Accepted_test

NeoCovasim: an agent-based epidemiological model with traffic flow and GPU acceleration

Authors:
Manolov Aleksander, Research Institute of System Biology and Medicine, Rospotrebnadzor, Moscow, Russia
Tsurkis Vera, Federal State Autonomous Educational Institution of Higher Education "Moscow Institute of Physics and Technology (National Research University), Moscow, Russia
Maslova Irina, Research Institute of System Biology and Medicine, Rospotrebnadzor, Moscow, Russia
Kozlov Ivan, Research Institute of System Biology and Medicine, Rospotrebnadzor, Moscow, Russia
Samoilov Andrey, Research Institute of System Biology and Medicine, Rospotrebnadzor, Moscow, Russia
Ilina Elena, Research Institute of System Biology and Medicine, Rospotrebnadzor, Moscow, Russia

Abstract ID: 556

Event: BGRS-abstracts

Sections: [Sym 2] Section “Mathematical epidemiology”

Based on the open-source Covasim platform, we developed NeoCovasim, a software package that allows parallel simulations of multiple localities connected by a transport network. Computational experiments showed a non-linear relationship between passenger traffic intensity and epidemiological dynamics. GPU acceleration significantly speed up the modelling process for large cities. Sensitivity analysis revealed that household size, class size, and workforce size are important parameters influencing model behavior.