Geomasking is a set of techniques that introduces noise or intentional errors into geospatial data to minimize the risk of identifying exact location information related to individuals while preserving the utility of the data to a controlled extent. It protects the geoprivacy of the data contributor and mitigates potential harm from data breaches while promoting safer data sharing. The development of digital health technologies and the extensive use of individual geospatial data in health studies have raised concerns about geoprivacy. The individual tracking data and health information, if accessed by unauthorized parties, may lead to privacy invasions, criminal activities, and discrimination. These risks underscore the importance of robust protective measures in the collection, management, and sharing of sensitive data. Geomasking techniques have been developed to safeguard geoprivacy in geospatial health data, addressing the risks and challenges associated with data sharing. This entry paper discusses the importance of geoprivacy in geospatial health data and introduces various kinds of geomasking methods and their applications in balancing the protection of individual privacy with the need for data sharing to ensure scientific reproducibility, highlighting the urgent need for more effective geomasking techniques and their applications.
The advance of geospatial data collection techniques and analytics methods led to the collection of high-resolution individual geospatial data for public health studies. From the detailed datasets of subjects’ residential locations and health information to the GPS tracking and wearable environmental sensors that record their daily movements and real-time environment exposures, geospatial health data contain a vast volume of details. Analyzing those individual-level geospatial data helps in understanding the nuanced relationship between environmental exposure and health outcomes. Further integrating with high-resolution geospatial context data (e.g., fine-scale census data, geographic information data, and remote sensing data) promotes exciting new research findings in health geography studies.
As geospatial data analytics grew in popularity in health studies, so did the risks of privacy breaches through decoding individual-level data or map products. It poses privacy concerns, especially when sensitive health information is involved, such as a person’s medical conditions, prescriptions, or genetic information. If the high-resolution individual geospatial data were overlayed with geographic context information via geospatial intelligence, the dataset contributors’ individual privacy was also at high risk
[1][2][1,2]. Detailed geospatial information can expose the dataset contributors’ important activity locations, including home, workplace, school, family, or friends’ locations. Further details can also be derived from the GPS tracking data, which could breach the subjects’ daily movement patterns, like where and when the subjects were staying at home or going to work.
The potential exposure of subjects’ location information raises the concern of geoprivacy in geospatial health data. Geoprivacy refers to the confidentiality of dataset contributors’ personal information of activity locations, movement patterns, and any geospatial information that may expose their location privacy. The geoprivacy concern is especially important in geospatial health data, where subjects’ health information can be easily related to their locations and re-identified
[3].
Concerns about geoprivacy mean that geospatial health data collected in one study cannot be easily shared. This limits the reusability of the scientific data and results in a significant waste of resources due to repetitive data collection
[4]. Furthermore, this impediment to data sharing undermines reproducibility, which is one of the cornerstones of the scientific paradigm
[2][5][2,5]. In the field of public health and health geography, geospatial health data are regulated by government policies, such as the Health Insurance Portability and Accountability Act
[6] in the United States, the General Data Protection Regulation in the European Union
[7], and the Personal Information Protection and Electronic Documents Act
[8] in Canada. The sharing or publishing of geospatial health data is not allowed if it does not meet the geoprivacy standard
[9][10][9,10]. In this context, sharing sensitive geospatial health data and promoting reproducibility of research findings in health geography studies are constrained by the efforts to protect geoprivacy. Scholars in the field are looking for solutions to balance the accessibility and the confidentiality of geospatial health data.
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