network science

Modelling virus spreading in ride-pooling networks

Pooled travellers infect each others through a complex, dynamic contact network. We simulate this in context of demand mobility patterns in Amsterdam, trace epidemic outbreaks and identify effective control measures mitigating it

see our preprint with Julian Sienkiewicz and Oded Cats (under review in Scientific Reports)

Figure 1: Results of epidemic spread across 2000 ride-pooling travellers in Amsterdam. Set of experimental results.





Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion. Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems. Yet, the potential of ride-pooling rides to serve as a safe and effective alternative given the personal and public health risks considerations associated with the COVID-19 pandemic is hitherto unknown.

To answer this, we combine epidemiological and behavioural shareability models to examine spreading among ride-pooling travellers, with an application for Amsterdam. Findings are at first sight devastating, with only few initially infected travellers needed to spread the virus to hundreds of ride-pooling users. Without intervention, ride-pooling system may substantially contribute to virus spreading. Notwithstanding, we identify an effective control measure allowing to halt the spreading before the outbreaks (at 50 instead of 800 infections) without sacrificing the efficiency achieved by pooling. Fixed matches among co-travellers disconnect the otherwise dense contact network, encapsulating the virus in small communities and preventing the outbreaks.