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Transport systems are vulnerable to events that create disruptions. Thissituation is particularly sensitive in parts of Africa with a low density ofhighways and an increasing level of violence. Here, we measure the risk of theAfrican transport network based on two separate indices: the intensity offuture events $\mu$ and the impact $\nu$ of one event on the flow that travelsthrough the network. To estimate the intensity of future events happening incity $i$, we construct a self-exciting point process. To estimate the impact ofan event, we consider a network of all highways in the continent and a modelledflow between any pair of cities. Based on both indicators, we construct the$\mu-\nu$ diagram and classify cities based on their combined impact andintensity. Results show that certain cities in the network have a high risk andincrease the vulnerability of Africa's infrastructure. These cities have a highpropensity for suffering subsequent violence against their civilians, and giventheir connectivity structure, they also substantially affect the overallregional functioning. Removing just ten edges would require rerouting 32% oftrips according to our model. The top 100 edges where violence might happenaccount 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, meaningthey act as hubs. Vulnerable areas tend to be characterised by the presence ofterrorist groups like Boko Haram in Nigeria.

Detecting the sensitive spots of the African interurban transport network