Use of big data in the surveillance of veterinary diseases: early detection of tick paralysis in companion animals

Use of big data in the surveillance of veterinary diseases: early detection of tick paralysis in companion animals

Background: Tick paralysis, resultant from envenomation by the scrub-tick Ixodes holocyclus, is a serious threat for small companion animals in the eastern coast of Australia. We hypothesise that surveillance systems that are built on Internet search queries may provide a more timely indication of high-risk periods more effectively than current approaches. Methods: Monthly tick paralysis notifications in dogs and cats across Australia and the states of Queensland (QLD) and New South Wales (NSW) were retrieved from Disease WatchDog surveillance system for the period 2011-2013. Internet search terms related to tick paralysis in small companion animals were identified using Google Correlate, and corresponding search frequency metrics were downloaded from Google Trends. Spearman's rank correlations and time series cross correlations were performed to assess which Google search terms lead or are synchronous with tick paralysis notifications. Results: Metrics data were available for 24 relevant search terms at national level, 16 for QLD and 18 for NSW, and they were all significantly correlated with tick paralysis notifications (P < 0.05). Among those terms, 70.8, 56.3 and 50 % showed strong Spearman's correlations, at national level, for QLD, and for NSW respectively, and cross correlation analyses identified searches which lead notifications at national or state levels. Conclusion: This study demonstrates that Internet search metrics can be used to monitor the occurrence of tick paralysis in companion animals, which would facilitate early detection of high-risk periods for tick paralysis cases. This study constitutes the first application of the rapidly emerging field of Internet-based surveillance to veterinary science.