A smartphone-based system for population-scale anonymized public health data collection and intervention

The wide availability and sophisticated functionalities of current mobile devices or smartphones can provide a new form of data collection capability relevant to public health. However, current data that is collected is typically siloed on individual devices and/or specific proprietary systems, only intended for individual use, limiting possible utilization for public health purposes. Additionally, the current aggregate data collection approaches do not incorporate key public health components such as support for interventions and demographic data. To address these limitations, in this paper we introduce and evaluate a system to provide aggregate population health data via utilizing smartphone capabilities, whilst fully maintaining the anonymity and privacy of each individual. In this paper we provide a detailed architecture, a method for local processing of aggregate population health data utilizing adaptive privacy thresholds to create a multi-party flexible approach to participatory data submission and evaluate its privacy properties at large scale.