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Data underlying the publication: Virus spreading in ride-pooling networks. Can ride-pooling become a safe and sustainable mobility alternative for pandemic urban systems?

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posted on 02.03.2021, 14:42 authored by Rafal KucharskiRafal Kucharski
The dataset contains results of experiments for the study of our research Data is used to generate results with this reproducible notebook:

- png with maps
- .csv with epidemic modelling results (For any given day, the model outputs information about the number of travellers in each state (S-I-Q-R) and newly infected travellers, based on which we can reproduce epidemic spreading profiles.)

Abstract of the study:
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.


ERC Starting Grant CriticalMaaS (Grant Number 804469)





TU Delft, Faculty of Civil Engineering and Geosciences, Smart Public Transport Lab