Work

Syndromic Surveillance—Review on Different Practices’ Performance and Added Value for Public Health

Year: 2026

Type: article

Abstract: 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 global experiences with syndromic surveillance from 2000 to 2025, 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 identified outbreaks two to fourteen days before to standard laboratory reporting across many trials. Data from the emergency department exhibited the highest sensitivity and specificity (respectively 47.34% and 91.95% according to ), whereas pharmacy and participative data offered early indicators at the community level. Integrated systems like ESSENCE (United States) and SurSaUD® (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 adaption. 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.

Source: Epidemiologia

DOI: 10.3390/epidemiologia7010023

Authors: Zhivka Getsova, Vanya Rangelova

Institutions: National Center of Infectious and Parasitic Diseases, Medical University Plovdiv

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,448