Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

Journal: Revista brasileira de epidemiologia = Brazilian journal of epidemiology
Published Date: May 13, 2024

Abstract

OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in the area. We also aimed to train a machine learning model to differentiate municipalities classified as hot spots vs. non-hot spots using disease surveillance variables as predictors.

Authors

  • Luis Silva
    Division of Biological and Environmental Sciences and Engineering, Red Sea Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
  • Luise Gomes da Motta
    Universidade Federal Fluminense - Niterói (RJ), Brazil.
  • Lynn Eberly
    University of Minnesota, Minneapolis - Minneapolis (MN), United States.

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