Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet

Abstract

Infodemiology can be defined as the science of distribution and determinants of information in an electronic medium, specifically the Internet, or in a population, with the ultimate aim to inform public health and public policy. Infodemiology data can be collected and analyzed in near real time. Examples for infodemiology applications include the analysis of queries from Internet search engines to predict disease outbreaks (eg. influenza), monitoring peoples' status updates on microblogs such as Twitter for syndromic surveillance, detecting and quantifying disparities in health information availability, identifying and monitoring of public health relevant publications on the Internet (eg. anti-vaccination sites, but also news articles or expert-curated outbreak reports), automated tools to measure information diffusion and knowledge translation, and tracking the effectiveness of health marketing campaigns. Moreover, analyzing how people search and navigate the Internet for health-related information, as well as how they communicate and share this information, can provide valuable insights into health-related behavior of populations. Seven years after the infodemiology concept was first introduced, this paper revisits the emerging fields of infodemiology and infoveillance and proposes an expanded framework, introducing some basic metrics such as information prevalence, concept occurrence ratios, and information incidence. The framework distinguishes supply-based applications (analyzing what is being published on the Internet, eg. on Web sites, newsgroups, blogs, microblogs and social media) from demand-based methods (search and navigation behavior), and further distinguishes passive from active infoveillance methods. Infodemiology metrics follow population health relevant events or predict them. Thus, these metrics and methods are potentially useful for public health practice and research, and should be further developed and standardized.

Keywords: epidemiology; infodemiology; infodemic; infoveillance; internet; forecasting; population surveillance; influenza; epidemic; pandemic; public health; consumer health information; epidemiological indicators; quality indicators; information storage and retrieval; biosurveillance; syndromic surveillance; human.

Figure 1

Information prevalence versus disease incidence scatterplot (Eysenbach, in preparation)

Figure 2

Information incidence (keyword occurrence) trends from Twitter status feeds ("tweets") (DIYCity/sickcity)

Figure 3

Relationship between information demand (searches on Google), flu cases, and influenza-like illnesses reported by sentinel physicians. Partial data from a five-year prospective study harvesting search and click data from Google 2004-2007 (Eysenbach 2007, presented at AMIA Annual Fall Symposium, Chicago 2007, method as described in [1])