  Transport systems are vulnerable to events that create disruptions. This
situation is particularly sensitive in parts of Africa with a low density of
highways and an increasing level of violence. Here, we measure the risk of the
African transport network based on two separate indices: the intensity of
future events $\mu$ and the impact $\nu$ of one event on the flow that travels
through the network. To estimate the intensity of future events happening in
city $i$, we construct a self-exciting point process. To estimate the impact of
an event, we consider a network of all highways in the continent and a modelled
flow between any pair of cities. Based on both indicators, we construct the
$\mu-\nu$ diagram and classify cities based on their combined impact and
intensity. Results show that certain cities in the network have a high risk and
increase the vulnerability of Africa's infrastructure. These cities have a high
propensity for suffering subsequent violence against their civilians, and given
their connectivity structure, they also substantially affect the overall
regional functioning. Removing just ten edges would require rerouting 32% of
trips according to our model. The top 100 edges where violence might happen
account for 17% of the trips. We find that cities with the highest $\mu-\nu$
risk are those characterised by small and medium size and large degree, meaning
they act as hubs. Vulnerable areas tend to be characterised by the presence of
terrorist groups like Boko Haram in Nigeria.
