Augmenting Public Health Surveillance with Big Data: Measurement Framework and Selected Applications

Abstract

This paper examines opportunities for big data in augmenting public health surveillance. We describe the use of social listening, remote sensing and mobility indices in supplementing surveillance data. We discuss the time varying reproductive number as an alternative to the basic reproductive number for monitoring an ongoing pandemic, present the INFORM risk management model for integrating insights, and discuss modalities for decision support systems. Selected examples of big data surveillance applications are presented along with considerations for further work.