In the GeoHealth research group, we develop frontier geospatial methods and computational tools to solve challenging problems in public health and make a positive impact on the world.
- Ph.D. Mathematics, University of Valencia.
- M.S. Biostatistics, Harvard University.
Honors and Awards
- 2012 Extraordinary Doctoral Award, University of Valencia.
- 2010 "La Caixa" Fellowship for postgraduate studies at Harvard University.
- 2009 "Ibercaja" Research Fellowship at Harvard Medical School.
Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny, ISBN 9780367357955
SpatialEpiApp, is a Shiny web application that allows to visualize spatial and spatio-temporal disease data, estimate disease risk and detect clusters.
Dr. Paula Moraga is an Assistant Professor in Statistics for Public Health and the Principal Investigator of the Geospatial Statistics and Health Surveillance research group.
- Geospatial data analysis and health surveillance
- Spatio-temporal disease data
- Statistics and spatial epidemiology
- Geospatial modeling
- Disease mapping
Education and early career
Dr. Paula Moraga graduated in Mathematics from the University of Valencia with an Erasmus year abroad at the Johannes Gutenberg University of Mainz. Following graduation, she worked in a technological company developing algorithms for optimal investment strategies. After that, she enrolled in the Ph.D. program in Statistics at the University of Valencia and worked at the office for regional statistics and the national childhood cancer registry. During her doctoral studies, she was awarded the prestigious "la Caixa" Fellowship for studying her Master's degree in Biostatistics at Harvard University, and this complemented her mathematical background with a solid knowledge in biostatistics and epidemiology. Dr. Moraga also received an Ibercaja Research Fellowship to carry out a research project at Harvard Medical School, a stipend from Google Summer of Code to write code for the R project and completed a traineeship at the European Center for Disease Prevention and Control (ECDC). After obtaining her Ph.D. with Extraordinary Award, Dr. Moraga was appointed to academic statistics positions at the University of Bath, Lancaster University, Queensland University of Technology, London School of Hygiene & Tropical Medicine, and Harvard School of Public Health.
Areas of expertise and current scientific interests
Dr. Moraga's research focuses on the development of innovative statistical methods and computational tools for geospatial data analysis and health surveillance and has directly informed strategic policy in reducing disease burden in several countries. Her projects include the development of modeling architectures to understand the spatio-temporal patterns and identify targets for intervention of malaria in Africa, leptospirosis in Brazil, and cancer in Australia. Dr. Moraga has worked on the development of a number of R packages for disease modeling, detection of clusters, and risk assessment of travel-related spread of disease, and she is the author of SpatialEpiApp, a Shiny web application for the analysis of spatial and spatio-temporal disease data. Dr. Moraga has taught statistics and spatial epidemiology courses at both undergraduate and graduate levels at universities in the United Kingdom, Australia, and Ethiopia, and has been invited to deliver training courses on geospatial modeling, disease mapping, the development of interactive visualization applications.
Dr. Moraga is a member of the R Epidemics Consortium (RECON), a group of international experts to create the next generation of analysis tools for disease outbreak response. She is also a member of the National Aeronautics and Space Administration (NASA) Datanauts, an international community of people interested in learning how to develop data science skills through access to and use of NASA's open data, and a member of R-Ladies Global, a worldwide organization to promote gender diversity in the R community.
Why geospatial statistics and health surveillance?
Geospatial statistics is crucial to solve challenging problems that arise in a variety of fields such as epidemiology, ecology and the environment. For example, it is important to estimate disease burden, assess air quality, predict the occurrence of species, and evaluate and monitor the United Nations Sustainable Development Goals. I am enthusiastic about working on innovative geospatial methods and computational tools that improve decision-making and have a great impact on the health and wellbeing of the population.
KAUST is a world-class research-intensive university that provides unparalleled resources and support to reach your full potential and deliver a real impact in the world.