Abstract
Hepatitis A (Hep A) can cause sporadic or epidemic disease and has been frequently linked to contamination of the global food chain. Global surveillance data on Hep A are unavailable, and in some countries, reporting is incomplete or not timely, either because of lack of human resources or sensitivities around reporting. The use of vast open-source data such as news-feeds and social media however can overcome barriers to surveillance and provide timely data on global epidemics. In this study we use EpiWATCH, semi-automated outbreak scanning service to review the global epidemiology of Hep A reports from 2016-2018. We reviewed the EpiWATCH Outbreak Alerts database for reports on the Hep A dated between August 1, 2016, to April 31, 2018 which was the analysed by outbreak clusters, location, and time. Of 5098 total entries in the database a total of 169 non-duplicate Hep A outbreak reports were found and included for descriptive analysis. The majority of outbreak reports (68.6%%; N=116/169) originated from the United States of America (USA). The largest Hep A outbreaks were multi-country outbreaks in the European region, and multistate outbreaks in the USA and Australia. Homelessness (mainly in US outbreaks) was the predominant risk factor (40.2%), followed by foodborne outbreaks (26.6%) and outbreaks in men who have sex with men (6.5%). Using EpiWATCH we found that the emergence of outbreaks in homeless people has dominated the epidemiology of Hep A in the U.S and this appears a relatively new phenomenon. Epidemic intelligence systems such as EpiWATCH are a useful proxy for global surveillance of Hep A outbreaks and using open-source data can provide epidemic intelligence and outbreak alerts where global data is unavailable.