Modelling virus spreading in ride-pooling networks

TL;DR

This paper models virus transmission in ride-pooling networks, revealing significant risks of COVID-19 spread but also identifying effective control measures that can prevent outbreaks without losing pooling efficiency.

Contribution

It combines epidemiological and behavioral models to analyze virus spread in ride-pooling, proposing a control strategy to prevent outbreaks while maintaining system efficiency.

Findings

Few initial infections can lead to large outbreaks without intervention.

Fixed matching of co-travellers can contain virus spread.

Control measures can prevent outbreaks at low infection thresholds.

Abstract

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.