scholarly journals Vaccination and Quarantine Effect on COVID-19 Transmission Dynamics Incorporating Chinese-Spring-Festival Travel Rush: Modeling and Simulations

2022 ◽  
Vol 84 (2) ◽  
Author(s):  
Yukun Zou ◽  
Wei Yang ◽  
Junjie Lai ◽  
Jiawen Hou ◽  
Wei Lin
Keyword(s):  
Chinese Spring ◽  
Transmission Dynamics ◽  
Modeling And Simulations ◽  
Spring Festival

scholarly journals Travel rush during Chinese Spring Festival and the 2019-nCoV

2020 ◽  
Vol 37 ◽  
pp. 101686 ◽  
Author(s):  
Juan Chen ◽  
Zhan-hui Feng ◽  
Lan Ye ◽  
Yong-ran Cheng ◽  
Meng-Yun Zhou ◽  
...  
Keyword(s):  
Chinese Spring ◽  
Spring Festival

scholarly journals The effects of firework regulation on air quality and public health during the Chinese Spring Festival from 2013 to 2017 in a Chinese megacity

2019 ◽  
Vol 126 ◽  
pp. 96-106 ◽  
Author(s):  
Lan Yao ◽  
Dongfang Wang ◽  
Qingyan Fu ◽  
Liping Qiao ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Public Health ◽  
Air Quality ◽  
Chinese Spring ◽  
Spring Festival

scholarly journals Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival

2019 ◽  
Vol 8 (10) ◽  
pp. 445 ◽  
Author(s):  
Jianwei Huang ◽  
Xintao Liu ◽  
Pengxiang Zhao ◽  
Junwei Zhang ◽  
Mei-Po Kwan
Keyword(s):  
Built Environment ◽  
Chinese Spring ◽  
Small Scale ◽  
Demographic Changes ◽  
Interaction Patterns ◽  
Trajectory Data ◽  
Transport Services ◽  
Spring Festival ◽  
Before And After ◽  
The Impact

Public transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festival in Shenzhen, China, are used to explore such interaction patterns. A time-series clustering method and an elasticity change index (ECI) are adopted to detect the changing transit mode patterns and the underlying dynamics. The findings indicate that the interactions between different transit modes vary over space and time and are competitive or complementary in different parts of the city. Both ordinary least-squares (OLS) and geographically weighted regression (GWR) models with built environment variables are used to reveal the impact of changes in different transit modes on ECIs and their linkage with the built environment. The results of this study will contribute to the planning and design of multi-modal transport services.

Cellular Responses to Exposure to Outdoor Air from the Chinese Spring Festival at the Air–Liquid Interface

2019 ◽  
Vol 53 (15) ◽  
pp. 9128-9138 ◽  
Author(s):  
Jie Ding ◽  
Jincheng Guo ◽  
Liming Wang ◽  
Yandong Chen ◽  
Bin Hu ◽  
...  
Keyword(s):  
Chinese Spring ◽  
Cellular Responses ◽  
Liquid Interface ◽  
Outdoor Air ◽  
Spring Festival ◽  
Air Liquid Interface

scholarly journals Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model

2020 ◽  
Vol 9 (11) ◽  
pp. 670
Author(s):  
Tao Zhou ◽  
Bo Huang ◽  
Xiaoqian Liu ◽  
Guangqin He ◽  
Qiang Gou ◽  
...  
Keyword(s):  
Urban Development ◽  
Chinese Spring ◽  
Large Scale ◽  
Spatial Interaction ◽  
Value Added ◽  
Flow Patterns ◽  
City Development ◽  
Migration Patterns ◽  
Horizontal Structure ◽  
Spring Festival

Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution migration datasets and insufficient consideration of interactive differences have limited such exploration. Accordingly, based on 2019 Chinese Spring Festival travel-related big data from the AMAP platform, we used social network analysis (SNA) methods to accurately reveal population flow patterns. Then, with consideration of the spatial heterogeneity of interactive patterns, we used spatially weighted interactive models (SWIMs), which were improved by the incorporation of weightings into the global Poisson gravity model, to efficiently quantify the effect of socioeconomic factors on migration patterns. These SWIMs generated the local characteristics of the interactions and quantified results that were more regionally consistent than those generated by other spatial interaction models. The migration patterns had a spatially vertical structure, with the city development level being highly consistent with the flow intensity; for example, the first-level developments of Beijing, Shanghai, Chengdu, Guangzhou, Shenzhen, and Chongqing occupied a core position. A spatially horizontal structure was also formed, comprising 16 closely related city communities. Moreover, the quantified impact results indicated that migration pattern variation was significantly related to the population, value-added primary and secondary industry, the average wage, foreign capital, pension insurance, and certain aspects of unbalanced urban development. These findings can help policymakers to guide population migration, rationally allocate industrial infrastructure, and balance urban development.

scholarly journals The impact of traffic isolation in Wuhan on the spread of 2019-nCov

2020 ◽  
Author(s):  
Gehui Jin ◽  
Jiayu Yu ◽  
Liyuan Han ◽  
Shiwei Duan
Keyword(s):  
Mortality Rate ◽  
Chinese Spring ◽  
Mainland China ◽  
Hubei Province ◽  
Migrant Population ◽  
Migration Index ◽  
Spring Festival ◽  
The Impact

The 2019-nCoV outbreak occurred near the Chinese Spring Festival transport period in Wuhan. As an important transportation center, the migration of Wuhan accelerated the spread of 2019-nCoV across mainland China. Based on the cumulative Baidu migration index (CBMI), we first analyzed the proportion of Wuhan’s migrant population to other cities. Our results confirm that there is a significant correlation between the export population of Wuhan and reported cases in various regions. We subsequently found that the mortality rate in Hubei Province was much higher than that in other regions of mainland China, while the investigation of potential cases in Wuhan was far behind other provinces in Mainland China, which indicates the effectiveness of early isolation.

scholarly journals The Implication of Road Toll Discount for Mode Choice: Intercity Travel during the Chinese Spring Festival Holiday

2018 ◽  
Vol 10 (8) ◽  
pp. 2700 ◽  
Author(s):  
Xiaomei Lin ◽  
Yusak Susilo ◽  
Chunfu Shao ◽  
Chengxi Liu
Keyword(s):  
Chinese Spring ◽  
High Speed ◽  
Public Transit ◽  
Mode Choice ◽  
Mixed Logit ◽  
Negative Effects ◽  
High Speed Rail ◽  
The Public ◽  
Spring Festival ◽  
Intercity Travel

Intercity travel congestion during the main national holidays takes place every year at different places around the world. Charge reduction measurements on existing toll roads have been implemented to promote an efficient use of the expressways and to reduce congestion on the public transit networks. However, some of these policies have had negative effects. A more comprehensive understanding of the determinants of holiday intercity travel patterns is critical for better policymaking. This paper aims to investigate the effectiveness of the road toll discount policy on mode choice behavior for intercity travel. A mixed logit model is developed to model the mode choices of intercity travelers, which is estimated based on survey data about intercity journeys from Beijing during the 2017 Chinese Spring Festival holiday. The policy impact is further discussed by elasticity and scenario simulations. The results indicate that the expressway toll discount does increase the car use and decrease the public transit usage. Given the decreased toll on expressways, the demand tends to shift from car to public transit, in an order of coach, high-speed rail, conventional rail, and airplane. When it comes to its effect on socio-demographic groups, men and lower-income travelers are identified to be more likely to change mode in response to variation of road toll. Finally, policy effectiveness is found to vary for travelers in different travel distance groups. Conclusions provide useful insights on road pricing management.

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