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Bayesian Computational Statistics and Modeling
BAYESCOMP
Bayesian Computational Statistics and Modeling

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Public health surveillance

Geospatial Data Science for Public Health Surveillance

Paula Moraga, Assistant Professor, Statistics

Mar 9, 11:15 - 12:45

B4/5 L0 A0215; Zoom Meeting 94713495879

Geospatial Data Public Health Public health surveillance geospatial statistics statistical methods

This talk presents an overview of our research on innovative statistical methods and computational tools for geospatial data analysis and health surveillance, and how this work has directly informed strategic policy to reduce disease burden.

Paula Moraga

Assistant Professor, Statistics

Spatial and spatio-temporal statistics geospatial modeling Spatial epidemiology Bayesian disease mapping point processes Public health surveillance

Dr. Moraga develops innovative statistical methods and computational tools for geospatial data analysis and health surveillance. The impact of her work has directly informed strategic policy in reducing the burden of diseases such as malaria and cancer in several countries.

Bayesian Computational Statistics and Modeling (BAYESCOMP)

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