2018/01/29 by Zhanwei Du, Du, Zhanwei, Yuan Bai +1
Mathematics · Medicine · Physics and Astronomy · #COVID-19 epidemiological studies #Complex Network Analysis Techniques #Data-Driven Disease Surveillance #FOS: Computer and information sciences #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1801.09333
openalex publication_date 2018/01/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In many developing countries, public transit plays an important role in daily life. However, few existing methods have considered the influence of public transit in their models. In this work, we present a dual-perspective view of the epidemic spreading process of the individual that involves both contamination in places (such as work places and homes) and public transit (such as buses and trains). In more detail, we consider a group of individuals who travel to some places using public transit, and introduce public transit into the epidemic spreading process. A novel modeling framework is proposed considering place-based infections and the public-transit-based infections. In the urban scenario, we investigate the public transit trip contribution rate (PTTCR) in the epidemic spreading process of the individual, and assess the impact of the public transit trip contribution rate by evaluating the volume of infectious people. Scenarios for strategies such as public transit and school closure were tested and analyzed. Our simulation results suggest that individuals with a high public transit trip contribution rate will increase the volume of infectious people when an infectious disease outbreak occurs by affecting the social network through the public transit trip contribution rate.