Enhancing disease surveillance with novel data streams: challenges and opportunities

TLDR

Novel data streams such as web search and social media hold promise for enhancing public health surveillance. The paper proposes a conceptual framework for integrating novel data streams into surveillance, focusing on identifying opportunities and defining minimal validity and utility tests. The framework requires engagement of public health authorities and consideration of diverse objectives and scales across local to international agencies. The authors argue that explicitly defining surveillance objectives and rigorously evaluating and comparing novel data streams against existing data is essential, yet often overlooked in current applications.

Abstract

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature.