{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T22:30:19Z","timestamp":1793485819715,"version":"4.5.0"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T00:00:00Z","timestamp":1770076800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Center of Competence ImmunoPathogen","award":["BG16RFPR002-1.014"],"award-info":[{"award-number":["BG16RFPR002-1.014"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Epidemiologia"],"abstract":"<jats:p>Timely identification of infectious disease threats is essential for public health readiness. Conventional indicator-based surveillance systems, while dependable for tracking established pathogens, frequently lack the agility and sensitivity to detect new infections promptly. Syndromic surveillance, which examines pre-diagnostic and non-specific health indicators from many data sources in near real time, serves as a significant complementary method that improves early warning and situational awareness. This narrative study analysed selected experiences with syndromic surveillance, utilising peer-reviewed literature and institutional records. Four primary data streams were examined: emergency department and hospital records, pharmacy and over the counter (OTC) sales, participative citizen-generated data, and hybrid multi-source systems. Syndromic indicators were reported to identify outbreaks two to fourteen days before standard laboratory reporting across many trials. Data from the emergency department exhibited the highest sensitivity and specificity (47.34% and 91.95%, respectively), whereas pharmacy and participative data offered early indicators at the community level. Integrated systems like ESSENCE (Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA) and SurSaUD\u00ae (Saint-Maurice cedex, Paris, France) attained enhanced accuracy yet necessitated significant data integration and governance capabilities. Syndromic surveillance enhances epidemic preparation by detecting atypical health-seeking behaviours and variations from baseline patterns prior to formal diagnosis. Nonetheless, its efficacy is contingent upon data quality, interoperability, and contextual adaptation. Countries like Bulgaria could improve national early-warning capabilities and overall health security through the gradual adoption of pilot projects and integration with existing surveillance networks.<\/jats:p>","DOI":"10.3390\/epidemiologia7010023","type":"journal-article","created":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T16:46:28Z","timestamp":1770137188000},"page":"23","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Syndromic Surveillance\u2014Review on Different Practices\u2019 Performance and Added Value for Public Health"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0756-5373","authenticated-orcid":false,"given":"Zhivka","family":"Getsova","sequence":"first","affiliation":[{"name":"Epidemiology Department, National Center of Infectious and Parasitic Diseases, 1504 Sofia, Bulgaria"},{"name":"Center of Competence ImmunoPathogen, 1504 Sofia, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9270-5996","authenticated-orcid":false,"given":"Vanya","family":"Rangelova","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Disaster Medicine, Faculty of Public Health, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1093\/oxfordjournals.epirev.a036021","article-title":"Public health surveillance in the United States","volume":"10","author":"Thacker","year":"1988","journal-title":"Epidemiol. Rev."},{"key":"ref_2","unstructured":"World Health Organization (2008). International Health Regulations (2005), World Health Organization."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/S1473-3099(13)70244-5","article-title":"Internet-based surveillance systems for monitoring emerging infectious diseases","volume":"14","author":"Milinovich","year":"2014","journal-title":"Lancet Infect. Dis."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.healthpol.2007.02.009","article-title":"Health systems barriers to effective use of infectious disease surveillance data in the context of decentralization in Georgia: A qualitative study","volume":"83","author":"Djibuti","year":"2007","journal-title":"Health Policy"},{"key":"ref_5","first-page":"100485","article-title":"Modernising infectious disease surveillance and early-warning systems: The need for action in China","volume":"23","author":"Xu","year":"2022","journal-title":"Lancet Reg. Health\u2014West. Pac."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2400084","DOI":"10.2807\/1560-7917.ES.2024.29.44.2400084","article-title":"Integrating indicator-based and event-based surveillance data for risk mapping of West Nile virus in Europe, 2006\u20132021","volume":"29","author":"Serres","year":"2024","journal-title":"Eurosurveillance"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1833","DOI":"10.1016\/S0140-6736(11)60834-9","article-title":"Assessment of syndromic surveillance in Europe","volume":"378","author":"Fouillet","year":"2011","journal-title":"Lancet"},{"key":"ref_8","unstructured":"Schaechter, M. (2009). Surveillance of infectious diseases. Encyclopedia of Microbiology, Academic Press. [3rd ed.]."},{"key":"ref_9","first-page":"100230","article-title":"Climate change and infectious disease in Europe: Impact, projections and adaptation","volume":"9","author":"Semenza","year":"2021","journal-title":"Lancet Reg. Health\u2014Eur."},{"key":"ref_10","first-page":"54","article-title":"Risks from the emergence of viral hemorrhagic fevers in Bulgaria and Europe","volume":"3","author":"Getzova","year":"2022","journal-title":"Gen. Med."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"106225","DOI":"10.1016\/j.actatropica.2021.106225","article-title":"Climate change and zoonoses: Current status, knowledge gaps, and future trends","volume":"226","author":"Rupasinghe","year":"2022","journal-title":"Acta Trop."},{"key":"ref_12","unstructured":"UK Health Security Agency (2025, December 05). First Detection of West Nile Virus in UK Mosquitoes, Available online: https:\/\/www.gov.uk\/government\/news\/first-detection-of-west-nile-virus-in-uk-mosquitoes."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1016\/j.jiph.2020.01.313","article-title":"Enhanced surveillance and response approaches for pilgrims and local Saudi populations against emerging Nipah, Zika and Ebola virus outbreaks","volume":"13","author":"Tambo","year":"2020","journal-title":"J. Infect. Public Health"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"101013","DOI":"10.1016\/j.nmni.2022.101013","article-title":"Reverse zoonosis and monkeypox: Time for a more advanced global surveillance system for emerging pathogens","volume":"48","author":"Afrooghe","year":"2022","journal-title":"N. Microbes N. Infect."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/S0140-6736(20)30183-5","article-title":"Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China","volume":"395","author":"Huang","year":"2020","journal-title":"Lancet"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1846","DOI":"10.7150\/ijbs.45018","article-title":"Initial success in the identification and management of COVID-19 indicates human-to-human transmission in Wuhan, China","volume":"16","author":"Awadasseid","year":"2020","journal-title":"Int. J. Biol. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1016\/S0140-6736(21)02796-3","article-title":"Estimating excess mortality due to the COVID-19 pandemic, 2020\u20132021","volume":"399","author":"Wang","year":"2022","journal-title":"Lancet"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.puhe.2020.11.016","article-title":"Doubled mortality rate during the COVID-19 pandemic in Italy","volume":"190","author":"Odone","year":"2021","journal-title":"Public Health"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.bsheal.2021.03.002","article-title":"Finding the real COVID-19 case-fatality rates for SAARC countries","volume":"3","author":"Shah","year":"2021","journal-title":"Biosaf. Health"},{"key":"ref_20","unstructured":"World Health Organization (2025, June 30). WHO Director-General Declares Mpox Outbreak a Public Health Emergency of International Concern. Available online: https:\/\/www.who.int\/news\/item\/14-08-2024-who-director-general-declares-mpox-outbreak-a-public-health-emergency-of-international-concern."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"669","DOI":"10.3201\/eid1604.090688","article-title":"Innovative uses for syndromic surveillance","volume":"16","author":"Zhang","year":"2010","journal-title":"Emerg. Infect. Dis."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"298","DOI":"10.3201\/eid3102.240533","article-title":"Global epidemiology of outbreaks of unknown cause identified by open-source intelligence, 2020\u20132022","volume":"31","author":"Honeyman","year":"2025","journal-title":"Emerg. Infect. Dis."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1067\/mem.2002.123127","article-title":"The Frontlines of Medicine Project","volume":"39","author":"Barthell","year":"2002","journal-title":"Ann. Emerg. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.annemergmed.2004.01.019","article-title":"Syndromic surveillance using regional emergency medicine Internet","volume":"44","author":"Foldy","year":"2004","journal-title":"Ann. Emerg. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1197\/jamia.M1352","article-title":"Automated syndromic surveillance for the 2002 Winter Olympics","volume":"10","author":"Gesteland","year":"2003","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_26","unstructured":"Espino, J.U., and Wagner, M.M. (2001, January 3\u20137). Accuracy of ICD-9-coded chief complaints for detection of acute respiratory illness. Proceedings of the AMIA Symposium 2001, Washington, DC, USA."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.annemergmed.2004.03.030","article-title":"Syndromic surveillance: Effects of syndrome grouping on outbreak detection","volume":"44","author":"Reis","year":"2004","journal-title":"Ann. Emerg. Med."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"e304","DOI":"10.5210\/ojphi.v11i1.9666","article-title":"Communicating detection capabilities of syndromic surveillance systems","volume":"11","author":"Morbey","year":"2019","journal-title":"Online J. Public Health Inform."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1017\/S0950268808001374","article-title":"Syndromic surveillance: Sensitivity and predictive value of case definitions","volume":"137","author":"Guasticchi","year":"2009","journal-title":"Epidemiol. Infect."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.annemergmed.2005.06.092","article-title":"Improving syndrome surveillance case definitions and Outcomes by Using Existing Data","volume":"46","author":"Roberts","year":"2005","journal-title":"Ann. Emerg. Med."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.annemergmed.2004.01.020","article-title":"The Frontlines of Medicine Project progress report: Standardized communication of emergency department triage data for syndromic surveillance","volume":"44","author":"Barthell","year":"2004","journal-title":"Ann. Emerg. Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1197\/jamia.M1052","article-title":"Roundtable on bioterrorism detection: Information system\u2013based surveillance","volume":"9","author":"Lober","year":"2002","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1097\/00124784-200107060-00006","article-title":"The emerging science of very early detection of disease outbreaks","volume":"7","author":"Wagner","year":"2001","journal-title":"J. Public Health Manag. Pract."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1197\/jamia.M1356","article-title":"Implementing syndromic surveillance: A practical guide informed by early experience","volume":"11","author":"Mandl","year":"2003","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2532","DOI":"10.1111\/tbed.13598","article-title":"Quantification of the sensitivity of early detection surveillance","volume":"67","author":"Cameron","year":"2020","journal-title":"Transbound. Emerg. Dis."},{"key":"ref_36","first-page":"1","article-title":"Summary of notifiable diseases\u2014United States, 2005","volume":"54","author":"McNabb","year":"2007","journal-title":"MMWR. Morb. Mortal. Wkly. Rep."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Yang, W. (2017). Infectious disease surveillance and early warning system during Beijing Olympic Games. Early Warning for Infectious Disease Outbreaks, Academic Press.","DOI":"10.1016\/B978-0-12-812343-0.00008-4"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.jiac.2019.09.011","article-title":"Syndromic surveillance using ambulance transfer data in Tokyo, Japan","volume":"26","author":"Sugishita","year":"2020","journal-title":"J. Infect. Chemother."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.ijid.2022.06.003","article-title":"Syndromic surveillance of respiratory infections during protracted conflict: Experiences from northern Syria, 2016\u20132021","volume":"122","author":"Tarnas","year":"2022","journal-title":"Int. J. Infect. Dis."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1203\/00006450-197909000-00014","article-title":"Sales of nonprescription cold remedies: A unique method of influenza surveillance","volume":"13","author":"Welliver","year":"1979","journal-title":"Pediatr. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"580","DOI":"10.2105\/AJPH.87.4.580","article-title":"A community waterborne outbreak of salmonellosis and the effectiveness of a boil water order","volume":"87","author":"Angulo","year":"1997","journal-title":"Am. J. Public Health"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1017\/S0950268897008327","article-title":"Surveillance data for waterborne illness detection: An assessment following a massive waterborne outbreak of Cryptosporidium infection","volume":"120","author":"Proctor","year":"1998","journal-title":"Epidemiol. Infect."},{"key":"ref_43","first-page":"185","article-title":"Waterborne cryptosporidiosis outbreak, North Battleford, Saskatchewan, Spring 2001","volume":"27","author":"Stirling","year":"2001","journal-title":"Can. Commun. Dis. Rep."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1197\/jamia.M1377","article-title":"Early detection of pediatric respiratory and diarrheal outbreaks from retail sales of electrolyte products","volume":"10","author":"Hogan","year":"2003","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"ref_45","first-page":"349","article-title":"Evaluation of over-the-counter pharmaceutical sales as a possible early warning indicator of public health","volume":"24","author":"Magruder","year":"2003","journal-title":"Johns Hopkins Univ. Appl. Phys. Lab. Tech. Dig."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Pivette, M., Mueller, J.E., Cr\u00e9pey, P., and Bar-Hen, A. (2014). Drug sales data analysis for outbreak detection of infectious diseases: A systematic literature review. BMC Infect. Dis., 14.","DOI":"10.1186\/s12879-014-0604-2"},{"key":"ref_47","first-page":"41","article-title":"Monitoring over-the-counter medication sales for early detection of disease outbreaks\u2014New York City","volume":"54","author":"Das","year":"2005","journal-title":"MMWR Morb. Mortal. Wkly. Rep."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"233","DOI":"10.7883\/yoken.JJID.2009.233","article-title":"Seasonal influenza surveillance using prescription data for anti-influenza medications","volume":"62","author":"Yoshida","year":"2009","journal-title":"Jpn. J. Infect. Dis."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"9540","DOI":"10.1038\/srep09540","article-title":"Estimating influenza attack rates in the United States using a participatory cohort","volume":"5","author":"Chunara","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"S386","DOI":"10.1093\/infdis\/jiw280","article-title":"Participatory syndromic surveillance of influenza in Europe","volume":"214","author":"Guerrisi","year":"2016","journal-title":"J. Infect. Dis."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"100462","DOI":"10.1016\/j.epidem.2021.100462","article-title":"Participatory syndromic surveillance as a tool for tracking COVID-19 in Bangladesh","volume":"35","author":"Mahmud","year":"2021","journal-title":"Epidemics"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"S124","DOI":"10.1016\/j.annemergmed.2004.07.397","article-title":"Syndromic surveillance for infectious disease outbreaks using chief complaint data","volume":"44","author":"Thomas","year":"2004","journal-title":"Ann. Emerg. Med."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.ajem.2009.09.009","article-title":"Emergency department syndromic surveillance for novel H1N1 Spring 2009","volume":"29","author":"Bellazzini","year":"2011","journal-title":"Am. J. Emerg. Med."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Rosenk\u00f6tter, N., Ziemann, A., Riesgo, L.G., Gillet, J.B., Vergeiner, G., Krafft, T., and Brand, H. (2013). Validity and timeliness of syndromic influenza surveillance during the autumn\/winter wave of A (H1N1) influenza 2009: Results of emergency medical dispatch, ambulance and emergency department data from three European regions. BMC Public Health, 13.","DOI":"10.1186\/1471-2458-13-905"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Chikotie, T., Watson, B., Kimanuka, U., and Banda, T. Leveraging electronic syndromic surveillance synthetic data to predict diarrhoea in Zimbabwean children under five: An explainable AI framework. Proceedings of the 2025 IST-Africa Conference (IST-Africa), Nairobi, Kenya, 28\u201330 May 2025.","DOI":"10.23919\/IST-Africa67297.2025.11060542"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"e941209-1","DOI":"10.12659\/MSM.941209","article-title":"Infectious disease surveillance using artificial intelligence and its role in epidemic and pandemic preparedness","volume":"29","author":"Parums","year":"2023","journal-title":"Med. Sci. Monit."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Lake, I.R., Col\u00f3n-Gonz\u00e1lez, F.J., Barker, G.C., Morbey, R.A., Smith, G.E., and Elliot, A.J. (2019). Machine learning to refine decision making within a syndromic surveillance service. BMC Public Health, 19.","DOI":"10.1186\/s12889-019-6916-9"}],"container-title":["Epidemiologia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2673-3986\/7\/1\/23\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T17:03:54Z","timestamp":1770138234000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2673-3986\/7\/1\/23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,3]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["epidemiologia7010023"],"URL":"https:\/\/doi.org\/10.3390\/epidemiologia7010023","relation":{},"ISSN":["2673-3986"],"issn-type":[{"value":"2673-3986","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,3]]}}}