{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T22:03:11Z","timestamp":1789509791448,"version":"build-2803163510"},"reference-count":21,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Public Health Surveill"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Automated outbreak detection can enhance infectious disease surveillance by enabling early identification of outbreaks and supporting timely public health measures. However, information on its current use by national public health institutes remains limited.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aimed to provide an updated and extended overview of automated outbreak detection use in the European Union and the United Kingdom by (1) assessing current demand, (2) examining the availability of key prerequisites within existing surveillance systems, and (3) identifying challenges and requirements for implementation.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A mixed methods approach was applied as part of the Joint Action UNITED4Surveillance. Data were collected between April 2023 and January 2024 through an online survey sent to 25 countries, an in-person workshop with experts from 16 countries, and follow-up meetings with participating national public health institutes. Additional information for selected countries was obtained from the literature. Data were analyzed descriptively.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Twenty-one countries completed the survey. In total, 33.3% (n=7) of the countries had established automated outbreak detection systems, 19% (n=4) were planning implementation, and 47.6% (n=10) participated in a pilot project. All surveyed countries reported acting on detected surveillance signals. Most had suitable surveillance infrastructure, including case-based data (n=20, 95.2%), daily reporting (n=21, 100%), and at least 3 years of historical data (n=21, 100%). Main barriers to implementation included limited funding (n=15, 71.4%), insufficient IT capacity, and data quality issues (n=9, 42.9%). Despite heterogeneity in methods and system design, outputs and user requirements were largely similar across countries, with needs for flexible outputs, stratification, and user-friendly interfaces.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n While the specific methods in existing automated outbreak detection systems differ, overall demands and outputs are similar, suggesting that a single tool could serve multiple countries. European Union\u2013funded Joint Actions may help address some of these barriers by supporting collaborative tool development and knowledge exchange.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/96576","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T08:25:06Z","timestamp":1787127906000},"page":"e96576-e96576","source":"Crossref","is-referenced-by-count":0,"title":["Requirements and Implementation Challenges of Automated Outbreak Detection Systems in the European Union: Mixed Methods Study"],"prefix":"10.2196","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0872-8990","authenticated-orcid":false,"given":"Paulina","family":"vom Felde genannt Imbusch","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5392-1774","authenticated-orcid":false,"given":"Ann Christin","family":"Vietor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1663-3499","authenticated-orcid":false,"given":"Inessa","family":"Markus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4678-1813","authenticated-orcid":false,"given":"Michaela","family":"Diercke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4894-6124","authenticated-orcid":false,"given":"Alexander","family":"Ullrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2019.103181","article-title":"A systematic review of aberration detection algorithms used in public health surveillance","volume":"94","author":"Yuan","journal-title":"J Biomed Inform"},{"key":"R2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijid.2016.10.005","article-title":"Drivers of earlier infectious disease outbreak detection: a systematic literature review","volume":"53","author":"Steele","journal-title":"Int J Infect Dis"},{"issue":"RR-5","key":"R3","first-page":"1","volume":"53","author":"Buehler","journal-title":"MMWR Recomm Rep"},{"issue":"1","key":"R4","doi-asserted-by":"publisher","DOI":"10.1017\/ash.2022.333","article-title":"The future of automated infection detection: innovation to transform practice (part III\/III)","volume":"3","author":"Branch-Elliman","journal-title":"Antimicrob Steward Healthc Epidemiol"},{"issue":"1","key":"R5","doi-asserted-by":"publisher","DOI":"10.1186\/s12874-023-02050-z","article-title":"Outbreak detection algorithms based on generalized linear model: a review with new practical examples","volume":"23","author":"Zareie","journal-title":"BMC Med Res Methodol"},{"issue":"1-2","key":"R6","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1093\/biomet\/41.1-2.100","article-title":"Continuous inspection schemes","volume":"41","author":"Page","journal-title":"Biometrika"},{"issue":"2 Suppl 1","key":"R7","doi-asserted-by":"publisher","first-page":"i89","DOI":"10.1007\/pl00022319","article-title":"The bioterrorism preparedness and response Early Aberration Reporting System (EARS)","volume":"80","author":"Hutwagner","journal-title":"J Urban Health"},{"issue":"1","key":"R8","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1111\/j.1467-985X.2011.00714.x","article-title":"Statistical methods for the prospective detection of infectious disease outbreaks: a review","volume":"175","author":"Unkel","journal-title":"J R Stat Soc Ser A Stat Soc"},{"issue":"3","key":"R9","doi-asserted-by":"publisher","first-page":"547","DOI":"10.2307\/2983331","article-title":"A statistical algorithm for the early detection of outbreaks of infectious disease","volume":"159","author":"Farrington","journal-title":"J R Stat Soc Ser A Stat Soc"},{"issue":"7","key":"R10","doi-asserted-by":"publisher","first-page":"1206","DOI":"10.1002\/sim.5595","article-title":"An improved algorithm for outbreak detection in multiple surveillance systems","volume":"32","author":"Noufaily","journal-title":"Stat Med"},{"issue":"36","key":"R11","first-page":"19658","volume":"15","author":"Hulth","journal-title":"Euro Surveill"},{"issue":"13","key":"R12","doi-asserted-by":"publisher","DOI":"10.2807\/1560-7917.ES.2016.21.13.30180","article-title":"A system for automated outbreak detection of communicable diseases in Germany","volume":"21","author":"Salmon","journal-title":"Euro Surveill"},{"key":"R13","unstructured":"Ghozzi S Ullrich A . 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