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来源类型 | Report |
规范类型 | 报告 |
DOI | https://doi.org/10.7249/RRA365-1 |
来源ID | RR-A365-1 |
Data Privacy During Pandemics: A Scorecard Approach for Evaluating the Privacy Implications of COVID-19 Mobile Phone Surveillance Programs | |
Benjamin Boudreaux; Matthew A. DeNardo; Sarah W. Denton; Ricardo Sanchez; Katie Feistel; Hardika Dayalani | |
发表日期 | 2020-07-30 |
出版年 | 2020 |
语种 | 英语 |
结论 |
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摘要 | Public health officials around the world are struggling to respond to the coronavirus disease 2019 (COVID-19) pandemic. To contain the highly infectious disease, governments have turned to mobile phone surveillance programs to augment traditional public health interventions. These programs have been designed to track COVID-19 symptoms, map population movement, trace the contacts of infected persons, enforce quarantine orders, and authorize movement through health passes. Although these programs enable more-robust public health interventions, they also raise concerns that the privacy and civil liberties of users will be violated. ,In this report, the authors evaluate the short- and long-term privacy harms associated with the use of these programs—including political, economic, and social harms. They consider whether two potentially competing goals can be achieved concurrently: (1) the use of mobile phones as public health surveillance tools to help manage COVID 19 and future public health crises, and (2) the protection of privacy and civil liberties. ,To evaluate the privacy implications of COVID-19 mobile surveillance programs, the authors create a concise, transparent, and standardized privacy scorecard. They use this scorecard approach to evaluate 40 mobile phone surveillance programs from around the world. The results indicate that the privacy implications vary considerably across programs, even within programs designed to accomplish similar public health goals. The authors offer recommendations to U.S. federal, state, and local officials to implement COVID-19 surveillance programs that better protect privacy, especially that of vulnerable and marginalized communities. |
目录 |
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主题 | Biosurveillance ; Coronavirus Disease 2019 (COVID-19) ; Data Analysis ; Health Information Privacy ; Health Information Technology |
URL | https://www.rand.org/pubs/research_reports/RRA365-1.html |
来源智库 | RAND Corporation (United States) |
引用统计 | |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/524168 |
推荐引用方式 GB/T 7714 | Benjamin Boudreaux,Matthew A. DeNardo,Sarah W. Denton,et al. Data Privacy During Pandemics: A Scorecard Approach for Evaluating the Privacy Implications of COVID-19 Mobile Phone Surveillance Programs. 2020. |
条目包含的文件 | ||||||
文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
RAND_RRA365-1.pdf(2446KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
1603819512586.jpg(6KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | ![]() 浏览 |
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