scholarly journals On-site Dining in Tokyo During the COVID-19 Pandemic: Time Series Analysis Using Mobile Phone Location Data (Preprint)

2021 ◽  
Author(s):  
Miharu Nakanishi ◽  
Ryosuke Shibasaki ◽  
Syudo Yamasaki ◽  
Satoshi Miyazawa ◽  
Satoshi Usami ◽  
...  
Keyword(s):  
Public Health ◽  
Mobile Phone ◽  
Social Dynamics ◽  
Time Lags ◽  
Tokyo Metropolitan ◽  
Metropolitan Government ◽  
Location Data ◽  
Mobility Data ◽  
Volume Coefficient ◽  
And Behavior

BACKGROUND During the second wave of COVID-19 in August 2020, the Tokyo Metropolitan Government implemented public health and social measures to reduce on-site dining. Assessing the associations between human behavior, infection, and social measures is essential to understand achievable reductions in cases and identify the factors driving changes in social dynamics. OBJECTIVE The aim of this study was to investigate the association between nighttime population volumes, the COVID-19 epidemic, and the implementation of public health and social measures in Tokyo. METHODS We used mobile phone location data to estimate populations between 10 PM and midnight in seven Tokyo metropolitan areas. Mobile phone trajectories were used to distinguish and extract on-site dining from stay-at-work and stay-at-home behaviors. Numbers of new cases and symptom onsets were obtained. Weekly mobility and infection data from March 1 to November 14, 2020, were analyzed using a vector autoregression model. RESULTS An increase in the number of symptom onsets was observed 1 week after the nighttime population volume increased (coefficient=0.60, 95% CI 0.28 to 0.92). The effective reproduction number significantly increased 3 weeks after the nighttime population volume increased (coefficient=1.30, 95% CI 0.72 to 1.89). The nighttime population volume increased significantly following reports of decreasing numbers of confirmed cases (coefficient=–0.44, 95% CI –0.73 to –0.15). Implementation of social measures to restaurants and bars was not significantly associated with nighttime population volume (coefficient=0.004, 95% CI –0.07 to 0.08). CONCLUSIONS The nighttime population started to increase after decreasing incidence of COVID-19 was announced. Considering time lags between infection and behavior changes, social measures should be planned in advance of the surge of an epidemic, sufficiently informed by mobility data.

scholarly journals Challenges in Contact Tracing by Mining Mobile Phone Location Data for COVID-19: Implications for Public Governance in South Africa

10.28945/4736 ◽  
2021 ◽  
Vol 16 ◽  
pp. 101-124
Author(s):  
Paul Kariuki ◽  
Lizzy O Ofusori ◽  
Prabhakar Rontala Subramanniam ◽  
Moses Okpeku ◽  
Maria L Goyayi
Keyword(s):  
Public Health ◽  
South Africa ◽  
Mobile Phone ◽  
Contact Tracing ◽  
Future Research ◽  
Public Governance ◽  
The Public ◽  
Location Data ◽  
Pertinent Data ◽  
Privacy And Confidentiality

Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving.

scholarly journals Visualizing Social and Behavior Change due to the Outbreak of COVID-19 Using Mobile Phone Location Data

2021 ◽  
Author(s):  
Takayuki Mizuno ◽  
Takaaki Ohnishi ◽  
Tsutomu Watanabe
Keyword(s):  
Behavior Change ◽  
Mobile Phone ◽  
Shopping Centers ◽  
Residential Areas ◽  
Night Time ◽  
Location Data ◽  
The Difference ◽  
And Behavior

AbstractWe visualize the rates of stay-home for residents by region using the difference between day-time and night-time populations to detect residential areas, and then observing the numbers of people leaving residential areas. There are issues with measuring stay-home rates by observing numbers of people visiting downtown areas, such as central urban shopping centers and major train stations. The first is that we cannot eliminate the possibility that people will avoid areas being observed and go to other areas. The second is that for people visiting downtown areas, we cannot know where they reside. These issues can be resolved if we quantify the degree of stay-home using the number of people leaving residential areas. There are significant differences in stay-home levels by region throughout Japan. By this visualization, residents of each region can see whether their level of stay-home is adequate or not, and this can provide incentive toward compliance suited to the residents of the region.

scholarly journals Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar

2021 ◽  
Author(s):  
Tanjona Ramiadantsoa ◽  
C. Jessica E. Metcalf ◽  
Antso Hasina Raherinandrasana ◽  
Santatra Randrianarisoa ◽  
Benjamin L. Rice ◽  
...  
Keyword(s):  
Public Health ◽  
Mobile Phone ◽  
Gravity Model ◽  
Human Mobility ◽  
Health Planning ◽  
Data Availability ◽  
Disease Spread ◽  
Mobile Phone Data ◽  
Migration Flow ◽  
Mobility Data

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches, but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

scholarly journals Detecting and Reducing Biases in Cellular-Based Mobility Data Sets

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 736
Author(s):  
Alicia Rodriguez-Carrion ◽  
Carlos Garcia-Rubio ◽  
Celeste Campo
Keyword(s):  
Mobile Phone ◽  
Mobile Networks ◽  
Human Mobility ◽  
Mobility Model ◽  
Data Sets ◽  
Location Data ◽  
Mobility Data ◽  
Key Factor ◽  
Data Collection Approach ◽  
Call Detail Records

Correctly estimating the features characterizing human mobility from mobile phone traces is a key factor to improve the performance of mobile networks, as well as for mobility model design and urban planning. Most related works found their conclusions on location data based on the cells where each user sends or receives calls or messages, data known as Call Detail Records (CDRs). In this work, we test if such data sets provide enough detail on users’ movements so as to accurately estimate some of the most studied mobility features. We perform the analysis using two different data sets, comparing CDRs with respect to an alternative data collection approach. Furthermore, we propose three filtering techniques to reduce the biases detected in the fraction of visits per cell, entropy and entropy rate distributions, and predictability. The analysis highlights the need for contextualizing mobility results with respect to the data used, since the conclusions are biased by the mobile phone traces collection approach.

Risk Attitudes and Behavior Among Norwegian Adolescents

2005 ◽  
Vol 10 (1) ◽  
pp. 25-38 ◽  
Author(s):  
Hilde Iversen ◽  
Torbjørn Rundmo ◽  
Hroar Klempe
Keyword(s):  
Public Health ◽  
Traffic Safety ◽  
Behavior Modification ◽  
Health Programs ◽  
Risk Attitudes ◽  
Community Based ◽  
Public Health Programs ◽  
The Core ◽  
And Behavior ◽  
Attitudes And Behavior

Abstract. The core aim of the present study is to compare the effects of a safety campaign and a behavior modification program on traffic safety. As is the case in community-based health promotion, the present study's approach of the attitude campaign was based on active participation of the group of recipients. One of the reasons why many attitude campaigns conducted previously have failed may be that they have been society-based public health programs. Both the interventions were carried out simultaneously among students aged 18-19 years in two Norwegian high schools (n = 342). At the first high school the intervention was behavior modification, at the second school a community-based attitude campaign was carried out. Baseline and posttest data on attitudes toward traffic safety and self-reported risk behavior were collected. The results showed that there was a significant total effect of the interventions although the effect depended on the type of intervention. There were significant differences in attitude and behavior only in the sample where the attitude campaign was carried out and no significant changes were found in the group of recipients of behavior modification.

“Scrub”

2012 ◽  
Vol 642 (1) ◽  
pp. 86-95 ◽  
Author(s):  
Scott N. Brooks
Keyword(s):  
Social Dynamics ◽  
Social Worlds ◽  
Site Analysis ◽  
Ethnographic Fieldwork ◽  
The Social ◽  
Specific Setting ◽  
Group Members ◽  
And Behavior ◽  
Complete Account

Conducting ethnographic fieldwork in varied spaces, with different actors, enriches our understanding. A researcher may find paradoxes in practices and ideas and ask for clarification, or recognize that social dynamics and behavior are peculiar to group members present in a specific setting. This article highlights the usefulness of intentional variability and flexibility in the field. Researchers should plan to do multi-site analysis (MSA) to look for negative cases and opportunities to challenge commonsense notions. Additionally, this article emphasizes that the relationships built during fieldwork shape the data that are captured. Therefore, researchers need to consider the bases for their relationships, including what the subjects get out of them, and how subjects’ positionality affects what comes to be known. This perspective de-emphasizes false norms of objectivity and renders a more complete account of the social worlds we study.

scholarly journals Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model

2016 ◽  
Vol 11 (1s) ◽  
Author(s):  
Adrian M. Tompkins ◽  
Nicky McCreesh
Keyword(s):  
Mobile Phone ◽  
Malaria Transmission ◽  
Gravity Model ◽  
Mobile Phone Data ◽  
Agent Based ◽  
Migration Model ◽  
Location Data ◽  
Home Location ◽  
One Year ◽  
Overnight Stays

One year of mobile phone location data from Senegal is analysed to determine the characteristics of journeys that result in an overnight stay, and are thus relevant for malaria transmission. Defining the home location of each person as the place of most frequent calls, it is found that approximately 60% of people who spend nights away from home have regular destinations that are repeatedly visited, although only 10% have 3 or more regular destinations. The number of journeys involving overnight stays peaks at a distance of 50 km, although roughly half of such journeys exceed 100 km. Most visits only involve a stay of one or two nights away from home, with just 4% exceeding one week. A new agent-based migration model is introduced, based on a gravity model adapted to represent overnight journeys. Each agent makes journeys involving overnight stays to either regular or random locations, with journey and destination probabilities taken from the mobile phone dataset. Preliminary simulations show that the agentbased model can approximately reproduce the patterns of migration involving overnight stays.

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