Meteorological and human mobility data on predicting COVID-19 cases by a novel hybrid decomposition method with anomaly detection analysis: a case study in the capitals of Brazil

AbstractSince spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.

Download Full-text

Segregation or integration? Exploring activity disparities between migrants and settled urban residents using human mobility data

Transactions in GIS ◽

10.1111/tgis.12760 ◽

2021 ◽

Author(s):

Qi‐Li Gao ◽

Yang Yue ◽

Wei Tu ◽

Jinzhou Cao ◽

Qing‐Quan Li

Keyword(s):

Human Mobility ◽

Urban Residents ◽

Mobility Data

Download Full-text

Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study using Floating Car Data in the Paris Region

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198121995500 ◽

2021 ◽

pp. 036119812199550

Author(s):

Danyang Sun ◽

Fabien Leurent ◽

Xiaoyan Xie

Keyword(s):

Large Scale ◽

City Planning ◽

Human Mobility ◽

Work Place ◽

Trajectory Data ◽

Floating Car Data ◽

Vehicle Trajectories ◽

Activity Types ◽

Paris Region

In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.

Download Full-text

Towards Sustainable Mobility? The Influence of the COVID-19 Pandemic on Romanian Mobile Citizens in Spain

Sustainability ◽

10.3390/su13074023 ◽

2021 ◽

Vol 13 (7) ◽

pp. 4023

Author(s):

Silvia Marcu

Keyword(s):

Sustainable Development Goals ◽

Human Mobility ◽

Sustainable Mobility ◽

The Sustainable Development ◽

New Models ◽

Challenges And Opportunities ◽

Development Goals ◽

Depth Interviews

Using the case study of Romanians in Spain, this article highlights how the COVID-19 crisis presents both challenges and opportunities when it comes to human mobility and sustainability. Drawing on in-depth interviews with mobile people during the period of lockdown and circulation restrictions, and in accordance with the objectives of the Sustainable Development Goals (SDGs), the paper advances and contributes to the relevance of sustainability and its impact on people’s mobility in the context of the COVID-19 pandemic. I argue that even in the midst of the crisis, sustainable ways may be found to promote and protect human mobility. The paper raises the way sustainability acts as a driver, gains relevance and influence, and contributes to the creation of new models of resilient mobility in times of crisis. The conclusions defend the respect for the SDGs regarding human mobility and emphasise the role of people on the move as sustainable actors learning to overcome distance and the barriers to their mobility during the pandemic.

Download Full-text

Mobility Patterns in Different Age Groups in Japan during the COVID-19 Pandemic: a Small Area Time Series Analysis through March 2021

Journal of Urban Health ◽

10.1007/s11524-021-00566-7 ◽

2021 ◽

Author(s):

Shuhei Nomura ◽

Yuta Tanoue ◽

Daisuke Yoneoka ◽

Stuart Gilmour ◽

Takayuki Kawashima ◽

...

Keyword(s):

Care Delivery ◽

Human Mobility ◽

Age Groups ◽

Virus Transmission ◽

Initial Response ◽

Health Care Delivery System ◽

Population Characteristics ◽

Mobility Patterns ◽

Mobility Data ◽

The Status

AbstractIn the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan—each defined as an area overlaid by several 125-meter grids—from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.

Download Full-text

Comparative Analysis of Geolocation Information through Mobile-Devices under Different COVID-19 Mobility Restriction Patterns in Spain

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10020073 ◽

2021 ◽

Vol 10 (2) ◽

pp. 73

Author(s):

Raquel Pérez-Arnal ◽

David Conesa ◽

Sergio Alvarez-Napagao ◽

Toyotaro Suzumura ◽

Martí Català ◽

...

Keyword(s):

Mobile Phones ◽

Human Mobility ◽

The Other ◽

Data Sources ◽

Experimental Setting ◽

Mobile Data ◽

Restriction Patterns ◽

Mobility Data ◽

The World ◽

Proper Interpretation

The COVID-19 pandemic is changing the world in unprecedented and unpredictable ways. Human mobility, being the greatest facilitator for the spread of the virus, is at the epicenter of this change. In order to study mobility under COVID-19, to evaluate the efficiency of mobility restriction policies, and to facilitate a better response to future crisis, we need to understand all possible mobility data sources at our disposal. Our work studies private mobility sources, gathered from mobile-phones and released by large technological companies. These data are of special interest because, unlike most public sources, it is focused on individuals rather than on transportation means. Furthermore, the sample of society they cover is large and representative. On the other hand, these data are not directly accessible for anonymity reasons. Thus, properly interpreting its patterns demands caution. Aware of that, we explore the behavior and inter-relations of private sources of mobility data in the context of Spain. This country represents a good experimental setting due to both its large and fast pandemic peak and its implementation of a sustained, generalized lockdown. Our work illustrates how a direct and naive comparison between sources can be misleading, as certain days (e.g., Sundays) exhibit a directly adverse behavior. After understanding their particularities, we find them to be partially correlated and, what is more important, complementary under a proper interpretation. Finally, we confirm that mobile-data can be used to evaluate the efficiency of implemented policies, detect changes in mobility trends, and provide insights into what new normality means in Spain.

Download Full-text