Threshold-based Alerting

Threshold-Based Alerting is an outbreak detection strategy in which automated alerts are generated when monitored epidemiological indicators exceed predefined quantitative thresholds, distinguishing it from model-based or adaptive methods that infer anomalies from learned patterns or probabilistic forecasts.

214

Publications

9.8K

Citations

854

Authors

400

Institutions

Publications per year

2017–2026

83

Authors

854

  1. SS
    Samuele Segoni

    University of Florence, Italy

    4 publications · 227 citations

    4

    h-index

  2. JK
    James K. Kuchar

    Massachusetts Institute of Technology, United States

    4 publications · 174 citations

    4

    h-index

  3. DL
    David L. Buckeridge

    McGill University, Canada

    3 publications · 255 citations

    3

    h-index

  4. FC
    Filippo Catani

    University of Florence, Italy

    3 publications · 191 citations

    3

    h-index

  5. AR
    Ascanio Rosi

    University of Florence, Italy

    3 publications · 191 citations

    3

    h-index

1–5 of 854

Venues

  1. Computers & Security

    5 publications · 156 citations

    5

    h-index

  2. Sensors

    4 publications · 196 citations

    4

    h-index

  3. Malaria Journal

    3 publications · 139 citations

    3

    h-index

  4. Scientific Reports

    3 publications · 196 citations

    3

    h-index

  5. PubMed

    Repository · 3 publications · 37 citations

    3

    h-index

1–5