Dataset Information

Yahtzee: an anonymized group level matching procedure.

ABSTRACT: Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific individual behaviors. In this paper we present a procedure to keep information about specific individuals from being "leaked" or shared in either direction between two sources of data without need of a trusted third party. To achieve this goal, we randomly assign individuals to anonymous groups before combining the anonymized information between the two sources of data. We refer to this method as the Yahtzee procedure, and show that it performs as predicted by theoretical analysis when we apply it to data from Facebook and public voter records.

SUBMITTER: Jones JJ

PROVIDER: S-EPMC3564933 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Yahtzee: an anonymized group level matching procedure.

Jones Jason J JJ Bond Robert M RM Fariss Christopher J CJ Settle Jaime E JE Kramer Adam D I AD Marlow Cameron C Fowler James H JH

PloS one 20130205 2

Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of computational social science and the enormous amount of data about people that is being collected makes protecting the privacy of research subjects ever more important. However, strict privacy procedures can hinder the process of joining diverse sources of data that contain information about specific indi ...[more]

PMID: 23441156

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Project description:BackgroundObesity is a serious public health problem. Existing research has shown a strong association between obesity and an individual's diet and physical activity. If we extend such an association to the neighborhood level, information about the diet and physical activity of the residents of a neighborhood may improve the estimate of neighborhood-level obesity prevalence and help identify the neighborhoods that are more likely to suffer from obesity. However, it is challenging to measure neighborhood-level diet and physical activity through surveys and interviews, especially for a large geographic area.MethodsWe propose a method for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data, and examine the extent to which the derived measurements can enhance obesity estimation, in addition to the socioeconomic and demographic variables typically used in the literature. We conduct case studies in three different U.S. cities, which are New York City, Los Angeles, and Buffalo, using anonymized mobile phone location data from the company SafeGraph. We employ five different statistical and machine learning models to test the potential enhancement brought by the derived measurements for obesity estimation.ResultsWe find that it is feasible to derive neighborhood-level diet and physical activity measurements from anonymized mobile phone location data. The derived measurements provide only a small enhancement for obesity estimation, compared with using a comprehensive set of socioeconomic and demographic variables. However, using these derived measurements alone can achieve a moderate accuracy for obesity estimation, and they may provide a stronger enhancement when comprehensive socioeconomic and demographic data are not available (e.g., in some developing countries). From a methodological perspective, spatially explicit models overall perform better than non-spatial models for neighborhood-level obesity estimation.ConclusionsOur proposed method can be used for deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone data. The derived measurements can enhance obesity estimation, and can be especially useful when comprehensive socioeconomic and demographic data are not available. In addition, these derived measurements can be used to study obesity-related health behaviors, such as visit frequency of neighborhood residents to fast-food restaurants, and to identify primary places contributing to obesity-related issues.

Project description:BackgroundCurrent isolation techniques for spotted fever group Rickettsia from clinical samples are laborious and are limited to tissue, blood and blood derivatives with volumes ideally greater than 1 mL. We validated the use of simplified methodologies for spotted fever group Rickettsia culture isolation that overcome sample volume limitations and provide utility in clinical diagnostics and research studies.Methodology/principal findingsA modified cell culture method is evaluated for the isolation of Rickettsia ssp. from human diagnostic samples. Culture sampling method, culture platform, and growth phase analysis were evaluated to determine best practices for optimal culture isolation conditions. Rickettsial isolates (R. conorii, R. rickettsii, and R. parkeri) were grown in Vero E6 cells over a course of 5 to 7 days at low inoculum treatments (~40 bacterial copies) to standardize the sampling strategy at a copy number reflective of the bacteremia in acute diagnostic samples. This methodology was verified using small volumes (50 μL) of 25 unprocessed clinical whole blood, plasma, and serum samples from acute samples of patients suspected of having Rocky Mountain Spotted Fever, of which 10 were previously confirmed positive via the PanR8 qPCR assay, 13 had no detectable Rickettsia DNA by the PanR8 qPCR assay, and 2 were not previously tested; these samples resulted in the cultivation of 7 new R. rickettsii isolates.Conclusions/significanceWe observed that rickettsial isolate growth in culture is reproducibly identified by real-time PCR testing of culture media within 72 hours after inoculation. Additionally, specimen sedimentation prior to isolation to remove red blood cells was found to decrease the amount of total organism available in the inoculum. A small volume culture method was established focusing on comparative qPCR detection rather than bacterial visualization, taking significantly shorter time to detect, and requiring less manipulation compared to traditional clinical isolate culture methods.

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Yahtzee: an anonymized group level matching procedure.

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Yahtzee: an anonymized group level matching procedure.

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