{
  "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.\n\nMethods: 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).\n\nResults: 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).\n\nConclusions: 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.\n\nKey messages: • A physician-driven digital participatory surveillance system can generate ILI signals concordant with sentinel surveillance at under $100 infrastructure cost.\n\n• 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",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "abstract",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "E Öntaş"
    },
    {
      "name": "H Guclu"
    },
    {
      "name": "Y Aydin Son"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ds61xmg7x6bth.bib",
  "cited_by": 0,
  "doi": "10.1093/eurpub/ckag169.1641",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13699753/",
  "id": "ds61xmg7x6bth",
  "issns": [
    "1101-1262",
    "1464-360X"
  ],
  "landing_url": "https://doi.org/10.1093/eurpub/ckag169.1641",
  "language": "en",
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "6. Poster Displays"
    ],
    [
      "heading",
      "AcademicSubjects/MED00860"
    ],
    [
      "heading",
      "AcademicSubjects/SOC01210"
    ],
    [
      "heading",
      "AcademicSubjects/SOC02610"
    ],
    [
      "heading",
      "DN. Infectious diseases control"
    ],
    [
      "openalex",
      "2713|Data-Driven Disease Surveillance"
    ]
  ],
  "openalex": "W7223701717",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13699753/pdf/?tool=EBI",
  "pmcid": "PMC13699753",
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/ds61xmg7x6bth.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:19Z",
      "native_id": "PMC13699753",
      "source": "pmc",
      "url": "https://doi.org/10.1093/eurpub/ckag169.1641"
    },
    {
      "first_seen": "2026-10-30T12:21:45Z",
      "native_id": "PMC:PMC13699753",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13699753"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2713|Data-Driven Disease Surveillance",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "SALGINTR: Digital Participatory ILI Surveillance System Among Physicians in Türkiye-Proof of Concept",
  "title_text": "SALGINTR: Digital Participatory ILI Surveillance System Among Physicians in Türkiye-Proof of Concept",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:36:17Z",
  "url": "https://research.draconitic.com/paper/ds61xmg7x6bth",
  "venue": "The European Journal of Public Health",
  "versions": []
}