Surveillance-based Forecasting

Surveillance-Based Forecasting is a disease forecasting approach that systematically leverages data from ongoing public health monitoring systems to predict the trajectory and burden of infectious diseases, distinguished by its reliance on real-time or near-real-time observational data streams rather than experimental or model-simulated inputs.

81

Publications

5K

Citations

360

Authors

188

Institutions

Publications per year

2017–2026

55

Authors

360

  1. JS
    John S. Brownstein

    Boston Children's Hospital, United States

    5 publications · 713 citations

    5

    h-index

  2. MS
    Mauricio Santillana

    Harvard University, United States

    4 publications · 693 citations

    4

    h-index

  3. JS
    Jeffrey Shaman

    Columbia University, United States

    4 publications · 401 citations

    4

    h-index

  4. PM
    Philip M. Polgreen

    University of Iowa, United States

    3 publications · 105 citations

    3

    h-index

  5. JM
    James M. McCaw

    The University of Melbourne, Australia

    3 publications · 115 citations

    3

    h-index

1–5 of 360

Venues

  1. PLoS Computational Biology

    7 publications · 759 citations

    7

    h-index

  2. PLoS ONE

    6 publications · 862 citations

    6

    h-index

  3. Scientific Reports

    4 publications · 162 citations

    4

    h-index

  4. 3

    h-index

  5. PubMed

    Repository · 3 publications · 491 citations

    3

    h-index

1–5