Abstract
Background
Participatory surveillance complements sentinel influenza monitoring in high-income settings, yet no platform has targeted physicians as both participants and clinical sentinels. We established SALGINTR, a digital, physician-driven participatory surveillance system for influenza-like illness (ILI), built from free cloud tools for ∼US $100.
Methods
Physicians across Türkiye were recruited via snowball sampling to submit weekly ILI self-reports online (https://www.salgin.com.tr) during epidemiological weeks 40–52 of the 2025–26 season. The ECDC ILI case definition was applied, and independent episodes were ascertained by a clinical-episode rule (consecutive symptomatic weeks attributed to the same agent counted as one). Concordance with national ERVISS sentinel surveillance was assessed using Pearson and Spearman correlations, cross-correlation, and Bland–Altman agreement. Detection used seven aberration algorithms (EARS C1–C3, CUSUM, EWMA, Farrington, Percentile).
Results
Of 243 registered physicians, 197 (analytical cohort) contributed 1,484 respondent-weeks. Cumulative ILI incidence was 50.8%, with 156 independent episodes from 190 symptomatic person-weeks. Weekly viral-systemic positivity showed dynamics concordant with sentinel surveillance after smoothing (raw Pearson r = 0.492, p = 0.088; 3W-MA r = 0.736, p = 0.010; Spearman ρ = 0.809, p = 0.003). Bland–Altman indicated no significant systematic bias (mean difference +4.6 pp; 95% LoA −18.3 to + 27.4). Both systems peaked in multi-algorithm consensus at the epidemic peak (W52); first-alarm timing showed no consistent lead (≈0 weeks).
Conclusions
SALGINTR shows that a physician-driven digital participatory surveillance system can generate ILI signals concordant with established sentinel surveillance at minimal cost. This proof-of-concept supports participatory surveillance as a complementary component of mosaic respiratory disease surveillance in middle-income settings.
Key messages
• A physician-driven digital participatory surveillance system can generate ILI signals concordant with sentinel surveillance at under $100 infrastructure cost.
• Signal timing showed no lead or lag versus sentinel surveillance; but as SALGINTR reports in real time while official data lag 2–4 weeks, it operationally delivers earlier epidemic warning in practice