Quantifying the differences in call detail records.
Ontology highlight
ABSTRACT:
SUBMITTER: Botta F
PROVIDER: S-EPMC8242929 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCall detail records (CDRs) are collected by mobile network operators in the course of providing their service. CDRs are increasingly being used in research along with other forms of big data and represent an emerging data type with potential for public good. Many jurisdictions have infrastructures for health data research that could benefit from the integration of CDRs with health data.ObjectiveThe objective of this study was to review how CDRs have been used in health research and to identify challenges and potential opportunities for their wider use in conjunction with health data.MethodsA literature review was conducted using structured search terms making use of major search engines. Initially, 4066 items were identified. Following screening, 46 full text articles were included in the qualitative synthesis. Information extracted included research topic area, population of study, datasets used, information governance and ethical considerations, study findings, and data limitations.ResultsThe majority of published studies were focused on low-income and middle-income countries. Making use of the location element in CDRs, studies often modeled the transmission of infectious diseases or estimated population movement following natural disasters with a view to implementing interventions. CDRs were used in anonymized or aggregated form, and the process of gaining regulatory approvals varied with data provider and by jurisdiction. None included public views on the use of CDRs in health research.ConclusionsDespite various challenges and limitations, anonymized mobile phone CDRs have been used successfully in health research. The use of aggregated data is a safeguard but also a further limitation. Greater opportunities could be gained if validated anonymized CDRs were integrated with routine health records at an individual level, provided that permissions and safeguards could be put in place. Further work is needed, including gaining public views, to develop an ethically founded framework for the use of CDRs in health research.
| S-EPMC6072975 | biostudies-literature
Project description:BackgroundMobile phone call detail records (CDRs) are increasingly being used in health research. The location element in CDRs is used in various health geographic studies, for example, to track population movement and infectious disease transmission. Vast volumes of CDRs are held by multinational organizations, which may make them available for research under various data governance regimes. However, there is an identified lack of public engagement on using CDRs for health research to contribute to an ethically founded framework.ObjectiveThis study aimed to explore public views on the use of call detail records in health research.MethodsViews on using CDRs in health research were gained via a series of three public workshops (N=61) informed by a pilot workshop of 25 people. The workshops included an initial questionnaire to gauge participants' prior views, discussion on health research using CDRs, and a final questionnaire to record workshop outcome views. The resulting data were analyzed for frequencies and emerging themes.ResultsAt the outset, most participants (66%, 40/61) knew that location data were collected by operators, but only 3% (2/61) knew they were being used for health research. Initially, the majority of the participants (62%, 38/61) was content for their anonymous CDRs to be used, and this increased (80%, 49/61) after the discussion explained that safeguards were in place. Participants highlighted that terms and conditions should be clearer, as should information to phone users on data collection, privacy safeguards, sharing, and uses in research.ConclusionsThis is the first known study exploring public views of using mobile phone CDRs in health research. It revealed a lack of knowledge among the public on uses of CDRs and indicated that people are generally amenable to the use of anonymized data for research, but they want to be properly informed and safeguarded. We recommend that public views be incorporated into an ethically founded framework for the use of CDRs in health research to promote awareness and social acceptability in data use.
| S-EPMC6352010 | biostudies-literature
Project description:Data derived from the plethora of networked digital devices hold great potential for public benefit. Among these, mobile phone call detail records (CDRs) present novel opportunities for research and are being used in a variety of health geography studies. Research suggests that the public is amenable to the use of anonymized CDRs for research; however, further work is needed to show that such data can be used appropriately. This study works toward an ethically founded data governance framework with social acceptability. Using a multifaceted approach, this study draws upon data governance arrangements in published health research using CDRs, with a consideration of public views and the public's information expectations from mobile network operators, and data use scenarios of CDRs in health research. The findings were considered against a backdrop of legislative and regulatory requirements. CDRs can be used at various levels of data and geographic granularity and may be integrated with additional, publicly available or restricted datasets. As such, there may be a significant risk of identity disclosure, which must be mitigated with proportionate control measures. An indicative relative risk of the disclosure model is proposed to aid this process. Subsequently, a set of recommendations is presented, including the need for greater transparency, accountability, and incorporation of public views for social acceptability. This study addresses the need for greater clarity and consistency in data governance for CDRs in health research. While recognizing the need to protect commercial interests, we propose that these recommendations be used to contribute toward an ethically founded practical framework to promote the safe, socially acceptable use of CDR data for public benefit. This pattern needs to be repeated for the appropriate use of new and emerging data types from other networking devices and the wider internet of things.
| S-EPMC6450474 | biostudies-literature
Project description:Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell phone data to shed light on urban migration patterns and deprivation in Tanzania. Call detail records were used to identify individuals who migrated to Dar es Salaam, Tanzania's largest city. A street survey of the city's subwards was used to determine which individuals moved to more deprived areas. t-tests showed that people who settled in poorer neighbourhoods had less money coming into their mobile money account after they moved, but not before. A machine learning approach was then utilized to predict which migrants will move to poorer areas of the city, making them arguably more vulnerable to poverty, unemployment and exploitation. Features indicating the strength and location of people's social connections in Dar es Salaam before they moved ('pull factors') were found to be most predictive, more so than traditional 'push factors' such as proxies for poverty in the migrant's source region.Supplementary informationThe online version contains supplementary material available at 10.1140/epjds/s13688-022-00340-y.
| S-EPMC9079216 | biostudies-literature
Project description:Excessive land use and suburbanisation around densely populated urban areas has gone hand in hand with a growth in overall transportation and discussions about causality of traffic congestions. The objective of this paper is to gain new insight regarding the composition of traffic flows, and to reveal how and to what extent suburbanites' travelling affects rush hour traffic. We put forward an alternative methodological approach using call detail records of mobile phones to assess the composition of traffic flows during the evening rush hour in Tallinn, Estonia. We found that daily commuting and suburbanites influence transportation demand by amplifying the evening rush hour traffic, although daily commuting trips comprises only 31% of all movement at that time. The geography of the Friday evening rush hour is distinctive from other working days, presumably in connection with domestic tourism and leisure time activities. This suggests that the rise of the overall mobility of individuals due to societal changes may play a greater role in evening rush hour traffic conditions than does the impact of suburbanisation.
| S-EPMC3498329 | biostudies-literature
Project description:Human mobility patterns created from mobile phone call detail records (CDRs) can provide
| S-EPMC10247678 | biostudies-literature
Project description:BackgroundThe exponential scale and pace of real-time data generated from mobile phones present opportunities for new insights and challenges across multiple sectors, including health care delivery and public health research. However, little attention has been given to the new ethical, social, and legal concerns related to using these mobile technologies and the data they generate in Africa.ObjectiveThe objective of this scoping review was to explore the ethical and related concerns that arise from the use of data from call detail records and mobile technology interventions for public health in the context of East Africa.MethodsWe searched the PubMed database for published studies describing ethical challenges while using mobile technologies and related 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 screened studies using prespecified eligibility criteria through a two-stage process by two independent reviewers. Studies were included if they were (1) related to mobile technology use and health, (2) published in English from 2000 to 2020, (3) available in full text, and (4) conducted in the East African region. We excluded articles that (1) were conference proceedings, (2) studies presenting an abstract only, (3) systematic and literature reviews, (4) research protocols, and (5) reports of mobile technology in animal subjects. We followed the five stages of a published framework for scoping reviews recommended by Arksey and O'Malley. Data extracted included title, publication year, target population, geographic region, setting, and relevance to mobile health (mHealth) and ethics. Additionally, we used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Extension for Scoping Reviews checklist to guide the presentation of this scoping review. The rationale for focusing on the five countries in East Africa was their geographic proximity, which lends itself to similarities in technology infrastructure development.ResultsOf the 94 studies identified from PubMed, 33 met the review inclusion criteria for the final scoping review. The 33 articles retained in the final scoping review represent studies conducted in three out of five East African countries: 14 (42%) from Uganda, 13 (39%) from Kenya, and 5 (16%) from Tanzania. Three main categories of concerns related to the use of mHealth technologies and mobile phone data can be conceptualized as (1) ethical issues (adequate informed consent, privacy and confidentiality, data security and protection), (2) sociocultural issues, and (3) regulatory/legal issues.ConclusionsThis scoping review identified major cross-cutting ethical, regulatory, and sociocultural concerns related to using data from mobile technologies in the East African region. A comprehensive framework that accounts for the critical concerns raised would be valuable for guiding the safe use of mobile technology data for public health research purposes.
| S-EPMC9204580 | biostudies-literature
Project description:Methods are needed to estimate the probability that a population is extinct, whether to underpin decisions regarding the continuation of a invasive species eradication program, or to decide whether further searches for a rare and endangered species could be warranted. Current models for inferring extinction probability based on sighting data typically assume a constant or declining sighting rate. We develop methods to analyse these models in a Bayesian framework to estimate detection and survival probabilities of a population conditional on sighting data. We note, however, that the assumption of a constant or declining sighting rate may be hard to justify, especially for incursions of invasive species with potentially positive population growth rates. We therefore explored introducing additional process complexity via density-dependent survival and detection probabilities, with population density no longer constrained to be constant or decreasing. These models were applied to sparse carcass discoveries associated with the recent incursion of the European red fox (Vulpes vulpes) into Tasmania, Australia. While a simple model provided apparently precise estimates of parameters and extinction probability, estimates arising from the more complex model were much more uncertain, with the sparse data unable to clearly resolve the underlying population processes. The outcome of this analysis was a much higher possibility of population persistence. We conclude that if it is safe to assume detection and survival parameters are constant, then existing models can be readily applied to sighting data to estimate extinction probability. If not, methods reliant on these simple assumptions are likely overstating their accuracy, and their use to underpin decision-making potentially fraught. Instead, researchers will need to more carefully specify priors about possible population processes.
| S-EPMC4005750 | biostudies-literature
Project description:Common ALL (cALL) is the most frequent entity of childhood ALL and carries an early pre-B cell phenotype. Expression patterns of 25 pediatric cALL samples were analyzed by use of high-density DNA microarrays HG-U133A. Leukemic patients’ bone marrow samples were compared to sorted B cells from cord blood of healthy donors expressing CD19 and CD10 surface antigens. Differential gene expression profiling of pediatric cALL versus non-malignant tissues enabled the identification of aberrantly expressed genes in malignant cells, facilitating discrimination of leukemic from normal cells and possibly revealing specific disease mechanisms. Principal component analysis clearly distinguished leukemia samples from normal controls. Significance analysis of microarrays revealed 487 genes significantly up-regulated, and 572 down-regulated genes in leukemic cells. A comparison to previous publications investigating genetically defined subsets of cALL revealed 465 genes previously not associated with cALL. Interestingly, terminal deoxynucleotidyl-transferase (DNTT) as well as in the context of cALL unknown genes, were found to be the strongest predictive genes for the malignant phenotype signifying the diagnostic value of our approach.
2012-06-30 | GSE34670 | GEO
Project description:The ability to generate episodic details while recollecting autobiographical events is believed to depend on a collection of brain regions that form a posterior medial network (PMN). How age-related differences in episodic detail generation relate to the PMN, however, remains unclear. The present study sought to examine individual differences, and the role of age, in PMN resting state functional connectivity (rsFC) associations with episodic detail generation. Late middle-aged and older adults (N = 41, ages 52-81), and young adults (N = 21, ages 19-35) were asked to describe recent personal events, and these memory narratives were coded for episodic, semantic and 'miscellaneous' details. Independent components analysis and regions-of-interest analyses were used to assess rsFC within the PMN separately for anterior connections (hippocampal and medial prefrontal) and posterior connections (hippocampal, parahippocampal and parieto-occipital), as these connections purportedly serve different functional roles in episodic detail generation. Compared to younger adults, older adults produced memory narratives with lower episodic specificity (ratio of episodic:total details) and a greater amount of semantic detail. Among the older adults, episodic detail amounts and episodic specificity were reduced with increasing age. There were no significant age differences in PMN rsFC. Stronger anterior PMN rsFC was related to lower episodic detail in the older adult group, but not in the young. Among the older adults, increasing age brought on an association between increased anterior PMN rsFC and reduced episodic specificity. In contrast, increasing age brought on an association between increased posterior PMN rsFC and increased semantic detail. The present study provides evidence that functional connectivity within the PMN, particularly anterior PMN, tracks individual differences in the amount of episodic details retrieved by older adults. Furthermore, these brain-behavior relationships appear to be age-specific, indicating that some process within aging alters the nature of how anterior PMN rsFC and episodic detail relate to each other. Whether this process entails an age-related loss of integrity to the PMN, or an age-related shift toward semantic retrieval, remains to be determined.
| S-EPMC8816892 | biostudies-literature