Analysis of Web access logs for surveillance of influenza.

RODS Laboratory, Center for Biomedical Informatics, University of Pittsburgh, PA 15219, USA.
Studies in health technology and informatics 02/2004; 107(Pt 2):1202-6.
Source: PubMed

ABSTRACT The purpose of this study was to determine whether the level of influenza in a population correlates with the number of times that internet users access information about influenza on health-related Web sites. We obtained Web access logs from the Healthlink Web site. Web access logs contain information about the user and the information the user accessed, and are maintained electronically by most Web sites, including Healthlink. We developed weekly counts of the number of accesses of selected influenza-related articles on the Healthlink Web site and measured their correlation with traditional influenza surveillance data from the Centers for Disease Control and Prevention (CDC) using the cross-correlation function (CCF). We defined timeliness as the time lag at which the correlation was a maximum. There was a moderately strong correlation between the frequency of influenza-related article accesses and the CDC's traditional surveillance data, but the results on timeliness were inconclusive. With improvements in methods for performing spatial analysis of the data and the continuing increase in Web searching behavior among Americans, Web article access has the potential to become a useful data source for public health early warning systems.

1 Bookmark
  • [Show abstract] [Hide abstract]
    ABSTRACT: Mass gatherings, such as music festivals and religious events, pose a health care challenge because of the risk of transmission of communicable diseases. This is exacerbated by the fact that participants disperse soon after the gathering, potentially spreading disease within their communities. The dispersion of participants also poses a challenge for traditional surveillance methods. The ubiquitous use of the Internet may enable the detection of disease outbreaks through analysis of data generated by users during events and shortly thereafter.
    Journal of Medical Internet Research 01/2014; 16(6):e154. · 3.77 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The internet and the World Wide Web have changed the ways that we function. As technologies grow and adapt, there is a huge potential for the internet to affect drug research and development, as well as many other aspects of clinical pharmacology. We review some of the areas of interest to date and discuss some of the potential areas in which internet-based technology can be exploited. Information retrieval from the web by health-care professionals is common, and bringing evidence-based medicine to the bedside affects the care of patients. As a primary research tool the web can provide a vast array of information in generating new ideas or exploring previous research findings. This has facilitated systematic reviewing, for example. The content of the web has become a subject of research in its own right. The web is also widely used as a research facilitator, including enhancement of communication between collaborators, provision of online research tools (such as questionnaires, management of large scale multicentre trials, registration of clinical trials) and distribution of information. Problems include information overload, ignorance of early data that are not indexed in databases, difficulties in keeping web sites up to date and assessing the validity of information retrieved. Some web-based activities are viewed with suspicion, including analysis by pharmaceutical companies of drug information to facilitate direct-to-consumer advertising of novel pharmaceuticals. Use of these technologies will continue to expand in often unexpected ways. Clinical pharmacologists must embrace internet technology and include it as a key priority in their research agenda.
    British Journal of Clinical Pharmacology 02/2012; 73(6):953-8. · 3.58 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent research has shown the potential of Web queries as a source for syndromic surveillance, and existing studies show that these queries can be used as a basis for estimation and prediction of the development of a syndromic disease, such as influenza, using log linear (logit) statistical models. Two alternative models are applied to the relationship between cases and Web queries in this paper. We examine the applicability of using statistical methods to relate search engine queries with scarlet fever cases in the UK, taking advantage of tools to acquire the appropriate data from Google, and using an alternative statistical method based on gamma distributions. The results show that using logit models, the Pearson correlation factor between Web queries and the data obtained from the official agencies must be over 0.90, otherwise the prediction of the peak and the spread of the distributions gives significant deviations. In this paper, we describe the gamma distribution model and show that we can obtain better results in all cases using gamma transformations, and especially in those with a smaller correlation factor.
    Informatics for Health and Social Care 03/2012; 37(2):106-24. · 1.27 Impact Factor

Full-text (3 Sources)

Available from
May 26, 2014