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Genetic Privacy and Identity in Community Settings - GetPreCiSe

社区环境中的遗传隐私和身份 - GetPreCiSe

基本信息

批准号：
9274368
负责人：
ELLEN WRIGHT CLAYTON
金额：
$ 100.57万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-05-16 至 2020-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9274368
关键词：
Address Affect Attention Attitude Automobile Driving Belief Benefits and Risks Calculi Communities Data Data Set Development Disease Ensure Ethics Family Fright Fruit Future Genetic Identity Genetic Privacy Genomics Health Individual Institution Institutional Review Boards Insurance Intervention Knowledge Laws Legal Life Life Experience Love Measures Methods Modeling Occupations Outcome Paper Persons Pharmacogenomics Phenotype Policies Policy Making Precision Medicine Initiative Prevention Privacy Probability Process Public Policy Publishing Recording of previous events Research Risk Role Secure Security Shapes Source Surface Theft Translations Trust Withdrawal Work Writing base cancer diagnosis cancer therapy clinical care clinical translation community setting cost data sharing demographics evidence base genetic variant genomic data genomic variation improved interdisciplinary approach material transfer agreement next generation phenomics programs public health relevance social success

项目摘要

DESCRIPTION (provided by applicant): Concerns about privacy and personal identity impede use of data about genomic variation, phenotypes, demographics, and exposures from large numbers of people to uncover the contributions of such information on health and disease, knowledge that can improve clinical care. People worry that these data and genomic data in particular, cannot be secured. Many fear that data about them will be used in ways they oppose (e.g., to deny them and those they love access to jobs and insurance) because existing legal rules about such uses are not comprehensive. Additionally, others worry that genomic data will undermine their self-understanding, for example, by identifying misattributed parentage or challenging beliefs about ancestral history. To evaluate and address concerns about privacy and identity, more research needs to be done to identify the risks - both real and perceived - and the benefits of data gathering in order more effectively to inform the public and policy. The driving hypothesis of the Genetic Privacy and Identity in Community Settings - GetPreCiSe Center, is that the debate about genetic privacy and identity to date has been based (a) on an incomplete understanding of the influences on the actors involved in genomics research and translation and (b) on possible, rather than probable, risks. Thus, too much of the research has focused on what individuals say, effectively minimizing the role of community and social influences in shaping attitudes toward privacy. Evidence already suggests that the likelihood that a person will be re-identified or harmed in some manner is quite low. Thus, current policies can both over- and under-protect people and data, depending on the context. This project will convene a diverse group of scholars with broadly interdisciplinary perspectives and community advisors to work together to develop a more comprehensive understanding of these worries and the factors that influence them, to model actual risks to privacy and identity, all of which will b used to inform policy. GetPreCiSe is guided by four interacting specific aims: 1. To enhance our understanding of the impact of threats to privacy and identity in genomic data. Concerns about privacy and identity involve the 1) Individual, who has been the focus of most policy debate, as well as 2) Families, 3) Communities, and 4) various Social institutions, each facing its own distinctive calculus of risk and benefit. All of these are subject to an array of influences. 2. To measure the efficacy of efforts to protect privacy and identity by 1) Communities, 2) IRBs, 3) Institutions that collect, hold, and share genomic and phenomic data, and 4) Law, using quantitative, analytic, and legal analyses. 3. To develop models to quantify the probability of genomic data re-identification and harm that take into account the set of influencing factors and efforts to protect data, as well as the costs that attacker(s) would incur to mount the attack and the potential benefits and penalties that the attacker(s) might receive with a successful attack. 4 To address concerns by developing interventions that provide certainty and enhance institutional trust, as well as policy solutions that could deter intrusions of privacy and misuse.