Quantifying human mobility resilience to the COVID-19 pandemic: A case study of Beijing, China

Liu, Yaxi; Wang, Xi; Ci, Song; Chen, Jie; Shu, Huan; Wu, Mingbo; Guo, Sihui; Huang, Qiang; Pei, Tao

doi:10.1016/j.scs.2022.104314

Cited by 18 publications

(5 citation statements)

References 91 publications

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“…In two waves of the epidemic in Hunan, due to different influencing factors, road transport resilience showed different heterogeneity patterns, which are consistent with previous research [60]. We can explain this result with the following factors.…”

Section: Potential Influencing Factors Of Road Transport Resiliencesupporting

confidence: 90%

“…The finding that there is regional heterogeneity [11,12] in road transport resilience under the same external disturbance is consistent with the results of previous research. This result may be related to the differences in epidemic prevention and control measures, travel willingness, and travel demand of residents, which have been analyzed in existing studies [58][59][60]. Specifically, the resilience of road transport in Beijing and Hunan is higher than that in Shanghai and Xinjiang.…”

Section: Potential Influencing Factors Of Road Transport Resiliencementioning

confidence: 99%

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Quantifying Road Transport Resilience to Emergencies: Evidence from China

Zhang,

Lu,

Wang

et al. 2023

Sustainability

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Facing the shock of emergencies, how resilient is the road transport system? In this process, how are the system’s absorption capacity, adaptability, and recovery capacity? These are very important for the development of sustainable road transportation. Taking China’s road transport during the COVID-19 pandemic as the research object, this paper introduces an integrated resilience quantification method, draws a road transport resilience curve, and comprehensively and dynamically analyzes and compares the resilience of China’s road transport system at different stages among different regions and under different epidemic waves. The results show that the resilience of road passenger and freight transport differs in the face of external disturbance. Freight transport resilience is better than that of passenger transport. Compared to passenger transport, freight transport is more robust; the impacted speed is slower, the recovery speed is faster, the recovery capacity is stronger, and the affected period is shorter. There is regional heterogeneity in road transport resilience. This heterogeneity is reflected in the whole change process of system performance with external disturbance, including absorption capacity, adaptation capacity, and recovery capacity. The resilience of road transport under different waves of the epidemic is different. Compared to the first wave of the epidemic, the resilience of road transport indicators at all stages has been dramatically improved in the later rebound wave of the epidemic. This can help in the development of evidence-based road transport sustainability strategies.

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Section: Potential Influencing Factors Of Road Transport Resiliencesupporting

confidence: 90%

Section: Potential Influencing Factors Of Road Transport Resiliencementioning

confidence: 99%

Quantifying Road Transport Resilience to Emergencies: Evidence from China

Zhang,

Lu,

Wang

et al. 2023

Sustainability

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“…The resilience of travel behaviors could describe changes in the urban/metro systems, transit stations, communities, and individuals and how they influence the desirable performance or goals of the latter. So far, the citywide resilience of travel behaviors has been conceptualized and measured in the existing studies ( Liu et al, 2023 ; Lu et al, 2022 ). The resilience of travel behaviors has also been used to examine responses from certain communities and individuals where people travel to and from and their impacts on the performance and goals mentioned above ( Hong et al, 2021 ; Podesta et al, 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong

Zhou

et al. 2023

Cities

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“…Climate warming will lead to an increase in household electricity consumption, while energy consumption will decrease [17]. Wenz conducted a related study on 35 European countries, and the results indicate that climate change will increase electricity consumption in some countries while decreasing it in certain cities. Extreme weather events will also cause a spatial redistribution of demand from north to south [18].…”

Section: Related Workmentioning

confidence: 99%

“…Zhang used indicators like vulnerability, robustness, speed, and return level to assess the impact of the COVID-19 pandemic on the subway system [34]. Liu utilized mobile signal data along with metrics like mobile population ratio, daily travel distance, and activity entropy, to measure the impact of the COVID-19 pandemic on population mobility and explored factors influencing population movement [35]. Hong utilized large-scale mobile data to quantify community-level evacuation and recovery patterns in Houston during Hurricane Harvey [36].…”

Section: Related Workmentioning

confidence: 99%

Quantitative Assessment of the Impact of Extreme Events on Electricity Consumption

Xiong,

Yan,

Qin

et al. 2023

Energies

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Global energy consumption is growing rapidly, with the frequency and intensity of extreme events constantly increasing, posing a long-term threat to power supply and consumption. Therefore, analyzing the spatiotemporal characteristics of electricity consumption and quantitatively assessing the impact of extreme events on electricity consumption are of great significance. Based on fine-grained electricity consumption data from Europe for the years 2019–2022, this paper employs a data mining perspective and four methods including Z-score, Isolation Forest, Local Outlier Factor, and Autoencoder to detect abnormal electricity consumption during extreme events. Additionally, it combines indicators such as elastic loss, vulnerability, and duration to measure the impact of extreme events on electricity consumption. It is found that low temperatures could lead to abrupt changes in electricity consumption, with Northern Europe being more significantly affected by low temperatures. The COVID-19 pandemic had the most significant impact on electricity consumption in Europe, with the middle part of Europe being the hardest hit during the first wave of the pandemic. Electricity anomalies during the pandemic period were related to national pandemic control policies and exhibited some lag. High temperatures persisted for a longer duration in the middle part of Europe.

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Quantifying human mobility resilience to the COVID-19 pandemic: A case study of Beijing, China

Cited by 18 publications

References 91 publications

Quantifying Road Transport Resilience to Emergencies: Evidence from China

Quantifying Road Transport Resilience to Emergencies: Evidence from China

Metro travel and perceived COVID-19 infection risks: A case study of Hong Kong

Quantitative Assessment of the Impact of Extreme Events on Electricity Consumption

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