An LBS and agent-based simulator for Covid-19 research

Abstract

The mobility data of citizens provide important information on the epidemic spread including Covid-19. However, the privacy versus security dilemma hinders the utilization of such data. This paper proposed a method to generate pseudo mobility data on a per-agent basis, utilizing the actual geographical environment data provided by LBS to generate the agent-specific mobility trajectories and export them as GPS-like data. Demographic characteristics such as behavior patterns, gender, age, vaccination, and mask-wearing status are also assigned to the agents. A web-based data generator was implemented, enabling users to make detailed settings to meet different research needs. The simulated data indicated the usability of the proposed methods.

COVID-19 is linked to changes in the time–space dimension of human mobility

“…To assess the changes in the spatial mobility patterns, preserving citizen privacy under the General Data Protection Regulation (more information available at gdpr-info.eu/, accessed on 1 June 2023), we employ the radius of gyration 64,65 as a spatial metric. The radius of gyration was chosen for being a well-known metric applied to measure human mobility 15,19,[64][65][66][67][68][69] . This measure was used during COVID-19 to gauge the general population's compliance with mobility restrictions 38,47,70 , inform policymakers on their decisions 38,44,47 and reveal differences in the impact on different socio-economic groups and minorities [71][72][73][74] .…”