The Dangers of Data Colonialism in Precision Public Health

Abstract

Precision public health has been defined as using multi-level and relatively novel data types (such as patient-provided digital data from internet applications and digital medical records) in order to predict and track population level disease dynamics as well as develop targeted interventions (Khoury, 2015, Khoury et al., 2018). Despite the promises of precision public health, it is also important to examine the field’s potential pitfalls, specifically its resonance with data colonialism. Without adequate attention to this emerging field’s vulnerabilities, precision public health efforts may continue histories of extraction and marginalization.