Multivariate Disease Mapping

Multivariate Disease Mapping is a statistical modeling framework within Bayesian disease mapping that jointly analyzes multiple related diseases or health outcomes across spatial units to improve estimation accuracy and uncover shared spatial patterns, distinguishing itself from univariate approaches by accounting for inter-disease correlations and borrowing strength across outcomes.

19

Publications

733

Citations

39

Authors

29

Institutions

Publications per year

2017–2026

6

Variants

Multivariate Spatial Disease Mapping

Authors

39

  1. MA
    Miguel A. Martínez‐Beneito

    Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Spain

    4 publications · 181 citations

    4

    h-index

  2. YC
    Ying C. MacNab

    University of British Columbia, Canada

    4 publications · 165 citations

    4

    h-index

  3. SB
    Sudipto Banerjee

    University of Minnesota, United States

    3 publications · 198 citations

    3

    h-index

  4. VS
    Volker Schmid

    University of Basel, Switzerland

    2 publications · 59 citations

    2

    h-index

  5. AK
    Amir Kavousi

    Shahid Beheshti University of Medical Sciences, Iran

    2 publications · 59 citations

    2

    h-index

1–5 of 39

Venues

  1. Statistics in Medicine

    4 publications · 137 citations

    4

    h-index

  2. Statistical Methods in Medical Research

    3 publications · 185 citations

    3

    h-index

  3. PubMed

    Repository · 2 publications · 59 citations

    2

    h-index

  4. PLoS ONE

    1 publications · 27 citations

    1

    h-index

  5. Biometrika

    1 publications · 78 citations

    1

    h-index

1–5