The tension between privacy concerns and study of the geography infectious diseases
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Dr. Mei-Po Kwan gave a talk for the American Geographical Society’s Location Tech Task Force where she discusses the tension between disease mitigation and privacy concerns . Nowadays, a big portion of the population carries mobile devices with integrated Global Positioning Systems. Therefore, from a public health point of view, it would be ideal if health authorities could identify people infected with an infectious disease, such as COVID-19, to reduce the spread of the disease. However, this would entail the use and possession of very private data that in a short amount of time could be used to reverse geocode the places where a person lives, works, recreates, etc.
I found the idea of geo-narratives particularly interesting and useful in highlighting the experience of vulnerable people without having to compromise the privacy of any individual. As Dr. Kwan mentions, geo-narratives can be use to shed light on and preserve the experiences of ordinary people with the place and their interaction. They can be used to complement the power of GIS with more qualitative information. Nonetheless, researchers and the people who generate and have access to the raw-data of geo-narratives must be particularly careful in generalizing the qualitative information, and introducing error in the geographical information to ensure the location privacy (see Kerski 2016) of the subjects of study. This is extremely important, not only because everyone has a right to location privacy, but also because releasing such detailed information about a vulnerable population may increase their vulnerability. as Poothuis (2018) explains, often in the visualization and use of geographical Big Data, the information may come down to the individual level. In contrast, small data usually is aggregated into different geographical units reducing the possibility of reverse geocoding to happen.
In terms of reproducibility, introducing error to protect the privacy of subject may generate complication from reproduction. In these kinds of research, it would be essential that researchers outline how exactly they generalized the data. Nonetheless, this generalization or introduction of error should not be reversible; that would defeat the whole purpose of introducing the error.
Related resources
Kwan, Mei-Po. 2020. Location Tech Task Force, Leadership Spotlight, Tracking Movement through Space during COVID-19. American Geographical Society.
Kerski, J. (2016). Location Privacy. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2016 Edition), John P. Wilson (ed.). DOI: 10.22224/gistbok/2016.3.2
Poorthuis, A. (2018). Big Data Visualization. The Geographic Information Science & Technology Body of Knowledge (3rd Quarter 2018 Edition), John P. Wilson (Ed.). DOI: 10.22224/gistbok/2018.3.5