Soon, the book "Building a Platform for Data-Driven Pandemic Prediction: From Data Modeling to Visualization - The CovidLP Project" will be released by the publisher Chapman & Hall/CRC, edited by DEST/UFMG professors Dani Gamerman, Marcos Prates, Vinícius Mayrink and Thaís Paiva, along with several collaborators, among them students of the graduate program in Statistics.
About the book:
- It is one of the results of the CovidLP project of short and long term predictions for COVID-19, which started to be developed at DEST in March 2020.
- It covers the construction of pandemic prediction platforms, providing an overview of probabilistic prediction for fully data-based modeling, and the use of tools such as R, Shiny and interactive plotting programs.
- Readers can follow different reading paths throughout the book, depending on their needs. Key audiences include applied statisticians, biostatisticians, computer scientists, epidemiologists, and practitioners interested in learning more about epidemic modeling in general, including the COVID-19 pandemic, and platform building.
Check out our website to stay updated on the book's release in September!