SpatialEpiApp: Effortless Analysis of Spatial and Spatio-temporal Disease Data
★ ★ ★ ★ ★ | 2 reviews | 8 users
About the app
SpatialEpiApp is an application designed for visualizing spatial and spatio-temporal disease data, estimating disease risk, and identifying clusters. It integrates modules for disease risk estimation using Bayesian hierarchical models with INLA, cluster detection using scan statistics in SaTScan, and interactive visualizations including maps with zooming and panning, and filterable tables. The app also enables report generation summarizing the analyses conducted. SpatialEpiApp facilitates user interaction through R packages like Leaflet for maps, dygraphs, and more. This tool is particularly valuable for health surveillance researchers lacking advanced statistical and programming skills. With SpatialEpiApp, users can easily upload maps and data, and more. It serves as a comprehensive app for disease risk estimation, cluster detection, and interactive spatial and spatio-temporal visualization. Original publication: Paula Moraga. Spat Spatiotemporal Epidemiol. 2017 Nov:23:47-57.
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App Updates and Comments
App creator
1 years ago
Check the original publication! In this paper we presented SpatialEpiApp, a Shiny web application for the analysis of spatial and spatio-temporal disease data. The application is easy to use and allows health researchers to perform sophisticated surveillance analyses without the need of having advanced statistical or programming skills. Specifically, it allows to obtain disease risk estimates and their uncertainty by fitting Bayesian models with R-INLA, and to detect clusters by using SaTScan.
App creator
1 years ago
Example data to test the app is located at https://github.com/Paula-Moraga/SpatialEpiApp/tree/master/inst/SpatialEpiApp/data/Ohio
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