Reconciling public health common good and individual privacy: new methods and issues in geoprivacy

Abstract

This article provides a state-of-the-art summary of location privacy issues and geoprivacy-preserving methods in public health interventions and health research involving disaggregate geographic data about individuals. Synthetic data generation (from real data using machine learning) is discussed in detail as a promising privacy-preserving approach. To fully achieve their goals, privacy-preserving methods should form part of a wider comprehensive socio-technical framework for the appropriate disclosure, use and dissemination of data containing personal identifiable information. Select highlights are also presented from a related December 2021 AAG (American Association of Geographers) webinar that explored ethical and other issues surrounding the use of geospatial data to address public health issues during challenging crises, such as the COVID-19 pandemic.

Moving beyond anonymity: Embracing a collective approach to location privacy in data-intensive geospatial analytics

“…The literature on location privacy is expanding to address the impacts caused by the emergence of geospatial data and technologies (Armstrong and Ruggles, 2005; Banerjee, 2019; Clarke and Wigan, 2011; Curry, 1997a; De Montjoye et al, 2013; Dobson, 2009; Swanlund and Schuurman, 2016; Taylor, 2016). Considerable efforts have been made to explore the conceptualization of location privacy (Armstrong et al, 2017; Duckham and Kulik, 2006; Keßler and McKenzie, 2018; Kwan et al, 2004), identify instances where location privacy can be compromised (McKenzie et al, 2016; Wernke et al, 2014), and develop methods to counter surveillance and privacy violations that specifically target or involve geographic locations (Jiang et al, 2021; Kamel Boulos et al, 2022; Lin and Xiao, 2023a; Swanlund and Schuurman, 2019). However, a major problem with the existing literature is its limit to an individualistic approach to privacy that emphasizes individuals’ control over access to their location information that can be used to identify them.…”

Geoprivacy in Neighbourhoods and Health Research: A Mini-Review of the Challenges and Best Practices in Epidemiological Studies

“…While in the past the collection of geographical data in epidemiological research was mostly completed using questionnaires, today, with GIS and, particularly, with the growing amount of sensor-based data, there is no ceiling for the amount of geographical data that can be collected. Consequently, the privacy and confidentiality of geographic data (geoprivacy) in health research became an important emerging topic ( 5 ). Geoprivacy refers to the “individual rights to prevent disclosure of the location of one’s home, workplace, daily activities, or trips” ( 6 ).…”