ABSTRACT
Exploratory data analysis tools designed to measure global and local spatial autocorrelation (e.g. Moran's (Formula presented.) statistic) have become standard in modern GIS software. However, there has been little development in amending these tools for visualization and analysis of patterns captured in spatio-temporal data. We design and implement an exploratory mapping tool, VASA (Visual Analysis for Spatial Association), that streamlines analytical pipelines in assessing spatio-temporal structure of data and enables enhanced visual display of the patterns captured in data. Specifically, VASA applies a set of cartographic visual variables to map local measures of spatial autocorrelation and helps delineate micro and macro trends in space-time processes. Two visual displays are presented: recency and consistency map and line-scatter plots. The former combines spatial and temporal data view of local clusters, while the latter drills down on the temporal trends of the phenomena. As a case study, we demonstrate the usability of VASA for the investigation of mobility patterns in response to the COVID-19 pandemic throughout 2020 in the United States. Using daily county-level and grid-level mobility metrics obtained from three different sources (SafeGraph, Cuebiq, and Mapbox), we demonstrate cartographic functionality of VASA for a swift exploratory analysis and comparison of mobility trends at different regional scales. © 2023 Cartography and Geographic Information Society.
ABSTRACT
Over the past two years, China has wrested domestic control of the COVID-19 pandemic through non-pharmaceutical interventions. However, the extent to which the pandemic has changed people's travel behavior in the new normal under the zero-COVID policy is not yet clear. This study investigates the profound effects of the zero-COVID strategy on human mobility in 365 Chinese cities over time. Our results suggest the following: (1) Even between city pairs with no local cases, intercity mobility decreased by an average of 16%, whereas intra-city mobility increased by 9% compared with the pre-pandemic baseline. Long-distance travel decreased substantially, while trips below 100 km increased slightly. These new trends indicate a localized pattern which is presumably caused by the wide adoption of teleworking and virtual classes, as well as concerns about the safety and availability of public transportation. (2) Containment measures caused a considerably acute decline in intercity short-distance trips but exerted a markedly lasting effect on long-distance trips. (3) Cities with lower levels of urbanization, smaller population sizes, less labor force, and lower GDP and GDP per capita experienced greater reductions in mobility, which may be due to their insufficient management capabilities. (4) The Chinese government has adopted adaptive measures to contain outbreaks. Stricter and more timely responses led to faster recoveries in the second half of 2021 compared with the first half. Inter- and intra-city mobility decreased by 41% and 26%, respectively, within the first 2 weeks of an outbreak, and it took 6-7 weeks to return to pre-outbreak levels. © The Author(s) 2023.
ABSTRACT
Human mobility during the centuries of industrial development has long been studied using interpretative models in which movements inside and outside urban areas have been considered in relation to successive phases of economic development. In more recent times the study of mobility has highlighted the overlapping of phenomena hitherto considered to be unrelated, such as commuting, tourism and migration. The hybrid nature of sundry phenomena has required a distinction to be made: production-related mobility and consumption-related mobility. Measures introduced to combat the Covid-19 pandemic have brought further changes to reference parameters in this sphere. At this early stage we have some clues as to the possible development of human mobility in the future. We may realistically imagine that large urban areas will no longer be viewed as areas of concentration and overlap of all human activities. It is therefore necessary to look again at the parameters of human mobility in relation to new time and space parameters. © 2022 Societe Belge de Geographie. All rights reserved.
ABSTRACT
COVID-19 has dramatically changed people's mobility patterns. This report aims to analyze the impact of COVID-19 on people's mobility through statistics and comparing the visits of POIs (Point-Of-Interests) in New York State in 2019 and 2020. The report uses data from SafeGraph, which is a data company. The raw data contains POI visits across the United States in 2019 and 2020. Considering the analysis size and difficulty of the data, POI visits from New York State are extracted for analysis, and POI locations are classified according to the tags provided by the source data. The scale of analysis is from macro to micro, and they are the total POI visits data of New York State based on different ways in 2019 and 2020, the POI visits of CBG (Census Block Group) division in New York City, and three representative POI samples to do individual analysis. The analysis methods are: (1) use line plot and bar plot statistics to compare the trends of POI visits data from 2019 to 2020, and (2) make the spatial visualization comparison, which includes grid map, scatter map, heatmap, and OD map, between the first peak of epidemic impact in the first full week of April 2019 and April 2020, and the scope is narrowed to New York City. Wherein the OD maps are drawn based on the CBG division. Compared to related work, the analysis object includes CBG, categories, and individual POI. In addition, the analysis method combines statistical graphs and spatial visualizations and explores the policy impact of the New York City government. This report adopts more multidimensional analysis methods and objects to improve the comprehensiveness and reliability of the analysis content. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic has completely disrupted and possibly permanently changed the way humans travel. In Puerto Rico, major travel restrictions to the island have persisted at different levels since March 2020, which heavily influenced residents' travel behaviors. However, it remains unclear about how big the impact is and how inequitable it might be. The goal of this study is to evaluate COVID-19's impacts on Puerto Rican's travel behaviors by analyzing travel flows from Puerto Rico to the contiguous US with a modified gravity model. The roles of socioeconomic factors regarding the Puerto Rican travelers and COVID-19 factors regarding the destination US states have been assessed. COVID-19 was a strong deterring factor of travel at the beginning of the pandemic and also in the winter of 2020, but it did not keep Puerto Ricans from traveling during the summer 2020 when most travel restrictions were lifted. We found that the elderly population of Puerto Rico, despite being more vulnerable to COVID-19, were much more likely to travel during the pandemic. We also found that, during the holiday season in 2020, some socioeconomically disadvantaged populations were more likely to be traveling, a direct contradiction to their travel flows the year prior. These findings shed light on about how disproportionately affected populations behavior changed from pre-pandemic to after the pandemic started. With the continuance of the pandemic, this information is extremely valuable for future planning with respect to emergency management, travel regulation, and social benefit. © 2023 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
New York has become one of the worst-affected COVID-19 hotspots and a pandemic epicenter due to the ongoing crisis. This paper identifies the impact of the pandemic and the effectiveness of government policies on human mobility by analyzing multiple datasets available at both macro and micro levels for New York City. Using data sources related to population density, aggregated population mobility, public rail transit use, vehicle use, hotspot and non-hotspot movement patterns, and human activity agglomeration, we analyzed the inter-borough and intra-borough movement for New York City by aggregating the data at the borough level. We also assessed the internodal population movement amongst hotspot and non-hotspot points of interest for the month of March and April 2020. Results indicate a drop of about 80% in people’s mobility in the city, beginning in mid-March. The movement to and from Manhattan showed the most disruption for both public transit and road traffic. The city saw its first case on March 1, 2020, but disruptions in mobility can be seen only after the second week of March when the shelter in place orders was put in effect. Owing to people working from home and adhering to stay-at-home orders, Manhattan saw the largest disruption to both inter- and intra-borough movement. But the risk of spread of infection in Manhattan turned out to be high because of higher hotspot-linked movements. The stay-at-home restrictions also led to an increased population density in Brooklyn and Queens as people were not commuting to Manhattan. Insights obtained from this study would help policymakers better understand human behavior and their response to the news and governmental policies. Copyright © 2022 Rajput, Li, Gao and Mostafavi.
ABSTRACT
In this paper we analyze the average hourly temporal dynamics of human mobility in the United States from 2019 to 2020. We discuss how large decreases in human mobility nonuniformly effect the daily temporal dynamics of aggregate human behavior. The data used are weekly activity patterns for POIs from 2019 to 2020 in the United States, provided by SafeGraph and made openly available to academic and research institutions. We use clustering methods to create metrics describing how human activity changes throughout the day/week at the county and national levels. In response to significant mobility reductions starting March 2020, daily temporal patterns of human activity changed nonuniformly. Morning activity started later, and evening activity started earlier in 2020 compared to 2019, and temporal behavioral patterns on weekdays began to look more similar to weekends. The changes in daily temporal behavior persisted throughout the year even as total mobility levels recovered. The results provide insights on the changes in human behavior in response covid-19 policies and illustrate influences on social systems, health, and transportation networks. © 2022 The Authors
ABSTRACT
In 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.