SpatialEpiApp is a Shiny web application that allows to visualize spatial and spatio-temporal disease data, estimate disease risk and detect clusters. The application incorporates modules for
Disease risk estimation using INLA
Detection of clusters using the scan statistics implemented in SaTScan
Interactive visualizations such as maps supporting padding and zooming and tables that allow for filtering
Generation of reports containing the analyses performed
Users with R
The application is implemented in the R package SpatialEpiApp. The development version from Github can be launched by executing the following code:
library(devtools) install_github("Paula-Moraga/SpatialEpiApp") library(SpatialEpiApp) run_app()
Users without R
If you do not have R installed you can see how the application works here. You just need to select the ‘Use sample data’ option and click the ‘Start analysis’ button on the right to see an example of lung cancer in Ohio. This is just the visualization part. To estimate risk and detect clusters you need R.
Analyze your own data
To analyze your own data you need to upload two files: 1) the map and 2) the data.
- Map: shapefile with the areas of the study region. The shapefile has to have columns for the area id and the area name.
- Data: csv file with cases and population for each area, time, and individual level covariates (for example age, sex). If areal level covariates are used, specify cases and population for each area and time, and the values of the covariates (for example socio economic index).
- The ids of the areas in the csv file have to be the same as the ids of the areas in the shapefile (so data and map can be linked).
- Time can be year, month or day but all dates have to be consecutive. For example, if we work with years from 2000 to 2010 we need information of all years 2000, 2001, 2002, … and 2010. The app does not work if we have, for example, years 2000, 2005 and 2010 only.