Internet-based infectious disease surveillance: assessing the merits and comparing performance across diseases

Tuesday, 19 August 2014
Exhibit hall (Dena'ina Center)
Gabriel J Milinovich, PhD , The University of Queensland, Brisbane, Australia
Archie C Clements, PhD , The University of Queensland, Brisbane, Australia
Wenbiao Hu, PhD , Queensland University of Technology, Brisbane, Australia
INTRODUCTION:  Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Internet-based systems are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with growing global internet penetration and shifts in health-related information seeking behaviour. Whilst monitoring infectious diseases using internet-based data has been applied to single or small groups of infectious diseases, no study has systematically assessed the suitability of this approach for a wide range of infectious diseases of high public health importance and ranked them according to their suitability for monitoring using this approach. This study aims to assess correlations between a wide spectrum of infectious diseases and Internet metrics for related search terms and to identify diseases for which internet-based data could be used to support early warning systems.

METHODS:  Official monthly notifications for 64 infectious diseases were correlated with Google Trends metrics for 164 search terms using data from Australia. Spearman’s rank correlations were performed on both national and state data and results used to assess performance of search terms for estimating disease notifications. Time series cross correlations were also performed on national data. 

RESULTS:  Notifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 13 (76.5%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems. 

CONCLUSIONS:  The findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, these internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases.