scholarly journals Using GPS-enabled mobile phones to evaluate the associations between human mobility changes and the onset of influenza illness

2021 ◽  
pp. 100458
Author(s):  
Youngseob Eum ◽  
EunHye Yoo
Keyword(s):  
Mobile Phones ◽  
Human Mobility ◽  
Influenza Illness

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

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.

Problems Rendezvousing

2008 ◽  
pp. 35-54
Author(s):  
Martin Colbert
Keyword(s):  
University Students ◽  
Mobile Phones ◽  
Mobile Technology ◽  
Human Mobility ◽  
Diary Study ◽  
User Performance ◽  
Mobile Telephones

This chapter seeks opportunities to use mobile technology to improve human mobility. To this end, the chapter reports a diary study of university students’ use of mobile telephones for rendezvousing—arranging, and traveling to, informal meetings with friends and family. This diary study reveals, and suggests explanations for, a number of deficits in user performance: (1) rendezvousers occasionally become highly stressed and lose valuable opportunities; (2) outcomes are worse when rendezvousing at unfamiliar locations; (3) 31 to 45 year olds report more personal sacrifices than 18 to 30 year olds; and (4) when mobile phones are used on the move, the experience of communication is slightly worse than when phones are used prior to departure. Ways of using mobile technology to make good these deficits are suggested.

scholarly journals Measuring mobility, disease connectivity and individual risk: a review of using mobile phone data and mHealth for travel medicine

2019 ◽  
Vol 26 (3) ◽  
Author(s):  
Shengjie Lai ◽  
Andrea Farnham ◽  
Nick W Ruktanonchai ◽  
Andrew J Tatem
Keyword(s):  
Health Risk ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Spatial Scales ◽  
Human Mobility ◽  
Travel Medicine ◽  
Mobile Phone Data ◽  
Individual Risk ◽  
Spatial And Temporal Scales ◽  
Human Movements

Abstract Rationale for review The increasing mobility of populations allows pathogens to move rapidly and far, making endemic or epidemic regions more connected to the rest of the world than at any time in history. However, the ability to measure and monitor human mobility, health risk and their changing patterns across spatial and temporal scales using traditional data sources has been limited. To facilitate a better understanding of the use of emerging mobile phone technology and data in travel medicine, we reviewed relevant work aiming at measuring human mobility, disease connectivity and health risk in travellers using mobile geopositioning data. Key findings Despite some inherent biases of mobile phone data, analysing anonymized positions from mobile users could precisely quantify the dynamical processes associated with contemporary human movements and connectivity of infectious diseases at multiple temporal and spatial scales. Moreover, recent progress in mobile health (mHealth) technology and applications, integrating with mobile positioning data, shows great potential for innovation in travel medicine to monitor and assess real-time health risk for individuals during travel. Conclusions Mobile phones and mHealth have become a novel and tremendously powerful source of information on measuring human movements and origin–destination-specific risks of infectious and non-infectious health issues. The high penetration rate of mobile phones across the globe provides an unprecedented opportunity to quantify human mobility and accurately estimate the health risks in travellers. Continued efforts are needed to establish the most promising uses of these data and technologies for travel health.

Human Mobility Estimation Following Massive Disaster Using Filtering Approach

2016 ◽  
Vol 11 (2) ◽  
pp. 217-224 ◽  
Author(s):  
Akihito Sudo ◽  
◽  
Takehiro Kashiyama ◽  
Takahiro Yabe ◽  
Hiroshi Kanasugi ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Real Time ◽  
Mobile Phones ◽  
Large Scale ◽  
Population Distribution ◽  
Human Mobility ◽  
Time Estimation ◽  
Observation Data ◽  
Real Time Estimation ◽  
Using Data

Real-time estimation of people distribution immediately after a disaster is directly related to disaster reduction and is also highly beneficial in society. Recently, traffic estimation research has been actively performed using data assimilation techniques for observation data obtained from mobile phones. However, there has been no research on data assimilation technique using real-time gridded aggregated observation data obtained from mobile phones, which are available and can be used to estimate population flow and distribution in a metropolitan area during a large-scale disaster. In this research, population distribution in an urban area during a disaster was estimated using gridded aggregated observation data obtained from mobile phones, using particle filter. The experimental results indicated that the particle filters enabled high-precision real-time estimation in the Kanto district.

scholarly journals New Approaches to Human Mobility: Using Mobile Phones for Demographic Research

Demography ◽  
2012 ◽  
Vol 50 (3) ◽  
pp. 1105-1128 ◽  
Author(s):  
John R. B. Palmer ◽  
Thomas J. Espenshade ◽  
Frederic Bartumeus ◽  
Chang Y. Chung ◽  
Necati Ercan Ozgencil ◽  
...  
Keyword(s):  
Mobile Phones ◽  
Human Mobility ◽  
Demographic Research ◽  
New Approaches

scholarly journals The relationship between human mobility measures and SAR-Cov-2 transmission varies by epidemic phase and urbanicity: results from the United States

2021 ◽  
Author(s):  
Nishant Kishore ◽  
Aimee R Taylor ◽  
Pierre E Jacob ◽  
Navin Vembar ◽  
Ted Cohen ◽  
...  
Keyword(s):  
United States ◽  
Mobile Phones ◽  
Human Mobility ◽  
Population Level ◽  
The United States ◽  
Mobile Phone Data ◽  
Reproductive Number ◽  
Generation Process ◽  
Data Generation ◽  
The Relationship

Global efforts to prevent the spread of the SARS-COV-2 pandemic in early 2020 focused on non-pharmaceutical interventions like social distancing; policies that aim to reduce transmission by changing mixing patterns between people. As countries have implemented these interventions, aggregated location data from mobile phones have become an important source of real-time information about human mobility and behavioral changes on a population level. Human activity measured using mobile phones reflects the aggregate behavior of a subset of people, and although metrics of mobility are related to contact patterns between people that spread the coronavirus, they do not provide a direct measure. In this study, we use results from a nowcasting approach from 1,396 counties across the US between January 22nd, 2020 and July 9th, 2020 to determine the effective reproductive number (R(t)) along an urban/rural gradient. For each county, we compare the time series of R(t) values with mobility proxies from mobile phone data from Camber Systems, an aggregator of mobility data from various providers in the United States. We show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties compared to baseline, but that the relationship weakens considerably after the initial 15 weeks of the epidemic, consistent with the emergence of a more complex ecosystem of local policies and behaviors including masking. Importantly, we highlight potential issues in the data generation process, representativeness and equity of access which must be addressed to allow for general use of these data in public health.

MOBILE PHONES AND YOUR HEALTH

Pathology ◽  
2001 ◽  
Vol 33 (3) ◽  
pp. 269-270
Author(s):  
Clive G. Harper ◽  
Victor K. Lee
Keyword(s):  
Mobile Phones

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Going digital on low-cost mobile phones in Bangladesh

2011 ◽  
Author(s):  
Christopher S. Walsh ◽  
Tom Power
Keyword(s):  
Mobile Phones ◽  
Low Cost
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