of internet quality, speed, or even take-up. There are of course many other barriers to access, such as affordability (both of service and handsets), the policy, regulatory and fiscal environment, the status of digital skills, gender, age, education etc. But lack of coverage of broadband signal is a binding constraint, and therefore our main focus.
Most internet adoption in Africa is driven by mobile connections, and the range of 3G/4G technology is location-dependent. But if those cell towers are not served by fiber (and rely instead on microwave or satellite), then the signal speed and capacity is typically lower, likely restricted to 2.5G and not true broadband. The map includes both terrestrial and undersea cables that are live and under construction and would require further work to indicate which of these cables are operational.
The data opens several interesting questions to be explored. For example, we can see the populations that are in most need of connectivity infrastructure and where investments should be made. But investors are more likely to be attracted by population hotspots rather than white-spots, which means that new investment tends to duplicate existing investment rather than to fill gaps. Hence a need for public intervention, for instance through universal access funds. But data interventions may be required too. Reliable information and up-to-date maps of digital infrastructure are hard to find and are generally not machine-readable. Digital infrastructure maps should be regarded as part of the public domain so that users and investors in other sectors of the economy can draw upon them. That would mean moving towards regionally-integrated digital infrastructure maps with access to real-time data on operations and maintenance being the goals. Better mapping will lead to better planning and more efficient investment.
As a next step, our small team (a collaboration between digital development colleagues working on the Digital Economy for Africa Initiative and spatial data specialists) is overlaying various other datasets, such as nightlight data from remote-sensing satellites, and applying machine learning techniques to gain an even more granular understanding of the connectivity needs. We are also exploring the data at a national level to visually represent a more detailed analysis of the needs and connectivity gaps for specific countries. An obvious step is to overlay fiber and cell tower maps to predict which cellular base stations are already fiberized. This analysis will hopefully benefit private sector operators, governments and development partners as they seek to work together to bring more of the African continent online.