The conspiracy of Covid-19 and 5G: Spatial analysis fallacies in the age of data democratization

Eoin Flaherty, Tristan Sturm, Elizabeth Farries

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)
65 Downloads (Pure)

Abstract

In a context of mistrust in public health institutions and practices, anti-COVID/vaccination protests and the storming of Congress have illustrated that conspiracy theories are real and immanent threat to health and wellbeing, democracy, and public understanding of science. One manifestation of this is the suggested correlation of COVID-19 with 5G mobile technology. Throughout 2020, this alleged correlation was promoted and distributed widely on social media, often in the form of maps overlaying the distribution of COVID-19 cases with the instillation of 5G towers. These conspiracy theories are not fringe phenomena, and they form part of a growing repertoire for conspiracist activist groups with capacities for organised violence. In this paper, we outline how spatial data have been co-opted, and spatial correlations asserted by conspiracy theorists. We consider the basis of their claims of causal association with reference to three key areas of geographical explanation: (1) how social properties are constituted and how they exert complex causal forces, (2) the pitfalls of correlation with spatial and ecological data, and (3) the challenges of specifying and interpreting causal effects with spatial data. For each, we consider the unique theoretical and technical challenges involved in specifying meaningful correlation, and how their discarding facilitates conspiracist attribution. In doing so, we offer a basis both to interrogate conspiracists’ uses and interpretation of data from elementary principles and offer some cautionary notes on the potential for their future misuse in an age of data democratization. Finally, this paper contributes to work on the basis of conspiracy theories in general, by asserting how – absent an appreciation of these key methodological principles – spatial health data may be especially prone to co-option by conspiracist groups.
Original languageEnglish
Article number114546
Number of pages10
JournalSocial Science & Medicine
Volume293
Early online date23 Dec 2021
DOIs
Publication statusPublished - 01 Jan 2022

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