Health Innovations and Applications: A summary of creative data and analytical techniques

Abstract

The past ten years have seen a rapid evolution of innovative data sources and methods for public health surveillance (PHS), indicating the need for a closer examination of the scientific maturity, viability, and practicality of use. The data from social media, internet search engines, the Internet of Things (IoT), wastewater surveillance, participatory surveillance, artificial intelligence (AI), and nowcasting are some of the recent innovations in PHS that are summarized in this article. By enhancing disease estimates, encouraging early warning for disease outbreaks, and producing more and/or more timely information for public health action, examples found indicate that new data sources and analytical techniques have the potential to improve PHS. AI is being used more and more to process vast amounts of digital data, and wastewater surveillance has resurfaced as a useful tool for early detection of the coronavirus disease 2019 (COVID-19) and other pathogens. Lack of scientific maturity, a dearth of real-world public health implementation examples, privacy and security concerns, and health equity implications are some of the obstacles to putting new approaches into practice. Important next steps for expanding the use of innovation include strengthening data governance, creating explicit guidelines for the use of AI technologies, and training the public health workforce.