@article {1435398,
	title = {Google Searches and Detection of Conjunctivitis Epidemics Worldwide},
	journal = {Ophthalmology},
	volume = {126},
	number = {9},
	year = {2019},
	month = {2019 Sep},
	pages = {1219-1229},
	abstract = {PURPOSE: Epidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is 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 then were 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{\textquoteright}s search engine using our study terms. MAIN OUTCOME MEASURES: Percent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches. RESULTS: We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69\% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45\% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83\% of our candidate epidemics had start dates before (of those, 20\% were more than 12 weeks before) their concurrent reported outbreak{\textquoteright}s report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P \&lt; 0.001) unlike control term candidates (P\&nbsp;= 0.40). CONCLUSIONS: Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80\% detected before an outbreak report{\textquoteright}s issuance date, some as early as the reported outbreak{\textquoteright}s start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.},
	issn = {1549-4713},
	doi = {10.1016/j.ophtha.2019.04.008},
	author = {Deiner, Michael S and McLeod, Stephen D and Wong, Jessica and Chodosh, James and Lietman, Thomas M and Porco, Travis C}
}
