Small area disease risk estimation and visualization using R

Paula Moraga

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Small area disease risk estimation is essential for disease prevention and control. In this paper, we demonstrate how R can be used to obtain disease risk estimates and quantify risk factors using areal data. We explain how to define disease risk models and how to perform Bayesian inference using the INLA package. We also show how to make interactive maps of estimates using the leaflet package to better understand the disease spatial patterns and communicate the results. We show an example of lung cancer risk in Pennsylvania, United States, in year 2002, and demonstrate that R represents an excellent tool for disease surveillance by enabling reproducible health data analysis.
Original languageEnglish
Pages (from-to)495-506
JournalThe R Journal
Volume10
Issue number1
Early online date7 Jun 2018
DOIs
Publication statusE-pub ahead of print - 7 Jun 2018

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