COVID-19’s Impact on Visitation Behavior to US National Parks From Communities of Color - Evidence From Mobile Phone Data

The widespread COVID-19 pandemic fundamentally changed many people’s ways of life. With the necessity of social distancing and lock downs across the United States, evidence shows more people engage in outdoor activities. With the utilization of location-based service (LBS) data, we seek to explore how visitation patterns to national parks changed among communities of color during the COVID-19 pandemic. Our results show that visitation rates to national parks located closer than 347km to individuals have increased amidst the pandemic, but the converse was demonstrated amongst parks located further than 347km from individuals. More importantly, COVID-19 has adversely impacted visitation figures amongst non-white and Native American communities, with visitation volumes declining if these communities are situated further from national parks. Our results show disproportionately low-representations amongst national park visitors from these communities of color. African American communities display a particularly concerning trend whereby their visitation to national parks is substantially lower amongst communities closer to national parks.

Profiling Residents’ Mobility with Grid-Aggregated Mobile Phone Trace Data Using Chengdu as the Case

People’s movement trace harvested from mobile phone signals has become an important new data source for studying human behavior and related socioeconomic topics in social science. With growing concern about privacy leakage of big data, mobile phone data holders now tend to provide aggregate-level mobility data instead of individual-level data. However, most algorithms for measuring mobility are based on individual-level data—how the existing mobility algorithms can be properly transformed to apply on aggregate-level data remains undiscussed. This paper explores the transformation of individual data-based mobility metrics to fit with grid-aggregate data. Fifteen candidate metrics measuring five indicators of mobility are proposed and the most suitable one for each indicator is selected. Future research about aggregate-level mobility data may refer to our analysis to assist in the selection of suitable mobility metrics.

News or social media? Socio-economic divide of mobile service consumption

Reliable and timely information on socio-economic status and divides is critical to social and economic research and policing. Novel data sources from mobile communication platforms have enabled new cost-effective approaches and models to investigate social disparity, but their lack of interpretability, accuracy or scale has limited their relevance to date. We investigate the divide in digital mobile service usage with a large dataset of 3.7 billion time-stamped and geo-referenced mobile traffic records in a major European country, and find profound geographical unevenness in mobile service usage—especially on news, e-mail, social media consumption and audio/video streaming. We relate such diversity with income, educational attainment and inequality, and reveal how low-income or low-education areas are more likely to engage in video streaming or social media and less in news consumption, information searching, e-mail or audio streaming. The digital usage gap is so large that we can accurately infer the socio-economic status of a small area or even its Gini coefficient only from aggregated data traffic. Our results make the case for an inexpensive, privacy-preserving, real-time and scalable way to understand the digital usage divide and, in turn, poverty, unemployment or economic growth in our societies through mobile phone data.

Using POI Data to Identify the Demand for Pedestrian Crossing Facilities at Mid-Block

In Chinese cities, the widespread problem of the low density of the road network has seriously damaged the convenience of pedestrian crossing, resulting in an unfriendly pedestrian experience and restricted development of non-motorized traffic within the city. Only by accurately capturing the crossing needs of pedestrians can we adopt a targeted approach to improve the pedestrian crossing experience. In this paper, the demand and supply are considered synthetically, and a method of using point of interest (POI) data to analyze the demand for pedestrian crossing facilities at the mid-block is proposed. First, we developed the method of calculating the pedestrian crossing demand intensity based on POI data. Secondly, based on the appropriate length threshold and pedestrian crossing demand intensity threshold, a series of road sections with strong demand for pedestrian crossing facilities are identified in the study area. Finally, we use mobile phone data to obtain the intensity of residents’ activity in different areas, and find that the distribution of the areas with more activity is basically the same as that of the target road sections. The result shows that the method proposed in this paper can effectively identify the road sections with strong demand for crossing facilities at mid-block, and can provide support for the improvement of urban non-motorized traffic.

COVID-19 Flow-Maps an open geographic information system on COVID-19 and human mobility for Spain

COVID-19 is an infectious disease caused by the SARS-CoV-2 virus, which has spread all over the world leading to a global pandemic. The fast progression of COVID-19 has been mainly related to the high contagion rate of the virus and the worldwide mobility of humans. In the absence of pharmacological therapies, governments from different countries have introduced several non-pharmaceutical interventions to reduce human mobility and social contact. Several studies based on Anonymized Mobile Phone Data have been published analysing the relationship between human mobility and the spread of coronavirus. However, to our knowledge, none of these data-sets integrates cross-referenced geo-localised data on human mobility and COVID-19 cases into one all-inclusive open resource. Herein we present COVID-19 Flow-Maps, a cross-referenced Geographic Information System that integrates regularly updated time-series accounting for population mobility and daily reports of COVID-19 cases in Spain at different scales of time spatial resolution. This integrated and up-to-date data-set can be used to analyse the human dynamics to guide and support the design of more effective non-pharmaceutical interventions.

Ethical, legal and social issues in the use of mobile technologies and archived cellphone data in the East African region: A Scoping Review (Preprint)

BACKGROUND Mobile phone adoption and the implementation of mobile health (mHealth) interventions to overcome health system challenges is on the rise in Africa and elsewhere in the world. Data derived from mobile phones hold great promise for transforming healthcare delivery and public health research. To date, little is known about the ethical, legal and social concerns related to the use of these data in Africa. OBJECTIVE We conducted a scoping review to explore the existing literature in order to understand the current ethical issues that arise when using mobile technology interventions and call detail records for public health research in the context of East Africa. METHODS We searched PubMed database for published studies describing ethical challenges while using mobile technologies and data in public health research between 2000 and 2020. A predefined search strategy was used as inclusion criteria with search terms such as “East Africa”, “mHealth”, “mobile phone data”, “public health”, “ethics”, or “privacy”. We followed five stages of a published framework for scoping reviews by Arksey and O’Malley. These stages include: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; and (5) collating, summarizing, and reporting the results. Studies were screened using pre-specified eligibility criteria through a two-stage process by two independent reviewers. Data extracted included title, publication year, target population, geographic region, setting, and relevance to mHealth and ethics. RESULTS Of the 94 studies identified from PubMed, 33 met the review inclusion criteria for the final scoping review. The included studies were conducted in three out of five countries in the East African Community. Five themes emerged as major concerns for using mHealth interventions and mobile phone data: privacy and confidentiality, data security and protection concerns, sociocultural issues, regulatory and legal and, adequate informed consent process. CONCLUSIONS This scoping review identified major crosscutting concerns related to use of mobile technologies and mobile phone data common to the East African region. A comprehensive framework that accounts for ethical, sociocultural, legal and regulatory concerns and, adequate consent process is needed to guide the safe use of mobile technology data for public health research purposes.

Do Migrant and Native Robbers Target Different Places?

The spatial pattern of crime has been a central theme of criminological research. Recently, the spatial variation in the crime location choice of offenders by different population groups has been gaining more attention. This study addresses the issue of whether the spatial distribution of migrant robbers’ crime location choices is different from those of native robbers. Further, what factors contribute to such differences? Using a kernel density estimation and the discrete spatial choice modeling, we combine the offender data, POI data, and mobile phone data to explain the crime location choice of the street robbers who committed offenses and were arrested from 2012 to 2016 in ZG City, China. The results demonstrate that the crime location choices between migrant robbers and native robbers have obvious spatial differences. Migrant robbers tend to choose the labor-intensive industrial cluster, while native robbers prefer the old urban areas and urban villages. Wholesale markets, sports stadiums, transportation hubs, and subway stations only affect migrant robbers’ crime location choices, but not native robbers’. These results may be attributable to the different spatial awareness between migrant robbers and native robbers. The implications of the findings for criminological theory and crime prevention are discussed.