Google searches and detection of conjunctivitis epidemics worldwide.

PURPOSE: and Objective: Epidemic and seasonal infectious conjunctivitis outbreaks can adversely impact education, workforce and economy. Yet conjunctivitis is typically not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data.

DESIGN: Search data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates were then assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity.

PARTICIPANTS: Populations by country that searched Google's search engine using our study terms.

MAIN OUTCOME MEASURES: Percent of known conjunctivitis outbreaks also found in the same country and time period by our candidate epidemics, identified from conjunctivitis-related searches RESULTS: We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared to our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 out of 26 (69% sensitivity) of the reported country-wide and/or island nation-wide outbreaks, 9 out of 20 (45% sensitivity) of the reported region and/or district-wide outbreaks, but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, was found on a country-level basis. We also found that 83% of our candidate epidemics had start dates prior (of those, 20% were over 12 weeks prior) to their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone would suggest (P <0.001), unlike control term candidates (P=0.40).

CONCLUSIONS: Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with over 80% detected prior to an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media and more search terms may further improve sensitivity and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data to potentially complementarily benefit traditional reporting and detection systems to improve epidemic awareness.