The impact of mobility network properties on predicted epidemic dynamics in Dhaka and Bangkok

Epidemics

Kenth Engø-Monsen¹  Caroline O. Buckee²  Tyler S. Brown³  Ayesha S. Mahmud⁴  Mathew V. Kiang⁵  Richard J. Maude⁶ 

[1] Harvard T.H. Chan School of Public Health, United States of America;Harvard T.H. Chan School of Public Health, United States of America;Massachusetts General Hospital, Infectious Diseases Division, United States of America;Stanford University School of Medicine, Department of Epidemiology and Population Health, United States of America;Telenor Research, Norway;University of California, Berkeley, Demography Department, United States of America;

关键词: Cities;    Human mobility;    Mobile phone data;    SARS-CoV-2 dynamics;   

DOI  :  

来源: DOAJ

【 摘 要 】

Properties of city-level commuting networks are expected to influence epidemic potential of cities and modify the speed and spatial trajectory of epidemics when they occur. In this study, we use aggregated mobile phone user data to reconstruct commuter mobility networks for Bangkok (Thailand) and Dhaka (Bangladesh), two megacities in Asia with populations of 16 and 21 million people, respectively. We model the dynamics of directly-transmitted infections (such as SARS-CoV-2) propagating on these commuting networks, and find that differences in network structure between the two cities drive divergent predicted epidemic trajectories: the commuting network in Bangkok is composed of geographically-contiguous modular communities and epidemic dispersal is correlated with geographic distance between locations, whereas the network in Dhaka has less distinct geographic structure and epidemic dispersal is less constrained by geographic distance. We also find that the predicted dynamics of epidemics vary depending on the local topology of the network around the origin of the outbreak. Measuring commuter mobility, and understanding how commuting networks shape epidemic dynamics at the city level, can support surveillance and preparedness efforts in large cities at risk for emerging or imported epidemics.

【 授权许可】

Unknown