Study on Urban Travel Volume During the Outbreak of COVID-19
10th International Conference on Mobile Wireless Middleware, Operating Systems and Applications, MOBILWARE 2021
; : 63-72, 2022.
Article
in English
| Scopus | ID: covidwho-1877736
ABSTRACT
The distribution and change of travel intensity reflect the pattern of the city and the activity of trip population. It is important to understand the pattern of the city and the activity of trip flow for urban planning and government decision-making. This paper constructs a Bayesian hierarchical spatiotemporal model with three effects space, time, and space-time, which uses the travel intensity data during the outbreak of the novel coronavirus (COVID-19) in Hubei province (2020.01.01–2020.05.02). With the help of Markoff’s Monte Carlo method, this paper analyzes the distribution and fluctuation of traffic flow in each city of Hubei province. The results show that the space-time model does not deteriorate compared with the main space model. The study found that nearly 41% of cities with a spatial effect higher than 1 were active during the epidemic in Hubei province and the time effect of travel intensity in Hubei province dropped rapidly from 2 to 0.5 after cities in Hubei province issued measures to close the cities one after another, which lasted nearly a month. Strict social distance intervention is one of the important reasons for Hubei province to control the epidemic effectively in a few months. At the same time, in the stability analysis of the city, we found that Wuhan belongs to an unstable area, which is unfavorable to the control of COVID-19. The research results provide a certain perspective for COVID-19 prevention and control when there are confirmed patients in the province, we believe that the government should first pay attention to those cities with high spatial effect and instability. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Bayesian hierarchical model; Spatiotemporal model; Travel intensity; Travel volume; Coronavirus; Disease control; Hierarchical systems; Monte Carlo methods; Bayesian; Bayesian hierarchical modelling; Decisions makings; Government decisions; Hubei Province; Spatial effect; Spatio-temporal models; Travel volumes; Urban travels; Decision making
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
10th International Conference on Mobile Wireless Middleware, Operating Systems and Applications, MOBILWARE 2021
Year:
2022
Document Type:
Article
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