SALGINTR: development and early evaluation of a low-cost cloud-based digital participatory surveillance system for influenza-like Illness among physicians in Türkiye - a proof of concept.

backgroundParticipatory surveillance complements sentinel influenza monitoring in high-income settings, yet no such 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), assembling an automated data collection and analysis pipeline from freely available cloud-based tools at a total infrastructure cost of approximately US $100.

methodsPhysicians across Türkiye were recruited via snowball sampling to provide weekly self-reports of ILI symptoms through an online platform ( www.salgin.com.tr ) during epidemiological weeks 40-52 of the 2025-26 influenza season. ECDC ILI case definition was applied, and independent ILI episodes were ascertained using a clinical-episode rule whereby consecutive symptomatic weeks attributed to the same agent were counted as a single episode. Temporal concordance with national sentinel surveillance was assessed by Pearson and Spearman correlation with moving-block bootstrap confidence intervals, lead-lag cross-correlation, and Bland-Altman agreement. Epidemic detection was evaluated using a panel of six aberration detection algorithms (EARS C1-C3, negative-binomial CUSUM, EWMA, empirical 95th percentile).

resultsOf 243 registered physicians, 197 (analytical cohort) contributed 1,484 respondent-weeks of observation. Cumulative ILI incidence was 50.8% (100/197), with 156 independent episodes identified from 190 symptomatic person-weeks using a clinical-episode definition. Season-level viral positivity was similar in the two streams (SALGINTR 17.3%, 95% CI 11.7-24.2, 27/156; sentinel 14.5%, 95% CI 12.8-16.2, 247/1,709). Weekly SALGINTR viral-systemic positivity was temporally concordant with sentinel surveillance under the pre-specified causal three-week moving average (Pearson r = 0.575, 95% CI 0.35 to 0.90; Spearman ρ = 0.747; pre-epidemic W40-W49 r = 0.886, 95% CI 0.38 to 0.94). Bland-Altman analysis indicated no significant systematic bias (mean difference + 4.6 pp; 95% limits of agreement - 18.3 to + 27.4 pp). Neither system produced any alarm during the ten pre-epidemic weeks, and alarm agreement across the window was substantial (Cohen's κ = 0.755; specification-curve median κ = 0.639 across 72 analytical choices). Lead-lag analysis identified no timing advantage in either direction (peak lag - 1 week; bootstrap CI - 2 to + 2 weeks).

conclusionsSALGINTR demonstrates 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 integration of participatory surveillance as a complementary component within mosaic respiratory disease surveillance frameworks in middle-income settings.