The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) Forecasting System is a set of tools coded in free, open-access software, that integrate surveillance and environmental data to model and create short-term forecasts for environmentally-mediated diseases. The updated EPIDEMIA forecasting system now is a core set of two packages for supplying functions, epidemiar and clusterapply, and a demonstration data project, epidemiar-demo, for simulated data and example scripts. There is also a fourth package available, epidemia-gee, that demonstrates the ability to connect directly to Google Earth Engine from R via python (with a sample script included in epidemiar-demo).
epidemiar version 3.1.1
Thin plate splines are now frozen at the end of known data to prevent edge effects.
New report_settings parameter fc_cyclicals_by to control if the seasonal cyclicals are calculated by 'cluster' (default) or 'group' (geogroup)
For Farrington event detection: now the adaptive historical years of data to include (to include the maximum number of years data available; b parameter) is calculated per week per geogroup. In addition, individual geogroup Farrington model failures will fail more gracefully without terminating the forecasting.
We suggest installing using remotes::install_github() function.
remotes::install_github("ecograph/[email protected]", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"))
If you are not installing via remotes::install_github(), and you are installing from the binary/source files: make sure that you have all the package dependencies installed (listed in the DESCRIPTION), as this does not automagically happen.
See the included package vignettes, and also epidemiar-demo for a full demo and walkthrough of how to create environmentally-mediated disease forecast reports. Package vignettes are also attached to this release in pdf form.
Other EPIDEMIA system items:
epidemiar: https://github.com/EcoGRAPH/epidemiar/releases/latest
clusterapply: https://github.com/EcoGRAPH/clusterapply/releases/latest
epidemiar-demo: https://github.com/EcoGRAPH/epidemiar-demo/releases/latest
epidemia-gee: https://github.com/EcoGRAPH/epidemia_gee/releases/latest