EURA Conversations Post #12 – 2 Nov 2020
by Inigo Lorente Riverola, Universidad Politécnica de Madrid,
More than a century and a half ago, Doctor John Snow uncovered the linkage between cholera and the urban infrastructure by tracking and mapping infections and deaths in London’s Soho, which constituted a milestone of what we call GIS (Geographic Information Systems) today.
Nowadays, it is indisputable that Covid-19 is the most mapped disease in history by public administrations, data journalists, and scholars attempting to depict its urban geography. Snow’s map proved that far from being airborne, cholera was related to unsafe water sources that needed to be re-planned, whereas empirical evidence shows the opposite for coronavirus.
Now, sources of infection have free-will, move and interact with others before noticing any symptom, adding huge uncertainty to an already complex urban reality, rendering numerous attempts to prevent coronavirus with Snow’s determinism unfeasible. Yet, the number of interactive Covid-19 dashboards, and the sketches of the so-called ‘post-Covid city’ grow to exhaustion; proving how the gap between spatial analysis of the virus and preventive urban planning action is wide open. Can we technically track and link infections to specific places? Can urban design be “Covid-safe”?
Smartphones and their capacity to capture individual interactions might ease the first issue. Based on the big-yet-sensitive-data, infected and exposed individuals could be rapidly advised by healthcare professionals, and planners could use data to infer the most prone to infection places like Snow did.
However, the digital divides —which include not knowing about and/or being willing to install and use some apps that actively track individuals— cannot be circumvented. Above all, the people’s right to privacy would require that collected data would need to be kept confidential for other than epidemiological purposes, thus limiting its availability for urban planning.
If such data existed, in the best-case scenario it could be openly studied by planners and be spatially aggregated —as it would have to be anonymized and maintained by currently overburdened public institutions. That would limit the spatial detail and update frequency of the data, that result in late responses, or worse, may produce extensive ‘red-linings’ that affect healthy people’s lives in those areas marked as vulnerable.
An alternative approach given the lack of deterministic data is necessarily indeterministic. If cities behave as complex systems, their form is an already digitized open-source of reliable information that allows assessing ‘how certainly’ people will interact in what places, depending on how they are interconnected.
The advances in network theory, computer science, and digital cartography may facilitate this task without encountering the ethical consequences personal tracking has. From that perspective, perhaps the safest city is the one that distributes social interactions in the most uncertain and indeterministic ways, providing complimentary places and paths without concentrating individuals around single, shared-by-many infrastructures.
Nonetheless, this is still a conjecture, not related to Covid-19 but to urban resilience itself, as we still do not know whether urban planning can tackle this pandemic, how to do so, and what data we can trust. Certainly, in a complex and densely interconnected global society, planning for this virus, and other challenges to come, requires embracing uncertainty, as the most indeterministic urban configurations have proven to be the most resilient ones.
In the next contribution to EURA Conversations Cristina Stanus, Lucian Blaga University of Sibiu, Romania, discusses working together.