Employing Quantitative and Qualitative Analytic Methods for Internet Biosurveillance of Pandemic Influenza
Year: 2013
Type: dissertation
Abstract: Public health surveillance has grown rapidly alongside the availability of big data and an increasingly interconnected global community.Internet biosurveillance, one facet of these surveillance activities, uses unstructured, largely informal data to provide early warning and situational awareness of globally relevant infectious disease events to their 2008/2009) to the preceding seasonal year (1967 and 2007/2008).We found a highly significant correlation (p < 0.0001) between direct indicator rates and pooled indirect indicator rates during the pandemic years (1968 and 2008/2009), suggesting the two indicator types tend to co-occur in news media.We found that specific indirect indicator category rates were highly correlated (r > 0.8) to direct indicator rates during the pandemic years: 1) Hong Kong -Official Acknowledgement, 2) Mexico City -Official Acknowledgement and Official Action.The qualitative results found that different indicator categories were meaningful for each pandemic, meaning can be lost when indicators are only analyzed quantitatively, and the content of one alarming news article can be enough to initiate a public health response.The conclusions of this study suggest that Internet biosurveillance may be more impactful if quantitative and qualitative analytic methods, like those tested here, are incorporated into the overall process for early warning and situational awareness of pandemic influenza.v Preface SARS, Swine Flu, MERS, TDR-TB, H7N9 Bird Flu: all of these infectious diseases have emerged 1 , posed threats to global health, and received extensive media attention within the last decade (Christian et al. 2013;Velayati, Farnia, and Masjedi 2013; N. P. Nelson et al. 2012; N. Nelson, Brownstein, and Hartley 2010;Walters et al. 2010;Brownstein, Freifeld, and Madoff 2009).Media interest in infectious disease outbreaks, coupled with emerging technologies that have provided additional Internet data inputs, has enabled and empowered the development of a new approach to infectious disease surveillance called Internet biosurveillance, or digital disease detection (DDD).Internet biosurveillance complements traditional public health surveillance and has a mission to provide early warning and situational awareness of infectious disease outbreaks, in hopes of aiding in a more rapid public health response, especially those with the potential to become globally important (D.M. Hartley et al. 2013;Corley et al. 2012;
Author: Emily Iarocci
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W755074498